Publikationer Kommunikationssystem
Journal papers
Backscatter communication (BC) is a promising technique for future Internet-of-Things (IoT) owing to its low complexity, low cost, and potential for energy-efficient operation in sensor networks. There are several network infrastructure setups that can be used for BC with IoT nodes. One of them is the bistatic setup where typically there is a need for high dynamic range and high-resolution analog-to-digital converters at the reader. In this paper, we investigate a bistatic BC setup with multiple antennas. We propose a novel transmission scheme, which includes a protocol for channel estimation at the carrier emitter (CE) as well as a transmit beamformer construction that suppresses the direct link interference between the two ends of a bistatic link (namely CE and reader), and increases the detection performance of the backscatter device (BD) symbol. Further, we derive a generalized log-likelihood ratio test (GLRT) to detect the symbol/presence of the BD. We also provide an iterative algorithm to estimate the unknown parameters in the GLRT. Finally, simulation results show that the required dynamic range of the system is significantly decreased, and the detection performance of the BD symbol is increased, by the proposed algorithm compared to a system not using beamforming at the CE.
@article{diva2:1851979,
author = {Kaplan, Ahmet and Vieira, Joao and Larsson, Erik G},
title = {{Direct Link Interference Suppression for Bistatic Backscatter Communication in Distributed MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2024},
volume = {23},
number = {2},
pages = {1024--1036},
}
This brief introduces a compensation structure for frequency response mismatch (FRM) errors in two-channel time-interleaved analog-to-digital converters (TI-ADCs) based on polynomial models of the channel frequency responses. It can be used for any Nyquist band and it comprises parallel error approximation branches (EABs), each branch consisting of a fixed differentiator of unique degree cascaded with a variable multiplier and a simple modulator. It suffices to alter the variable multipliers when the channels change, thereby avoiding online filter design. In addition, it achieves a lower latency and a significantly lower computational complexity compared to cascaded polynomial-based structures. Numerical simulations and comparisons are included, validating the efficacy of the proposed structure.
@article{diva2:1851978,
author = {Deng, Mingxin and Johansson, Håkan and Wang, Yinan and Li, Zhiwei and Xu, Hui},
title = {{Efficient Parallel Polynomial-Based Compensation Structure for Frequency Response Mismatch in Two-Channel TI-ADCs}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2024},
volume = {71},
number = {2},
pages = {992--996},
}
Distributed antennas must be phase-calibrated (phase-synchronized) for certain operations, such as reciprocity-based joint coherent downlink beamforming, to work. We use rigorous signal processing tools to analyze the accuracy of calibration protocols that are based on over-the-air measurements between antennas, with a focus on scalability aspects for large systems. We show that (i) for some who-measures-on-whom topologies, the errors in the calibration process are unbounded when the network grows; and (ii) despite that conclusion, it is optimal - irrespective of the topology - to solve a single calibration problem for the entire system and use the result everywhere to support the beamforming. The analyses are exemplified by investigating specific topologies, including lines, rings, and two-dimensional surfaces.
@article{diva2:1851111,
author = {Larsson, Erik G},
title = {{Massive Synchrony in Distributed Antenna Systems}},
journal = {IEEE Transactions on Signal Processing},
year = {2024},
volume = {72},
pages = {855--866},
}
We study an opinion dynamics model in which each agent takes a random Bernoulli distributed action whose probability is updated at each discrete time step, and we prove that this model converges almost surely to consensus. We also provide a detailed critique of a claimed proof of this result in the literature. We generalize the result by proving that the assumption of irreducibility in the original model is not necessary. Furthermore, we prove as a corollary of the generalized result that the almost sure convergence to consensus holds also in the presence of a stubborn agent which never changes its opinion. In addition, we show that the model, in both the original and generalized cases, converges to consensus also in $r$th mean.
@article{diva2:1846986,
author = {Abrahamsson, Olle and Danev, Danyo and Larsson, Erik G},
title = {{Strong Convergence of a Random Actions Model in Opinion Dynamics}},
journal = {IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS},
year = {2024},
volume = {10},
pages = {147--161},
}
Cell-free massive multiple-input multiple-output (MIMO) is a promising technology for next-generation communication systems. This work proposes a novel partially coherent (PC) transmission framework to cope with the challenge of phase misalignment among the access points (APs), which is important for unlocking the full potential of cell-free massive MIMO technology. With the PC operation, the APs are only required to be phase-aligned within clusters. Each cluster transmits the same data stream towards each user equipment (UE), while different clusters send different data streams. We first propose a novel algorithm to group APs into clusters such that the distance between two APs is always smaller than a reference distance ensuring the phase alignment of these APs. Then, we propose new algorithms that optimize the combining at UEs and precoding at APs to maximize the downlink sum data rates. We also propose a novel algorithm for data stream allocation to further improve the sum data rate of the PC operation. Numerical results show that the PC operation using the proposed framework with a sufficiently small reference distance can offer a sum rate close to the sum rate of the ideal fully coherent (FC) operation that requires network-wide phase alignment. This demonstrates the potential of PC operation in practical deployments of cell-free massive MIMO networks.
@article{diva2:1842766,
author = {Kunnath Ganesan, Unnikrishnan and Vu, Tung Thanh and Larsson, Erik G.},
title = {{Cell-Free Massive MIMO With Multi-Antenna Users and Phase Misalignments: A Novel Partially Coherent Transmission Framework}},
journal = {IEEE Open Journal of the Communications Society},
year = {2024},
volume = {5},
pages = {1639--1655},
}
With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated that future wireless networks will jointly serve both FL and downlink non-FL user groups in the same time-frequency resource. While in the downlink of each FL iteration, both groups simultaneously receive data from the base station in the same time-frequency resource, the uplink of each FL iteration requires bidirectional communication to support uplink transmission for FL users and downlink transmission for non-FL users. To overcome this challenge, we present half-duplex (HD) and full-duplex (FD) communication schemes to serve both groups. More specifically, we adopt the massive multiple-input multiple-output technology and aim to maximize the minimum effective rate of non-FL users under a quality of service (QoS) latency constraint for FL users. Since the formulated problem is nonconvex, we propose a power control algorithm based on successive convex approximation to find a stationary solution. Numerical results show that the proposed solutions perform significantly better than the considered baselines schemes. Moreover, the FD-based scheme outperforms the HD-based counterpart in scenarios where the self-interference is small or moderate and/or the size of FL model updates is large.
@article{diva2:1840093,
author = {Farooq, Muhammad and Vu, Thanh Tung and Ngo, Hien Quoc and Tran, Le-Nam},
title = {{Massive MIMO for Serving Federated Learning and Non-Federated Learning Users}},
journal = {IEEE Transactions on Wireless Communications},
year = {2024},
volume = {23},
number = {1},
pages = {247--262},
}
In distributed massive multiple-input multiple-output (MIMO) systems, multiple geographically separated access points (APs) communicate simultaneously with a user, leveraging the benefits of multi-antenna coherent MIMO processing and macro-diversity gains from the distributed setups. However, time and frequency synchronization of the multiple APs is crucial to achieve good performance and enable joint precoding. In this paper, we analyze the synchronization requirement among multiple APs from a reciprocity perspective, taking into account the multiplicative impairments caused by mismatches in radio frequency (RF) hardware. We demonstrate that a phase calibration of reciprocity-calibrated APs is sufficient for the joint coherent transmission of data to the user. To achieve synchronization, we propose a novel over-the-air synchronization protocol, named BeamSync, to calibrate the geographically separated APs without sending any measurements to the central processing unit (CPU) through fronthaul. We show that sending the synchronization signal in the dominant direction of the channel between APs is optimal. Additionally, we derive the optimal phase and frequency offset estimators. Simulation results indicate that the proposed BeamSync method enhances performance by 3 dB when the number of antennas at the APs is doubled. Moreover, the method performs well compared to traditional beamforming techniques.
@article{diva2:1839813,
author = {Kunnath Ganesan, Unnikrishnan and Sarvendranath, Rimalapudi and Larsson, Erik G.},
title = {{BeamSync: Over-The-Air Synchronization for Distributed Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2024},
pages = {1--1},
}
The 5th-Generation New Radio (5G-NR) network have been widely deployed around the world in the frequency range 1/range 2 bands. Once specific frequency bands within these ranges can vary across different countries and regions due to regulatory differences, it should be carried out radio network planning to evaluate the 5G coverage considering the particularities of different locations. In this regard, this paper performs a throughly analysis of the following methods for modeling wireless channel propagation in Quito, Ecuador: 3rd Generation Partnership Project, Knife Edge Diffraction (KED), ASTER and Dominant Path model (DPM). Specifically, we focus on KED, ASTER, and DPM for 3.5/28-GHz bands to determine the propagation models in three-Dimensional urban macro scenarios. In the radio network planning, the multiple-input multiple-output array antennas, 2x2/4x4 configuration radiation patterns are deployed using WINPROP tool and 64 x 64 array configuration with the ATOLL tool. 5G frequency specifications, path loss, influence of diffraction, reflection, blocking, and fading between transmitter and receiver have been considered for scenarios of interest, such as dense urban and urban in Quito, by using fixed wireless access applications and Vehicular-to-Everything (V2X) communications. In addition, data rates, throughput, and the quality metrics of the received reference signal, i.e., the signal-to-noise plus interference ratio, the reference signal received quality, the reference signal received power, and the received signal strength indicator, are also assessed for each propagation model. Finally, we provide useful insights into propagation models and design usage rules for the bands mentioned in 5G networks for Quito city.
@article{diva2:1835472,
author = {Guijarro, Valdemar Ramon Farre and Vega Sanchez, Jose David and Paredes, Martha Cecilia Paredes and Arevalo, Felipe Grijalva and Moya Osorio, Diana},
title = {{Comparative Evaluation of Radio Network Planning for Different 5G-NR Channel Models on Urban Macro Environments in Quito City}},
journal = {IEEE Access},
year = {2024},
volume = {12},
pages = {5708--5730},
}
Facing the upcoming era of Internet-of-Things and connected intelligence, efficient information processing, computation, and communication design becomes a key challenge in large-scale intelligent systems. Recently, Over-the-Air (OtA) computation has been proposed for data aggregation and distributed computation of functions over a large set of network nodes. Theoretical foundations for this concept exist for a long time, but it was mainly investigated within the context of wireless sensor networks. There are still many open questions when applying OtA computation in different types of distributed systems where modern wireless communication technology is applied. In this article, we provide a comprehensive overview of the OtA computation principle and its applications in distributed learning, control, and inference systems, for both server-coordinated and fully decentralized architectures. Particularly, we highlight the importance of the statistical heterogeneity of data and wireless channels, the temporal evolution of model updates, and the choice of performance metrics, for the communication design in OtA federated learning (FL) systems. Several key challenges in privacy, security, and robustness aspects of OtA FL are also identified for further investigation.
@article{diva2:1847643,
author = {Chen, Zheng and Larsson, Erik G and Fischione, Carlo and Johansson, Mikael and Malitsky, Yura},
title = {{Over-the-Air Computation for Distributed Systems: Something Old and Something New}},
journal = {IEEE Network},
year = {2023},
volume = {37},
number = {5},
pages = {240--246},
}
We consider high-dimensional MIMO transmissions in frequency division duplexing (FDD) systems. For precoding, the frequency selective channel has to be measured, quantized and fed back to the base station by the users. When the number of antennas is very high this typically leads to prohibitively high quantization complexity and large feedback. In 5G New Radio (NR), a modular quantization approach has been applied for this, where first a low-dimensional subspace is identified for the whole frequency selective channel, and then subband channels are linearly mapped to this subspace and quantized. We analyze how the components in such a modular scheme contribute to the overall quantization distortion. Based on this analysis we improve the technology components in the modular approach and propose an orthonormalized wideband precoding scheme and a sequential wideband precoding approach which provide considerable gains over the conventional method. We compare the performance of the developed quantization schemes to prior art by simulations in terms of the projection distortion, overall distortion and spectral efficiency, in a scenario with a realistic spatial channel model.
@article{diva2:1845841,
author = {Liao, Jialing and Vehkalahti, Roope and Pllaha, Tefjol and Han, Wei and Tirkkonen, Olav},
title = {{Modular CSI Quantization for FDD Massive MIMO Communication}},
journal = {IEEE Transactions on Wireless Communications},
year = {2023},
volume = {22},
number = {12},
pages = {8543--8558},
}
Unmanned aerial vehicles (UAVs) have emerged as a specular technology that can assist the terrestrial base stations. However, the battery limitation of UAV inhibits the system performance by decreasing the overall lifespan of coverage provided by the UAV, driving the necessity of replacement and recharging. Thus, the energy-depleted UAV must be returned to a charging station and be replaced by a fully charged UAV to increase the service span. Therefore, this paper presents a novel framework of UAV replacement to maintain coverage continuity in a UAV-assisted wireless communication system when a serving UAV runs out of energy. Our objective during this replacement process is to maximize the minimum achievable throughput to the UAV-served ground users by jointly optimizing the three-dimensional (3D) multi-UAV trajectory and resources allocated to the users from the individual UAVs. The formulated problem is non-convex for which an efficient algorithm based on successive convex approximation and alternating optimization is proposed. Numerical results provide insights into the UAV trajectories and the effectiveness of the proposed scheme compared to the existing benchmark schemes.
@article{diva2:1840201,
author = {Gupta, Nishant and Agarwal, Satyam and Mishra, Deepak and Kumbhani, Brijesh},
title = {{Trajectory and Resource Allocation for UAV Replacement to Provide Uninterrupted Service}},
journal = {IEEE Transactions on Communications},
year = {2023},
volume = {71},
number = {12},
pages = {7288--7302},
}
The beam-oriented digital predistortion (BO-DPD) is not sufficient to linearize the output from a subarray of power amplifiers (PAs) in different directions except the desired direction. Therefore, subsequent to the BO-DPD operation, we perform a post-weighting (PW) processing to minimize the nonlinear radiations in the wide range of directions under crosstalk. Here, the optimized PW coefficients are multiplied by the polynomial terms of the BO-DPD, then, the resultant signals are distributed to the PAs to compensate the nonlinear radiations. In this work, first, we propose fully-featured post-weighting (FF-PW) scheme, then, we derive a low-complexity post-weighting (LC-PW) scheme.
@article{diva2:1832743,
author = {Prasad, Ganesh and Johansson, Håkan},
title = {{A Low-Complexity Post-Weighting Predistorter in a mMIMO Transmitter Under Crosstalk}},
journal = {IEEE Communications Letters},
year = {2023},
volume = {27},
number = {12},
pages = {3315--3319},
}
An intelligent reflecting surface (IRS) is a cost and energy-efficient solution to improve wireless system performance. Transmit antenna selection (AS) harnesses the benefits of multiple antennas with a smaller number of radio frequency (RF) chains. We focus on joint optimization of antenna subset and transmit beamforming at the transmitter (Tx) and passive beamforming at the IRS to maximize the receive signal power. We derive a closed-form optimal AS rule for a Tx and receiver (Rx) equipped with single RF chain each and ideal IRS. We analyze its performance with a correlated channel model and then extend it to non-ideal IRS. We also propose a simpler rule that significantly reduces the number of computations and pilots. For an Rx that performs maximal ratio combining, we propose a manifold optimization algorithm and a low-complexity selection rule. For a Tx with multiple RF chains, we propose a subset selection algorithm that yields a locally optimal solution and an alternating optimization algorithm that reduces complexity. Our simulations study the impact of estimation errors, discrete phase shifts, and channel correlation on the proposed selection rules, which perform better than the existing AS rules. They also show that the proposed low-complexity rules are near-optimal.
@article{diva2:1830144,
author = {Sarvendranath, Rimalapudi and Chavva, Ashok Kumar Reddy and Larsson, Erik G},
title = {{Optimal Antenna Selection and Beamforming for an IRS Assisted System}},
journal = {IEEE Transactions on Wireless Communications},
year = {2023},
volume = {22},
number = {9},
pages = {5698--5710},
}
The acquisition of the channel covariance matrix is of paramount importance to many strategies in multiple-input-multiple-output (MIMO) communications, such as the minimum mean-square error (MMSE) channel estimation. Therefore, plenty of efficient channel covariance matrix estimation schemes have been proposed in the literature. However, an abrupt change in the channel covariance matrix may happen occasionally in practice due to the change in the scattering environment and the user location. Our paper aims to adopt the classic change detection theory to detect the change in the channel covariance matrix as accurately and quickly as possible such that the new covariance matrix can be re-estimated in time. Specifically, this paper first considers the technique of on-line change detection (also known as quickest/sequential change detection), where we need to detect whether a change in the channel covariance matrix occurs at each channel coherence time interval. Next, because the complexity of detecting the change in a high-dimension covariance matrix at each coherence time interval is too high, we devise a low-complexity off-line strategy in massive MIMO systems, where change detection is merely performed at the last channel coherence time interval of a given time period. Numerical results show that our proposed on-line and off-line schemes can detect the channel covariance change with a small delay and a low false alarm rate. Therefore, our paper theoretically and numerically verifies the feasibility of detecting the channel covariance change accurately and quickly in practice.
@article{diva2:1830087,
author = {Liu, Runnan and Liu, Liang and He, Dazhi and Zhang, Wenjun and Larsson, Erik G},
title = {{Detecting Abrupt Change in Channel Covariance Matrix for MIMO Communication}},
journal = {IEEE Transactions on Wireless Communications},
year = {2023},
volume = {22},
number = {11},
pages = {7834--7847},
}
Future wireless networks are expected to support ubiquitous extended reality (XR) with human-to-human communications. XR is a term that refers to all real-and-virtual combined environments and human-machine interactions generated by computer technology and wearables, where the X represents any current or future spatial computing technology. XR includes augmented reality (AR), mixed reality (MR), and virtual reality (VR) that all are immersive at different levels and entail distinct degrees of sensory inputs. The ultra-high resolution, detailed representation, panoramic scenery, and multi-stimuli of XR provide a unique immersive experience, allowing users to interact within an alternative world. Transmitting XR video, with its ultra-high bit rate and low latency, presents critical challenges to wireless networking.
@article{diva2:1821678,
author = {Wu, Yongpeng and Larsson, Erik G and Li, Jing and Lozano, Angel and Morin, Luce and Xu, Mai and Xiao, Chengshan and Yang, Wei},
title = {{Guest Editorial Signal Processing for XR Communications and Systems}},
journal = {IEEE Journal on Selected Topics in Signal Processing},
year = {2023},
volume = {17},
number = {5},
pages = {913--918},
}
IntroductionBreast cancer is the most common malignant tumor among women. Mammography is the specific type of X-ray recommended to examine the breasts. However, they are difficult to interpret due to the size of the lesions, shape, indefinite borders, and low contrast of the masses with respect to healthy tissue, mainly in very dense breasts. Computer-aided detection (CAD) systems increase the efficiency of diagnoses and reduce the workload of specialists.PurposeA CAD system that uses artificial intelligence (AI) based on "You Only Look Once" (YOLO), with two models YOLOv5x and YOLOv5s, is tested for the detection of breast nodules from mammography.MethodTransfer learning and data augmentation techniques were applied. Image sets for training and validation were created from an international database (Vindr-Mammo). The network was trained and validated, and for the best model obtained, an external test was performed from a second database belonguing to "The Mammographic Image Analysis Society" (MIAS Database).ResultsThe best model was obtained with YOLOv5x. This reached a maximum sensitivity of 80% in internal validation and 72% with external test data.ConclusionYOLOv5x and YOLOv5s models showed potential for the task of detecting masses from mammographies.
@article{diva2:1809970,
author = {Quinones-Espin, Alejandro Ernesto and Perez-Diaz, Marlen and Espin-Coto, Rafaela Mayelin and Rodríguez Linares, Deijany and Lopez-Cabrera, Jose Daniel},
title = {{Automatic detection of breast masses using deep learning with YOLO approach}},
journal = {Health and Technology},
year = {2023},
volume = {13},
number = {6},
pages = {915--923},
}
The emerging concept of Over-the-Air (OtA) computation has shown great potential for achieving resource-efficient data aggregation across large wireless networks. However, current research in this area has been limited to the standard many-to-one topology, where multiple nodes transmit data to a single receiver. In this letter, we address the problem of applying OtA computation to scenarios with multiple receivers, and propose a novel communication design that exploits joint precoding and decoding over multiple time slots. To determine the optimal precoding and decoding vectors, we formulate an optimization problem that aims to minimize the mean squared error of the desired computations while satisfying the unbiasedness condition and power constraints. Our proposed multi-slot design is shown to be effective in saving communication resources (e.g., time slots) and achieving smaller estimation errors compared to the baseline approach of separating different receivers over time.
@article{diva2:1795399,
author = {Chen, Zheng and Malitskyi, Yurii},
title = {{Over-the-Air Computation With Multiple Receivers: A Space-Time Approach}},
journal = {IEEE Wireless Communications Letters},
year = {2023},
volume = {12},
number = {8},
pages = {1399--1403},
}
We consider network-assisted full-duplex (NAFD) cell-free massive multiple-input multiple-output (CF-mMIMO) systems, where full-duplex (FD) transmission is virtually realized via half-duplex (HD) hardware devices. The HD access points (APs) operating in uplink (UL) mode and those operating in downlink (DL) mode simultaneously serve DL and UL user equipments (UEs) in the same frequency bands. We comprehensively analyze the performance of NAFD CF-mMIMO from both a spectral efficiency (SE) and energy efficiency (EE) perspectives. Specifically, we propose a joint optimization approach that designs the AP mode assignment, power control, and large-scale fading (LSFD) weights to improve the sum SE and EE of NAFD CF-mMIMO systems. We formulate two mixed-integer nonconvex optimization problems of maximizing the sum SE and EE, under realistic power consumption models, and the constraints on minimum individual SE requirements, maximum transmit power at each DL AP and UL UE. The challenging formulated problems are transformed into tractable forms and two novel algorithms are proposed to solve them using successive convex approximation techniques. More importantly, our approach can be applied to jointly optimize power control and LSFD weights for maximizing the sum SE and EE of HD and FD CF-mMIMO systems, which, to date, has not been studied. Numerical results show that: (a) our joint optimization approach significantly outperforms the heuristic approaches in terms of both sum SE and EE; (b) in CF-mMIMO systems, the NAFD scheme can provide approximately 30% SE gains, while achieving a remarkable EE gain of up to 200% compared with the HD and FD schemes.
@article{diva2:1794259,
author = {Mohammadi, Mohammadali and Vu, Thanh Tung and Ngo, Hien Quoc and Matthaiou, Michail},
title = {{Network-Assisted Full-Duplex Cell-Free Massive MIMO: Spectral and Energy Efficiencies}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2023},
volume = {41},
number = {9},
pages = {2833--2851},
}
Antenna arrays can be either reciprocity calibrated (R-calibrated), which facilitates reciprocity-based beamforming, or fully calibrated (F-calibrated), which additionally facilitates transmission and reception in specific physical directions. We first expose, to provide context, the fundamental principles of over-the-air R-and F-calibration of distributed arrays. We then describe a new method for calibration of two arrays that are individually F-calibrated, such that the combined array becomes jointly F-calibrated.
@article{diva2:1791318,
author = {Larsson, Erik G and Vieira, Joao},
title = {{Phase Calibration of Distributed Antenna Arrays}},
journal = {IEEE Communications Letters},
year = {2023},
volume = {27},
number = {6},
pages = {1619--1623},
}
Wireless communication technology has progressed dramatically over the past 25 years, in terms of societal adoption as well as technical sophistication. In 1998, mobile phones were still in the process of becoming compact and affordable devices that could be widely utilized in both developed and developing countries. There were "only" 300 million mobile subscribers in the world [1]. Cellular networks were among the first privatized telecommunication markets, and competition turned the devices into fashion accessories with attractive designs that could be individualized. The service was circumscribed to telephony and text messaging, but it was groundbreaking in that, for the first time, telecommunication was between people rather than locations.
@article{diva2:1791227,
author = {Bjornson, Emil and Eldar, Yonina C. and Larsson, Erik G and Lozano, Angel and Poor, H. Vincent},
title = {{Twenty-Five Years of Signal Processing Advances for Multiantenna Communications: From theory to mainstream technology}},
journal = {IEEE signal processing magazine (Print)},
year = {2023},
volume = {40},
number = {4},
pages = {107--117},
}
Digital differentiators enable the computation of the derivative of a continuous-time signal at discrete time instances, and they are used in many signal processing applications. This paper derives a unified filter order estimate for digital differentiators that are realized with linear-phase finite-length impulse response filters and designed in the minimax sense. The estimate is useful at the high-level system design when assessing the implementation complexity and it enables fewer designs when finding the minimal filter order required to satisfy a prescribed tolerable approximation error. The proposed unified estimate covers both wideband and lowpass differentiators of integer degrees up to ten. Furthermore, degree-individual filter order estimates are derived which improve and extend previous results. The performance of both the unified and degree-individual order estimates is evaluated through simulation examples and compared with previous estimates.
@article{diva2:1789181,
author = {Wang, Yinan and Deng, Mingxin and Johansson, Håkan and Li, Zhiwei and Li, Qingjiang},
title = {{Unified Filter Order Estimate for Minimax-Designed Linear-Phase FIR Wideband and Lowpass Digital Differentiators}},
journal = {Circuits, systems, and signal processing},
year = {2023},
volume = {42},
number = {11},
pages = {6966--6987},
}
Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified to stimulate the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed.
@article{diva2:1775943,
author = {Wang, Cheng-Xiang and You, Xiaohu and Gao, Xiqi and Zhu, Xiuming and Li, Zixin and Zhang, Chuan and Wang, Haiming and Huang, Yongming and Chen, Yunfei and Haas, Harald and Thompson, John S. and Larsson, Erik G and Di Renzo, Marco and Tong, Wen and Zhu, Peiying and Shen, Xuemin and Poor, H. Vincent and Hanzo, Lajos},
title = {{On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds}},
journal = {IEEE Communications Surveys and Tutorials},
year = {2023},
volume = {25},
number = {2},
pages = {905--974},
}
The usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high-energy beamforming (EB) gains. Considering the limited computational capability and constant-envelope precoding for PIS, we propose three novel low-complexity passive EB designs for optimizing the efficacy of PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. The first EB design involves solving a univariate equation, and closed forms expressed are presented for the other two. Further, to maximize the practical utility of PET, we introduce a novel channel estimation (CE) protocol for obtaining least-squares estimators for the channels as required for EB designing. Using them, we also derive closed-form expressions for optimal PIS location and optimal time allocation between CE and PET within each coherence block to maximize the users net harvested energy. Numerical results verify the CE analysis and validate the novel analytical bound derived for received power during PET and proposed PIS designs quality against existing benchmarks. We show that the proposed jointly optimal design for PET can yield a significant improvement of about 15 dB, and a reduced active array size at PB can achieve the desired EB gain with sufficient passive elements at PIS. Finally, we also briefly discuss how the proposed CE and EB designs can be extended to the multiuser settings.
@article{diva2:1765854,
author = {Mishra, Deepak and Johansson, Håkan},
title = {{Low-Complexity Beamforming Designs and Channel Estimation for Passive-Intelligent-Surface-Assisted MISO Energy Transfer}},
journal = {IEEE Internet of Things Journal},
year = {2023},
volume = {10},
number = {9},
pages = {8286--8304},
}
Many real-world scenarios for massive machine-type communication involve sensors monitoring a physical phenomenon. As a consequence, the activity pattern of these sensors will be correlated. In this letter, we study how the correlation of user activities can be exploited to improve detection performance in grant-free random access systems where the users transmit pilot-hopping sequences and the detection is performed based on the received energy. We show that we can expect considerable performance gains by adding regularizers, which take the activity correlation into account, to the non-negative least squares, which has been shown to work well for independent user activity.
@article{diva2:1755182,
author = {Becirovic, Ema and Bjornson, Emil and Larsson, Erik G},
title = {{Activity Detection in Distributed Massive MIMO With Pilot-Hopping and Activity Correlation}},
journal = {IEEE Wireless Communications Letters},
year = {2023},
volume = {12},
number = {2},
pages = {272--276},
}
Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents. In this work, we propose an asynchronous FL design with periodic aggregation to tackle the straggler issue in FL systems. Considering limited wireless communication resources, we investigate the effect of different scheduling policies and aggregation designs on the convergence performance. Driven by the importance of reducing the bias and variance of the aggregated model updates, we propose a scheduling policy that jointly considers the channel quality and training data representation of user devices. The effectiveness of our channel-aware data-importance-based scheduling policy, compared with state-of-the-art methods proposed for synchronous FL, is validated through simulations. Moreover, we show that an "age-aware" aggregation weighting design can significantly improve the learning performance in an asynchronous FL setting.
@article{diva2:1754629,
author = {Hu, Chung-Hsuan and Chen, Zheng and Larsson, Erik G},
title = {{Scheduling and Aggregation Design for Asynchronous Federated Learning Over Wireless Networks}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2023},
volume = {41},
number = {4},
pages = {874--886},
}
This paper considers a single-cell massive MIMO (multiple-input multiple-output) system with dual-polarized antennas at both the base station and users. We study a channel model that includes the key practical aspects that arise when utilizing dual-polarization: channel cross-polar discrimination (XPD) and cross-polar correlations (XPC) at the transmitter and receiver. We derive the achievable uplink and downlink spectral efficiencies (SE) with and without successive interference cancellation (SIC) when using the linear minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio (MR) combining/precoding schemes. The expressions depend on the statistical properties of the MMSE channel estimator obtained for the dual-polarized channel model. Closed-form uplink and downlink SE expressions for MR combining/precoding are derived. Using these expressions, we propose power-control algorithms that maximize the uplink and downlink sum SEs under uncorrelated fading but can be used to enhance performance also with correlated fading. We compare the SEs achieved in dual-polarized and uni-polarized setups numerically and evaluate the impact of XPD and XPC conditions. The simulations reveal that dual-polarized setups achieve 40-60% higher SEs and the gains remain also under severe XPD and XPC. Dual-polarized also systems benefit more from advanced signal processing that compensates for imperfections.
@article{diva2:1750801,
author = {Özdogan, Özgecan and Bjornson, Emil},
title = {{Massive MIMO With Dual-Polarized Antennas}},
journal = {IEEE Transactions on Wireless Communications},
year = {2023},
volume = {22},
number = {2},
pages = {1448--1463},
}
In the current contribution, we examine the feasibility of fully-energy-autonomous operation of reconfigurable intelligent surfaces (RIS) through wireless energy harvesting (EH) from incident information signals. Towards this, we first identify the main RIS energy-consuming components and present a suitable and accurate energy-consumption model that is based on the recently proposed integrated controller architecture and includes the energy consumption needed for channel estimation. Building on this model, we introduce a novel RIS architecture that enables EH through RIS unit-cell (UC) splitting. Subsequently, we introduce an EH policy, where a subset of the UCs is used for beamsteering, while the remaining UCs absorb energy. In particular, we formulate a subset al.ocation optimization problem that aims at maximizing the signal-to-noise ratio (SNR) at the receiver without violating the RISs energy consumption demands. As a problem solution, we present low-complexity heuristic algorithms. The presented numerical results reveal the feasibility of the proposed architecture and the efficiency of the presented algorithms with respect to both the optimal and very high-complexity brute-force approach and the one corresponding to random subset selection. Furthermore, the results reveal how important the placement of the RIS as close to the transmitter as possible is, for increasing the harvesting effectiveness.
@article{diva2:1749819,
author = {Ntontin, Konstantinos and Boulogeorgos, Alexandros-Apostolos A. and Björnson, Emil and Martins, Wallace Alves and Kisseleff, Steven and Abadal, Sergi and Alarcon, Eduard and Papazafeiropoulos, Anastasios and Lazarakis, Fotis I. and Chatzinotas, Symeon},
title = {{Wireless Energy Harvesting for Autonomous Reconfigurable Intelligent Surfaces}},
journal = {IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING},
year = {2023},
volume = {7},
number = {1},
pages = {114--129},
}
We consider distributed average consensus in a wireless network with partial communication to reduce the number of transmissions in every iteration/round. Considering the broadcast nature of wireless channels, we propose a probabilistic approach that schedules a subset of nodes for broadcasting information to their neighbors in every round. We compare several heuristic methods for assigning the node broadcast probabilities under a fixed number of transmissions per round. Furthermore, we introduce a pre-compensation method to correct the bias between the consensus value and the average of the initial values, and suggest possible extensions for our design. Our results are particularly relevant for developing communication-efficient consensus protocols in a wireless environment with limited frequency/time resources.
@article{diva2:1745529,
author = {P\'{e}rez Herrera, Daniel and Chen, Zheng and Larsson, Erik G},
title = {{Distributed Consensus in Wireless Networks With Probabilistic Broadcast Scheduling}},
journal = {IEEE Signal Processing Letters},
year = {2023},
volume = {30},
pages = {41--45},
}
Non-independent and identically distributed (non-IID) data distribution among clients is considered as the key factor that degrades the performance of federated learning (FL). Several approaches to handle non-IID data, such as personalized FL and federated multitask learning (FMTL), are of great interest to research communities. In this work, first, we formulate the FMTL problem using Laplacian regularization to explicitly leverage the relationships among the models of clients for multitask learning. Then, we introduce a new view of the FMTL problem, which, for the first time, shows that the formulated FMTL problem can be used for conventional FL and personalized FL. We also propose two algorithms FedU and decentralized FedU (dFedU) to solve the formulated FMTL problem in communication-centralized and decentralized schemes, respectively. Theoretically, we prove that the convergence rates of both algorithms achieve linear speedup for strongly convex and sublinear speedup of order 1/2 for nonconvex objectives. Experimentally, we show that our algorithms outperform the conventional algorithm FedAvg, FedProx, SCAFFOLD, and AFL in FL settings, MOCHA in FMTL settings, as well as pFedMe and Per-FedAvg in personalized FL settings.
@article{diva2:1723306,
author = {Dinh, Canh T. and Vu, Thanh Tung and Tran, Nguyen H. and Dao, Minh N. and Zhang, Hongyu},
title = {{A New Look and Convergence Rate of Federated Multitask Learning With Laplacian Regularization}},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
year = {2023},
}
We consider a resource-constrained IoT network, where multiple users make on-demand requests to a cache-enabled edge node to send status updates about various random processes, each monitored by an energy harvesting sensor. The edge node serves users requests by deciding whether to command the corresponding sensor to send a fresh status update or retrieve the most recently received measurement from the cache. Our objective is to find the best actions of the edge node to minimize the average age of information (AoI) of the received measurements upon request, i.e., average on-demand AoI, subject to per-slot transmission and energy constraints. First, we derive a Markov decision process model and propose an iterative algorithm that obtains an optimal policy. Then, we develop an asymptotically optimal low-complexity algorithm - termed relax-then-truncate - and prove that it is optimal as the number of sensors goes to infinity. Simulation results illustrate that the proposed relax-then-truncate approach significantly reduces the average on-demand AoI compared to a request-aware greedy policy and a weighted AoI policy, and also depict that it performs close to the optimal solution even for moderate numbers of sensors.
@article{diva2:1743907,
author = {Hatami, Mohammad and Leinonen, Markus and Chen, Zheng and Pappas, Nikolaos and Codreanu, Marian},
title = {{On-Demand AoI Minimization in Resource-Constrained Cache-Enabled IoT Networks With Energy Harvesting Sensors}},
journal = {IEEE Transactions on Communications},
year = {2022},
volume = {70},
number = {11},
pages = {7446--7463},
}
This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL). The synchronous design relies on strict synchronization among users when executing each FL communication round, while the asynchronous design allows more flexibility for users to save energy by using lower computing frequencies. The session-based design splits the downlink and uplink phases in each FL communication round into separate sessions. In this design, we assign users such that one of the participating users in each session finishes its transmission and does not join the next session. As such, more power and degrees of freedom will be allocated to unfinished users, resulting in higher rates, lower transmission times, and hence, higher energy efficiency. In all three designs, we use zero-forcing processing for both uplink and downlink, and develop algorithms that optimize user assignment, time allocation, power, and computing frequencies to minimize the energy consumption at the base station and users, while guaranteeing a predefined maximum execution time of each FL communication round.
@article{diva2:1723907,
author = {Vu, Thanh Tung and Ngo, Hien Quoc and Dao, Minh N. and Ngo, Duy Trong and Larsson, Erik G and Le-Ngoc, Tho},
title = {{Energy-Efficient Massive MIMO for Federated Learning:
Transmission Designs and Resource Allocations}},
journal = {IEEE Open Journal of the Communications Society},
year = {2022},
volume = {3},
pages = {2329--2346},
}
The mobile data traffic has been exponentially growing during the last several decades. This was enabled by the densification of the network infrastructure in terms of increased cell density (i.e., Ultra-Dense Network (UDN)) and/or the increased number of active antennas per Access Point (AP) (i.e., massive Multiple-Input Multiple -Output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations. Cell-Free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each User Equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework to discuss the essential details (i.e., transmission procedure and mathematical system model). Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues in implementing CF mMIMO and point out the potential future directions. Finally, we conclude this paper with a summary of the key lessons learned in this field.
@article{diva2:1720824,
author = {Chen, Shuaifei and Zhang, Jiayi and Zhang, Jing and Björnson, Emil and Ai, Bo},
title = {{A survey on user-centric cell-free massive MIMO systems}},
journal = {Digital Communications and Networks},
year = {2022},
volume = {8},
number = {5},
pages = {695--719},
}
When data are available for all nodes of a Gaussian graphical model, then, it is possible to use sample correlations and partial correlations to test to what extent the conditional independencies that encode the structure of the model are indeed verified by the data. In this paper, we give a heuristic rule useful in such a validation process: When the correlation subgraph involved in a conditional independence is balanced (i.e., all its cycles have an even number of negative edges), then a partial correlation is usually a contraction of the corresponding correlation, which often leads to conditional independence. In particular, the contraction rule can be made rigorous if we look at concentration subgraphs rather than correlation subgraphs. The rule is applied to real data for elementary gene regulatory motifs.
@article{diva2:1714787,
author = {Zenere, Alberto and Larsson, Erik G and Altafini, Claudio},
title = {{Relating balance and conditional independence in graphical models}},
journal = {Physical review. E},
year = {2022},
volume = {106},
number = {4},
}
We develop a new algorithm for activity detection for grant-free multiple access in distributed multiple-input multiple-output (MIMO). The algorithm is a distributed version of the approximate message passing (AMP) based on a soft combination of likelihood ratios computed independently at multiple access points. The underpinning theoretical basis of our algorithm is a new observation that we made about the state evolution in the AMP. Specifically, with a minimum mean-square error denoiser, the state maintains a block-diagonal structure whenever the covariance matrices of the signals have such a structure. We show by numerical examples that the algorithm outperforms competing schemes from the literature.
@article{diva2:1706151,
author = {Bai, Jianan and Larsson, Erik G},
title = {{Activity Detection in Distributed MIMO: Distributed AMP via Likelihood Ratio Fusion}},
journal = {IEEE Wireless Communications Letters},
year = {2022},
volume = {11},
number = {10},
pages = {2200--2204},
}
Intelligent reflecting surface (IRS) and device-to-device (D2D) communication are two promising technologies for improving transmission reliability between transceivers in communication systems. In this paper, we consider the design of reliable communication between the access point (AP) and actuators for a downlink multiuser multiple-input single-output (MISO) system in the industrial IoT (IIoT) scenario. We propose a two-stage protocol combining IRS with D2D communication so that all actuators can successfully receive the message from AP within a given delay. The superiority of the protocol is that the communication reliability between AP and actuators is doubly augmented by the IRS-aided first-stage transmission and the second-stage D2D transmission. A joint optimization problem of active and passive beamforming is formulated, which aims to maximize the number of actuators with successful decoding. We study the joint beamforming problem for cases where the channel state information (CSI) is perfect and imperfect. For each case, we develop efficient algorithms that include convergence and complexity analysis. Simulation results demonstrate the necessity and role of IRS with a well-optimized reflection matrix, and the D2D network in promoting reliable communication. Moreover, the proposed protocol can enable reliable communication even in the presence of stringent latency requirements and CSI estimation errors.
@article{diva2:1698876,
author = {Cheng, Jing and Shen, Chao and Chen, Zheng and Pappas, Nikolaos},
title = {{Robust Beamforming Design for IRS-Aided URLLC in D2D Networks}},
journal = {IEEE Transactions on Communications},
year = {2022},
volume = {70},
number = {9},
pages = {6035--6049},
}
Reciprocity-based time-division duplex (TDD) Massive MIMO (multiple-input multiple-output) systems utilize channel estimates obtained in the uplink to perform precoding in the downlink. However, this method has been criticized of breaking down, in the sense that the channel estimates are not good enough to spatially separate multiple user terminals, at low uplink reference signal signal-to-noise ratios, due to insufficient channel estimation quality. Instead, codebook-based downlink precoding has been advocated for as an alternative solution in order to bypass this problem. We analyze this problem by considering a “grid-of-beams world” with a finite number of possible downlink channel realizations. Assuming that the terminal accurately can detect the downlink channel, we show that in the case where reciprocity holds, carefully designing a mapping between the downlink channel and the uplink reference signals will perform better than both the conventional TDD Massive MIMO and frequency-division duplex (FDD) Massive MIMO approach. We derive elegant metrics for designing this mapping, and further, we propose algorithms that find good sequence mappings.
@article{diva2:1695470,
author = {Becirovic, Ema and Björnson, Emil and Larsson, Erik G.},
title = {{Combining Reciprocity and CSI Feedback in MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2022},
volume = {21},
number = {11},
pages = {10065--10080},
}
This letter considers the development of transmission strategies for the downlink of massive multiple-input multiple-output networks, with the objective of minimizing the completion time of the transmission. Specifically, we introduce a session-based scheme that splits time into sessions and allocates different rates in different sessions for the different users. In each session, one user is selected to complete its transmission and will not join subsequent sessions, which results in successively lower levels of interference when moving from one session to the next. An algorithm is developed to assign users and allocate transmit power that minimizes the completion time. Numerical results show that our proposed session-based scheme significantly outperforms conventional non-session-based schemes.
@article{diva2:1691849,
author = {Vu, Tung T. and Hien, Quoc Ngo and Dao, Minh N. and Matthaiou, Michail and Larsson, Erik G.},
title = {{Data Size-Aware Downlink Massive MIMO: A Session-Based Approach}},
journal = {IEEE Wireless Communications Letters},
year = {2022},
volume = {11},
number = {7},
pages = {1468--1472},
}
A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation of a reduced-dimension data subspace, called principal components (PCs). In this paper, to support one-shot DPCA in wireless systems, we propose a framework of analog MIMO transmission featuring the uncoded analog transmission of local PCs for estimating the global PCs. To cope with channel distortion and noise, two maximum-likelihood (global) PC estimators are presented corresponding to the cases with and without receive channel state information (CSI). The first design, termed coherent PC estimator, is derived by solving a Procrustes problem and reveals the form of regularized channel inversion where the regulation attempts to alleviate the effects of both receiver noise and data noise. The second one, termed blind PC estimator, is designed based on the subspace channel-rotation-invariance property and computes a centroid of received local PCs on a Grassmann manifold. Using the manifold-perturbation theory, tight bounds on the mean square subspace distance (MSSD) of both estimators are derived for performance evaluation. The results reveal simple scaling laws of MSSD concerning device population, data and channel signal-to-noise ratios (SNRs), and array sizes. More importantly, both estimators are found to have identical scaling laws, suggesting the dispensability of CSI to accelerate DPCA. Simulation results validate the derived results and demonstrate the promising latency performance of the proposed analog MIMO.
@article{diva2:1690253,
author = {Chen, Xu and Larsson, Erik G and Huang, Kaibin},
title = {{Analog MIMO Communication for One-Shot Distributed Principal Component Analysis}},
journal = {IEEE Transactions on Signal Processing},
year = {2022},
volume = {70},
pages = {3328--3342},
}
In this paper, two different timing-mismatch compensation strategies for two-channel time-interleaved analog-to-digital converters are comprehensively analyzed and compared. In the first strategy (SA), one channel serves as a reference channel, and the other channel is compensated to match the reference channel using the timing mismatch between the channels. In the second strategy (SB), both channels are compensated to match each other, using half the value of the channel mismatch with different signs. For SB, the paper introduces a novel compensation structure that utilizes parallel differentiator-multiplier (PDM) branches. Expressions for the spurious-free dynamic range (SFDR) after compensation are derived for both strategies. These expressions reveal that the novel PDM structure achieves a remarkably greater SFDR than the existing cascaded differentiator-multiplier (CDM) compensation structure which can be used for both SA and SB. This is because, after compensation, the remaining aliasing distortion in the proposed PDM structure is shown to be of higher approximation order (in terms of the mismatch value) and thus substantially smaller than in the CDM structure. Simulations included in the paper validate the theoretical results.
@article{diva2:1675839,
author = {Wang, Yinan and Johansson, Håkan and Deng, Mingxin and Li, Zhiwei},
title = {{On the Compensation of Timing Mismatch in Two-Channel Time-Interleaved ADCs: Strategies and a Novel Parallel Compensation Structure}},
journal = {IEEE Transactions on Signal Processing},
year = {2022},
volume = {70},
pages = {2460--2475},
}
The successful emergence of deep learning (DL) in wireless system applications has raised concerns about new security-related challenges. One such security challenge is adversarial attacks. Although there has been much work demonstrating the susceptibility of DL-based classification tasks to adversarial attacks, regression-based problems in the context of a wireless system have not been studied so far from an attack perspective. The aim of this paper is twofold: (i) we consider a regression problem in a wireless setting and show that adversarial attacks can break the DL-based approach and (ii) we analyze the effectiveness of adversarial training as a defensive technique in adversarial settings and show that the robustness of DL-based wireless system against attacks improves significantly. Specifically, the wireless application considered in this paper is the DL-based power allocation in the downlink of a multicell massive multi-input-multi-output system, where the goal of the attack is to yield an infeasible solution by the DL model. We extend the gradient-based adversarial attacks: fast gradient sign method (FGSM), momentum iterative FGSM, and projected gradient descent method to analyze the susceptibility of the considered wireless application with and without adversarial training. We analyze the deep neural network (DNN) models performance against these attacks, where the adversarial perturbations are crafted using both the white-box and black-box attacks.
@article{diva2:1674751,
author = {Manoj, B. R. and Sadeghi, Meysam and Larsson, Erik G},
title = {{Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Training}},
journal = {IEEE Transactions on Cognitive Communications and Networking},
year = {2022},
volume = {8},
number = {2},
pages = {707--719},
}
As the security of global navigation satellite systems (GNSSs) for civilian usage is increasingly important, navigation message authentication (NMA) significantly improves resilience to spoofing attacks. However, not all attacks can be effectively countered: a strong variant of replay/relay attacks, distance-decreasing (DD) attacks, can shorten pseudorange measurements, without manipulating the cryptographically protected navigation message, thus manipulating the position, velocity, and time solution undetected. First, we discuss how DD attacks can tamper with GNSS signals, demonstrating the attack effectiveness on a recorded Galileo signal. DD attacks might introduce bit errors to the forged signals, but the adversary can keep this error rate very low with proper attack parameter settings. Then, based on our mathematical model of the prompt correlator output of the tracking phase at the victim receiver, we find that the correlator output distribution changes in the presence of DD attacks. This leads us to apply hypothesis testing to detect DD attacks, notably a goodness-of-fit (GoF) test and a generalized likelihood ratio test (GLRT), depending on the victims knowledge on the DD attacks. Monte Carlo simulations are used to evaluate the detection probability and the receiver operating characteristic curves for two tests, for different adversary configuration and noise settings. Then, we evaluate the effectiveness of the GoF test and the GLRT with a synthesized DD signal. Both tests can detect DD attacks with similar performance in high-signal-to-noise-ratio (SNR) environments. The GLRT detection probability is approximately 20% higher than that of the GoF test in low-SNR environments.
@article{diva2:1657284,
author = {Zhang, Kewei and Larsson, Erik G and Papadimitratos, Panos},
title = {{Protecting GNSS Open Service Navigation Message Authentication Against Distance-Decreasing Attacks}},
journal = {IEEE Transactions on Aerospace and Electronic Systems},
year = {2022},
volume = {58},
number = {2},
pages = {1224--1240},
}
The prospects of using a reconfigurable intelligent surface (RIS) to aid wireless communication systems have recently received much attention. Among the different use cases, the most popular one is where each element of the RIS scatters the incoming signal with a controllable phase-shift, without increasing its power. In prior literature, this setup has been analyzed by neglecting the electromagnetic interference, consisting of the inevitable incoming waves from external sources. In this letter, we provide a physically meaningful model for the electromagnetic interference that can be used as a baseline when evaluating RIS-aided communications. The model is used to show that electromagnetic interference has a non-negligible impact on communication performance, especially when the size of the RIS grows large. When the direct link is present (though with a relatively weak gain), the RIS can even reduce the communication performance. Importantly, it turns out that the SNR grows quadratically with the number of RIS elements only when the spatial correlation matrix of the electromagnetic interference is asymptotically orthogonal to that of the effective channel (including RIS phase-shifts) towards the intended receiver. Otherwise, the SNR only increases linearly.
@article{diva2:1654711,
author = {Torres, Andrea de Jesus and Sanguinetti, Luca and Björnson, Emil},
title = {{Electromagnetic Interference in RIS-Aided Communications}},
journal = {IEEE Wireless Communications Letters},
year = {2022},
volume = {11},
number = {4},
pages = {668--672},
}
We study downlink channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in time-division duplex. The users must know their effective channel gains to decode their received downlink data. Previous works have used the mean value as the estimate, motivated by channel hardening. However, this is associated with a performance loss in non-isotropic scattering environments. We propose two novel estimation methods that can be applied without downlink pilots. The first method is model-based and asymptotic arguments are utilized to identify a connection between the effective channel gain and the average received power during a coherence interval. The second method is data-driven and trains a neural network to identify a mapping between the available information and the effective channel gain. Both methods can be utilized for any channel distribution and precoding. For the model-aided method, we derive all expressions in closed form for the case when maximum ratio or zero-forcing precoding is used. We compare the proposed methods with the state-of-the-art using the normalized mean-squared error and spectral efficiency (SE). The results suggest that the two proposed methods provide better SE than the state-of-the-art when there is a low level of channel hardening, while the performance difference is relatively small with the uncorrelated channel model.
@article{diva2:1650879,
author = {Ghazanfari, Amin and Trinh Van, Chien and Björnson, Emil and Larsson, Erik G},
title = {{Model-Based and Data-Driven Approaches for Downlink Massive MIMO Channel Estimation}},
journal = {IEEE Transactions on Communications},
year = {2022},
volume = {70},
number = {3},
pages = {2085--2101},
}
Deep learning (DL) architectures have been successfully used in many applications including wireless systems. However, they have been shown to be susceptible to adversarial attacks. We analyze DL-based models for a regression problem in the context of downlink power allocation in massive multiple-input-multiple-output systems and propose universal adversarial perturbation (UAP)-crafting methods as white-box and black-box attacks. We benchmark the UAP performance of white-box and black-box attacks for the considered application and show that the adversarial success rate can achieve up to 60% and 40%, respectively. The proposed UAP-based attacks make a more practical and realistic approach as compared to classical white-box attacks.
@article{diva2:1630070,
author = {Santos, Pablo Millán and Manoj, B. R. and Sadeghi, Meysam and Larsson, Erik G},
title = {{Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System}},
journal = {IEEE Wireless Communications Letters},
year = {2022},
volume = {11},
number = {1},
pages = {67--71},
}
The shape of a surface determines how it interacts with wireless radio-frequency signals. Taking a homogenous metal plate as an example, we can bend and rotate it in different ways to make the incident wireless signal become diffusely or specularly reflected in the desired manner. The same effect can be electronically achieved by using an intelligent reflecting surface (IRS), which is a 2D array of metamaterials. By creating heterogeneous impedance variations over the surface, we can synthesize the reflection of a bent and rotated surface but without any mechanical manipulations.
@article{diva2:1626411,
author = {Björnson, Emil and Marcenaro, Lucio},
title = {{Configuring an Intelligent Reflecting Surface for Wireless Communications: Highlights from the 2021 IEEE Signal Processing Cup student competition [SP Competitions]}},
journal = {IEEE signal processing magazine (Print)},
year = {2022},
volume = {39},
number = {1},
pages = {126--131},
}
In this work, we study age-optimal scheduling with stability constraints in a multiple access channel with two heterogeneous source nodes transmitting to a common destination. The first node is connected to a power grid and it has randomly arriving data packets. Another energy harvesting (EH) sensor monitors a stochastic process and sends status updates to the destination. We formulate an optimization problem that aims at minimizing the average age of information (AoI) of the EH node subject to the queue stability condition of the grid-connected node. First, we consider a Probabilistic Random Access (PRA) policy where both nodes make independent transmission decisions based on some fixed probability distributions. We show that with this policy, the average AoI is equal to the average peak AoI, if the EH node only sends freshly generated samples. In addition, we derive the optimal solution in closed form, which reveals some interesting properties of the considered system. Furthermore, we consider a Drift-Plus-Penalty (DPP) policy and develop AoI-optimal and peak-AoI-optimal scheduling algorithms using the Lyapunov optimization theory. Simulation results show that the DPP policy outperforms the PRA policy in various scenarios, especially when the destination node has low multi-packet reception capabilities.
@article{diva2:1694130,
author = {Chen, Zheng and Pappas, Nikolaos and Björnson, Emil and Larsson, Erik G.},
title = {{Optimizing Information Freshness in a Multiple Access Channel With Heterogeneous Devices}},
journal = {IEEE Open Journal of the Communications Society},
year = {2021},
volume = {2},
pages = {456--470},
}
Cell-free massive multiple-input multiple-output (MIMO) provides more uniform spectral efficiency (SE) for users (UEs) than cellular technology. The main challenge to achieve the benefits of cell-free massive MIMO is to realize signal processing in a scalable way. In this paper, we consider scalable full-pilot zero-forcing (FZF), partial FZF (PFZF), protective weak PFZF (PWPFZF), and local regularized ZF (LRZF) combining by exploiting channel statistics. We derive closed-form expressions of the uplink SE for FZF, PFZF, and PWPFZF combining with large-scale fading decoding over independent Rayleigh fading channels, taking channel estimation errors and pilot contamination into account. Moreover, we investigate the impact of the number of pilot sequences, antennas per AP, and APs on the performance. Numerical results show that LRZF provides the highest SE. However, PWPFZF is preferable when the number of pilot sequences is large and the number of antennas per AP is small. The reason is that PWPFZF has lower computational complexity and the SE expression can be computed in closed-form. Furthermore, we investigate the performance of PWPFZF combining with fractional power control and the numerical results show that it improves the performance of weak UEs and realizes uniformly good service for all UEs in a scalable fashion.
@article{diva2:1626947,
author = {Zhang, Jiayi and Zhang, Jing and Björnson, Emil and Ai, Bo},
title = {{Local Partial Zero-Forcing Combining for Cell-Free Massive MIMO Systems}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {12},
pages = {8459--8473},
}
The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry. Most papers make theoretical studies based on elementary models, while the prototyping of RIS-aided wireless communication and real-world field trials are scarce. In this paper, we describe a new RIS prototype consisting of 1100 controllable elements working at 5.8 GHz band. We propose an efficient algorithm for configuring the RIS over the air by exploiting the geometrical array properties and a practical receiver-RIS feedback link. In our indoor test, where the transmitter and receiver are separated by a 30 cm thick concrete wall, our RIS prototype provides a 26 dB power gain compared to the baseline case where the RIS is replaced by a copper plate. A 27 dB power gain was observed in the short-distance outdoor measurement. We also carried out long-distance measurements and successfully transmitted a 32 Mbps data stream over 500 m. A 1080p video was live-streamed and it only played smoothly when the RIS was utilized. The power consumption of the RIS is around 1 W. Our paper is vivid proof that the RIS is a very promising technology for future wireless communications.
@article{diva2:1626923,
author = {Pei, Xilong and Yin, Haifan and Tan, Li and Cao, Lin and Li, Zhanpeng and Wang, Kai and Zhang, Kun and Björnson, Emil},
title = {{RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {12},
pages = {8627--8640},
}
We consider Global Navigation Satellite Systems (GNSS) spoofing attacks and devise a countermeasure appropriate for mobile GNSS receivers. Our approach is to design detectors that, operating after the signal acquisition, enable the victim receiver to determine with high probability whether it is under a spoofing attack or not. Namely, the binary hypothesis is that either the GNSS receiver tracks legitimate satellite signals, H-0, or spoofed signals, H-1. We assume that there exists an unknown number of multiple spoofers in the environment and the attack strategy (which legitimate signals are spoofed by which spoofers) is not known to the receiver. Based on these assumptions, we propose an algorithm that identifies the number of spoofers and clusters the spoofing data by using Bayesian information criterion (BIC) rule. Depending on the estimated and clustered data we propose a detector, called as generalized likelihood ratio (GLRT)-like detector. We compare the performance of the GLRT-like detector with a genie-aided detector in which the attack strategy and the number of spoofers is known by the receiver. In addition to this, we extend the GLRT-like detector for the case where the noise variance is also unknown and present the performance results.
@article{diva2:1624634,
author = {Gülgün, Ziya and Larsson, Erik G and Papadimitratos, Panagiotis},
title = {{Multiple Spoofer Detection for Mobile GNSS Receivers Using Statistical Tests}},
journal = {IEEE Access},
year = {2021},
volume = {9},
pages = {166382--166394},
}
Wireless-based activity sensing has gained significant attention due to its wide range of applications. We investigate radio-based multi-class classification of human activities using massive multiple-input multiple-output (MIMO) channel measurements in line-of-sight and non line-of-sight scenarios. We propose a tensor decomposition-based algorithm to extract features by exploiting the complex correlation characteristics across time, frequency, and space from channel tensors formed from the measurements, followed by a neural network that learns the relationship between the input features and output target labels. Through evaluations of real measurement data, it is demonstrated that the classification accuracy using a massive MIMO array achieves significantly better results compared to the state-of-the-art even for a smaller experimental data set.
@article{diva2:1624032,
author = {Manoj, Banugondi Rajashekara and Tian, Guoda and Gunnarsson, Sara and Tufvesson, Fredrik and Larsson, Erik G.},
title = {{Sensing and Classification Using Massive MIMO: A Tensor Decomposition-Based Approach}},
journal = {IEEE Wireless Communications Letters},
year = {2021},
volume = {10},
number = {12},
pages = {2649--2653},
}
Internet of Things (IoT) has attracted considerable attention in recent years due to its potential of interconnecting a large number of heterogeneous wireless devices. However, it is usually challenging to provide reliable and efficient random access control when massive IoT devices are trying to access the network simultaneously. In this article, we investigate methods to introduce intelligent random access management for a massive cellular IoT network to reduce access latency and access failures. Toward this end, we introduce two novel frameworks, namely, local device selection (LDS) and intelligent preamble selection (IPS). LDS enables local communication between neighboring devices to provide cluster-wide cooperative congestion control, which leads to a better distribution of the access intensity under bursty traffics. Taking advantage of the capability of reinforcement learning in developing cooperative multiagent policies, IPS is introduced to enable the optimization of the preamble selection policy in each IoT clusters. To handle the exponentially growing action space in IPS, we design a novel reinforcement learning structure, named branching actor-critic, to ensure that the output size of the underlying neural networks only grows linearly with the number of action dimensions. Simulation results indicate that the introduced mechanism achieves much lower access delays with fewer access failures in various realistic scenarios of interests.
@article{diva2:1622075,
author = {Bai, Jianan and Song, Hao and Yi, Yang and Liu, Lingjia},
title = {{Multiagent Reinforcement Learning Meets Random Access in Massive Cellular Internet of Things}},
journal = {IEEE Internet of Things Journal},
year = {2021},
volume = {8},
number = {24},
pages = {17417--17428},
}
This paper studies the interplay between device-to-device (D2D) communications and real-time monitoring systems in a cellular-based Internet of Things (IoT) network. In particular, besides the possibility that the IoT devices communicate directly with each other in a D2D fashion, we consider that they frequently send time-sensitive information/status updates (about some underlying physical processes observed by them) to their nearest cellular base stations (BSs). Specifically, we model the locations of the IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another independent PPP. For this setup, we characterize the performance of D2D communications using the average network throughput metric whereas the performance of the real-time applications is quantified by the Age of Information (AoI) metric. The IoT devices are considered to employ a distance-proportional fractional power control scheme while sending status updates to their serving BSs. Hence, depending upon the maximum transmission power available, the IoT devices located within a certain distance from the BSs can only send status updates. This association strategy, in turn, forms the Johnson-Mehl (JM) tessellation, such that the IoT devices located in the JM cells are allowed to send status updates. The average network throughput is obtained by deriving the mean success probability for the D2D links. On the other hand, the temporal mean AoI of a given status update link can be treated as a random variable over space since its success delivery rate is a function of the interference field seen from its receiver. Thus, in order to capture the spatial disparity in the AoI performance, we characterize the spatial moments of the temporal mean AoI. In particular, we obtain these spatial moments by deriving the moments of both the conditional success probability and the conditional scheduling probability for status update links. Our results provide useful design guidelines on the efficient deployment of future massive IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications.
@article{diva2:1621714,
author = {Mankar, Praful D. and Chen, Zheng and Abd-Elmagid, Mohamed A. and Pappas, Nikolaos and Dhillon, Harpreet S.},
title = {{Throughput and Age of Information in a Cellular-Based IoT Network}},
journal = {IEEE Transactions on Wireless Communications},
year = {2021},
volume = {20},
number = {12},
pages = {8248--8263},
}
Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging technology for beyond 5G with its promising features such as higher spectral efficiency and superior spatial diversity as compared to conventional multiple-input-multiple-output (MIMO) technology. The main working principle of cell-free mMIMO is that many distributed access points (APs) cooperate simultaneously to serve all the users within the network without creating cell boundaries. This paper considers the uplink of a cell-free mMIMO system utilizing the radio stripe network architecture with a sequential fronthaul between the APs. A novel uplink sequential processing algorithm is developed, which is proved to be optimal in both the maximum spectral efficiency (SE) and the minimum mean square error (MSE) sense. A detailed quantitative analysis of the fronthaul requirement or signaling of the proposed algorithm and its comparison with competing sub-optimal algorithms is provided. Key conclusions and implications are summarized in the form of corollaries. Based on the analytical and numerical simulation results, we conclude that the proposed scheme can significantly reduce the fronthaul signaling, without compromising the communication performance.
@article{diva2:1616163,
author = {Shaik, Zakir Hussain and Björnson, Emil and Larsson, Erik G},
title = {{MMSE-Optimal Sequential Processing for Cell-Free Massive MIMO With Radio Stripes}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {11},
pages = {7775--7789},
}
In this paper, we investigate the impact of channel aging on the performance of cell-free (CF) massive multiple-input multiple-output (MIMO) systems with both spatial correlation and pilot contamination. We derive novel closed-form uplink and downlink spectral efficiency (SE) expressions that take imperfect channel estimation into account. More specifically, we consider large-scale fading decoding and matched-filter receiver cooperation in the uplink. The uplink performance of a small-cell (SC) system is derived for comparison. The CF massive MIMO system achieves higher 95%-likely uplink SE than the SC system. In the downlink, the coherent transmission has four times higher 95%-likely per-user SE than the non-coherent transmission. Statistical channel cooperation power control (SCCPC) is used to mitigate the inter-user interference. SCCPC performs better than full power transmission, but the benefits are gradually weakened as the channel aging becomes stronger. Furthermore, strong spatial correlation reduces the SE but degrades the effect of channel aging. Increasing the number of antennas can improve the SE while decreasing the energy efficiency. Finally, we use the maximum normalized Doppler shift to design the SE-improved length of the resource block. Simulation results are presented to validate the accuracy of our expressions and prove that the CF massive MIMO system is more robust to channel aging than the SC system.
@article{diva2:1607596,
author = {Zheng, Jiakang and Zhang, Jiayi and Björnson, Emil and Ai, Bo},
title = {{Impact of Channel Aging on Cell-Free Massive MIMO Over Spatially Correlated Channels}},
journal = {IEEE Transactions on Wireless Communications},
year = {2021},
volume = {20},
number = {10},
pages = {6451--6466},
}
Standard cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems is a promising technology to cover the demands for higher data rates in fifth-generation (5G) networks and beyond. These systems assume a large number of distributed access points (APs) using joint coherent transmission to communicate with the users. However, CF mMIMO systems present an increasing computational complexity as the number of users increases. Scalable cell-free CF (SCF) systems have been proposed to face this challenge. Given that the cost-efficient deployment of such large networks requires low-cost transceivers, which are prone to unavoidable hardware imperfections, realistic evaluations of SCF mMIMO systems should take them into account before implementation. Hence, in this work, we focus on the impact of hardware impairments (HWIs) on the SCF mMIMO systems through a general model accounting for both additive and multiplicative impairments. Notably, there is no other work in the literature studying the impact of phase noise (PN) in the local oscillators (LOs) of CF mMIMO systems or in general the impact of any HWIs in SCF mMIMO systems. In particular, we derive upper and lower bounds on the uplink capacity accounting for HWIs. Moreover, we obtain the optimal hardware-aware (HA) partial minimum mean-squared error (PMMSE) combiner. Especially, the lower bound is derived in closed-form using the theory of deterministic equivalents (DEs). Among the interesting findings, we observe that separate LOs (SLOs) outperform a common LO (CLO), and the additive transmit distortion degrades more the performance than the additive receive distortion.
@article{diva2:1607560,
author = {Papazafeiropoulos, Anastasios and Björnson, Emil and Kourtessis, Pandelis and Chatzinotas, Symeon and Senior, John M.},
title = {{Scalable Cell-Free Massive MIMO Systems: Impact of Hardware Impairments}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2021},
volume = {70},
number = {10},
pages = {9701--9715},
}
In the past few years, a large body of literature has been created on downlink Non-Orthogonal Multiple Access (NOMA), employing superposition coding and Successive Interference Cancellation (SIC), in multi-antenna wireless networks. Furthermore, the benefits of NOMA over Orthogonal Multiple Access (OMA) have been highlighted. In this paper, we take a critical and fresh look at the downlink Next Generation Multiple Access (NGMA) literature. Instead of contrasting NOMA with OMA, we contrast NOMA with two other multiple access baselines. The first is conventional Multi-User Linear Precoding (MU-LP), as used in Space-Division Multiple Access (SDMA) and multi-user Multiple-Input Multiple-Output (MIMO) in 4G and 5G. The second, called Rate-Splitting Multiple Access (RSMA), is based on multi-antenna Rate-Splitting (RS). It is also a non-orthogonal transmission strategy relying on SIC developed in the past few years in parallel and independently from NOMA. We show that there is some confusion about the benefits of NOMA, and we dispel the associated misconceptions. First, we highlight why NOMA is inefficient in multi-antenna settings based on basic multiplexing gain analysis. We stress that the issue lies in how the NOMA literature, originally developed for single-antenna setups, has been hastily applied to multi-antenna setups, resulting in a misuse of spatial dimensions and therefore loss in multiplexing gains and rate. Second, we show that NOMA incurs a severe multiplexing gain loss despite an increased receiver complexity due to an inefficient use of SIC receivers. Third, we emphasize that much of the merits of NOMA are due to the constant comparison to OMA instead of comparing it to MU-LP and RS baselines. We then expose the pivotal design constraint that multi-antenna NOMA requires one user to fully decode the messages of the other users. This design constraint is responsible for the multiplexing gain erosion, rate and spectral efficiency loss, ineffectiveness to serve a large number of users, and inefficient use of SIC receivers in multi-antenna settings. Our analysis and simulation results confirm that NOMA should not be applied blindly to multi-antenna settings, highlight the scenarios where MU-LP outperforms NOMA and vice versa, and demonstrate the inefficiency, performance loss, and complexity disadvantages of NOMA compared to RSMA. The first takeaway message is that, while NOMA is suited for single-antenna settings (as originally intended), it is not efficient in most multi-antenna deployments. The second takeaway message is that another non-orthogonal transmission framework, based on RSMA, exists which fully exploits the multiplexing gain and the benefits of SIC to boost the rate and the number of users to serve in multi-antenna settings and outperforms both NOMA and MU-LP. Indeed, RSMA achieves higher multiplexing gains and rates, serves a larger number of users, is more robust to user deployments, network loads and inaccurate channel state information and has a lower receiver complexity than NOMA. Consequently, RSMA is a promising technology for NGMA and future networks such as 6G and beyond.
@article{diva2:1602365,
author = {Clerckx, Bruno and Mao, Yijie and Schober, Robert and Jorswieck, Eduard A. and Love, David J. and Yuan, Jinhong and Hanzo, Lajos and Li, Geoffrey Ye and Larsson, Erik G and Caire, Giuseppe},
title = {{Is NOMA Efficient in Multi-Antenna Networks?
A Critical Look at Next Generation Multiple Access Techniques}},
journal = {IEEE Open Journal of the Communications Society},
year = {2021},
volume = {2},
pages = {1310--1343},
}
User activity detection in grant-free random access massive machine type communication (mMTC) using pilot-hopping sequences can be formulated as solving a non-negative least squares (NNLS) problem. In this work, two architectures using different algorithms to solve the NNLS problem is proposed. The algorithms are implemented using a fully parallel approach and fixed-point arithmetic, leading to high detection rates and low power consumption. The first algorithm, fast projected gradients, converges faster to the optimal value. The second algorithm, multiplicative updates, is partially implemented in the logarithmic domain, and provides a smaller chip area and lower power consumption. For a detection rate of about one million detections per second, the chip area for the fast algorithm is about 0.7 mm 2 compared to about 0.5 mm 2 for the multiplicative algorithm when implemented in a 28 nm FD-SOI standard cell process at 1 V power supply voltage. The energy consumption is about 300 nJ/detection for the fast projected gradient algorithm using 256 iterations, leading to a convergence close to the theoretical. With 128 iterations, about 250 nJ/detection is required, with a detection performance on par with 192 iterations of the multiplicative algorithm for which about 100 nJ/detection is required.
@article{diva2:1599759,
author = {Mohammadi Sarband, Narges and Becirovic, Ema and Krysander, Mattias and Larsson, Erik G. and Gustafsson, Oscar},
title = {{Massive Machine-Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access}},
journal = {IEEE Open Journal of Circuits and Systems},
year = {2021},
volume = {2},
pages = {253--264},
}
n/a
@article{diva2:1598644,
author = {Liu, Liang and Larsson, Erik G and Popovski, Petar and Caire, Giuseppe and Chen, Xiaoming and Khosravirad, Saeed R.},
title = {{MASSIVE MACHINE-TYPE COMMUNICATIONS FOR IOT}},
journal = {IEEE wireless communications},
year = {2021},
volume = {28},
number = {4},
pages = {56--56},
}
Future wireless networks need to support massive machine type communication (mMTC) where a massive number of devices accesses the network and massive MIMO is a promising enabling technology. Massive access schemes have been studied for co-located massive MIMO arrays. In this paper, we investigate the activity detection in grant-free random access for mMTC in cell-free massive MIMO networks using distributed arrays. Each active device transmits a non-orthogonal pilot sequence to the access points (APs) and the APs send the received signals to a central processing unit (CPU) for joint activity detection. The maximum likelihood device activity detection problem is formulated and algorithms for activity detection in cell-free massive MIMO are provided to solve it. The simulation results show that the macro diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large.
@article{diva2:1597046,
author = {Kunnath Ganesan, Unnikrishnan and Björnson, Emil and Larsson, Erik G.},
title = {{Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {11},
pages = {7520--7530},
}
A cell-free Massive multiple-input multiple-output (MIMO) system is considered, where the access points (APs) are linked to a central processing unit (CPU) via the limited-capacity fronthaul links. It is assumed that only the quantized version of the weighted signals are available at the CPU. The achievable rate of a limited fronthaul cell-free massive MIMO with local minimum mean square error (MMSE) detection is studied. We study the assumption of uncorrelated quantization distortion, which is commonly used in literature. We show that this assumption will not affect the validity of the insights obtained in our work. To investigate this, we compare the uplink per-user rate with different system parameters for two different scenarios; 1) the exact uplink per-user rate and 2) the uplink per-user rate while ignoring the correlation between the inputs of the quantizers. Finally, we present the conditions which imply that the quantization distortions across APs can be assumed to be uncorrelated.
@article{diva2:1596458,
author = {Bashar, Manijeh and Xiao, Pei and Tafazolli, Rahim and Cumanan, Kanapathippillai and Burr, Alister G. and Björnson, Emil},
title = {{Limited-Fronthaul Cell-Free Massive MIMO With Local MMSE Receiver Under Rician Fading and Phase Shifts}},
journal = {IEEE Wireless Communications Letters},
year = {2021},
volume = {10},
number = {9},
pages = {1934--1938},
}
This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works.
@article{diva2:1589828,
author = {Nguyen, Tien Hoa and Van Chien, Trinh and Ngo, Hien Quoc and Tran, Xuan Nam and Björnson, Emil},
title = {{Pilot Assignment for Joint Uplink-Downlink Spectral Efficiency Enhancement in Massive MIMO Systems With Spatial Correlation}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2021},
volume = {70},
number = {8},
pages = {8292--8297},
}
Reconfigurable Intelligent Surface (RIS) is a promising solution to reconfigure the wireless environment in a controllable way. To compensate for the double-fading attenuation in the RIS-aided link, a large number of passive reflecting elements (REs) are conventionally deployed at the RIS, resulting in large surface size and considerable circuit power consumption. In this paper, we propose a new type of RIS, called active RIS, where each RE is assisted by active loads (negative resistance), that reflect and amplify the incident signal instead of only reflecting it with the adjustable phase shift as in the case of a passive RIS. Therefore, for a given power budget at the RIS, a strengthened RIS-aided link can be achieved by increasing the number of active REs as well as amplifying the incident signal. We consider the use of an active RIS to a single input multiple output (SIMO) system. However, it would unintentionally amplify the RIS-correlated noise, and thus the proposed system has to balance the conflict between the received signal power maximization and the RIS-correlated noise minimization at the receiver. To achieve this goal, it has to optimize the reflecting coefficient matrix at the RIS and the receive beamforming at the receiver. An alternating optimization algorithm is proposed to solve the problem. Specifically, the receive beamforming is obtained with a closed-form solution based on linear minimum-mean-square-error (MMSE) criterion, while the reflecting coefficient matrix is obtained by solving a series of sequential convex approximation (SCA) problems. Simulation results show that the proposed active RIS-aided system could achieve better performance over the conventional passive RIS-aided system with the same power budget.
@article{diva2:1589825,
author = {Long, Ruizhe and Liang, Ying-Chang and Pei, Yiyang and Larsson, Erik G},
title = {{Active Reconfigurable Intelligent Surface-Aided Wireless Communications}},
journal = {IEEE Transactions on Wireless Communications},
year = {2021},
volume = {20},
number = {8},
pages = {4962--4975},
}
Cell-free massive MIMO systems consist of many distributed access points with simple components that jointly serve the users. In millimeter wave bands, only a limited set of predetermined beams can be supported. In a network that consolidates these technologies, downlink analog beam selection stands as a challenging task for the network sum-rate maximization. Low-cost digital filters can improve the network sum-rate further. In this work, we propose low-cost joint designs of analog beam selection and digital filters. The proposed joint designs achieve significantly higher sum-rates than the disjoint design benchmark. Supervised machine learning (ML) algorithms can efficiently approximate the input-output mapping functions of the beam selection decisions of the joint designs with low computational complexities. Since the training of ML algorithms is performed off-line, we propose a well-constructed joint design that combines multiple initializations, iterations, and selection features, as well as beam conflict control, i.e., the same beam cannot be used for multiple users. The numerical results indicate that ML algorithms can retain 99-100% of the original sum-rate results achieved by the proposed well-constructed designs.
@article{diva2:1588487,
author = {Yetis, Cenk M. and Björnson, Emil and Giselsson, Pontus},
title = {{Joint Analog Beam Selection and Digital Beamforming in Millimeter Wave Cell-Free Massive MIMO Systems}},
journal = {IEEE Open Journal of the Communications Society},
year = {2021},
volume = {2},
pages = {1647--1662},
}
Y In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. The level of hardware impairments (HWIs) indicates how strong the signal distortion introduced by hardware imperfections is. In particular, the analog-to-digital converters (ADCs) have an important impact on signal distortion and power consumption. This article addresses the fundamental problem of selecting the optimal hardware quality in the Massive MIMO space. In particular, we examine the optimal HWI and ADC bit allocation per BS antenna to maximize the SE. The results show that in co-located arrays with low channel gain variations across antennas, equal ADC bit allocation is optimal. In contrast, cell-free Massive MIMO systems benefit the most from optimizing the ADC bit allocation achieving improvements in the order of 2 [bit-per-channel-use] per user equipment when using regularized zero-forcing (RZF). In addition, when including the impact of power consumption in cell-free Massive MIMO with RZF, allocating low values of mixed ADC bit resolutions across the BS antennas can increase the energy efficiency up to 30% compared to equal ADC bit allocation.
@article{diva2:1588129,
author = {Verenzuela, Daniel and Björnson, Emil and Matthaiou, Michail},
title = {{Optimal Per-Antenna ADC Bit Allocation in Correlated and Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {7},
pages = {4767--4780},
}
In this letter, we consider the uplink of a cell-free Massive multiple-input multiple-output (MIMO) network where each user is decoded by a subset of access points (APs). An additional step is introduced in the cell-free Massive MIMO processing: each AP in the uplink locally implements soft MIMO detection and then shares the resulting bit log-likelihoods on the front-haul link. The decoding of the data is performed at the central processing unit (CPU), collecting the data from the APs. The non-linear processing at the APs consists of the approximate computation of the posterior density for each received data bit, exploiting only local channel state information. The proposed method offers good performance in terms of frame-error-rate and considerably lower complexity than the optimal maximum-likelihood demodulator.
@article{diva2:1587979,
author = {DAndrea, Carmen and Larsson, Erik G},
title = {{Improving Cell-Free Massive MIMO by Local Per-Bit Soft Detection}},
journal = {IEEE Communications Letters},
year = {2021},
volume = {25},
number = {7},
pages = {2400--2404},
}
We introduce the concept of frequency-mixing intelligent reflecting surface (FMx-IRS), where the elements of the surface continuously change the phases of the incident signals. In this way, the FMx-IRS acts as a frequency mixer and makes the propagation environment nonlinear, thereby introducing new frequencies. We study the basic features of the proposed concept and demonstrate its advantages that stem from the novel type of control over the wireless propagation. The channel decoupling feature and the correlation between reflected channels are elaborated for the architecture, and are validated by the simulations.
@article{diva2:1587222,
author = {Yuan, Jide and De Carvalho, Elisabeth and Williams, Robin Jess and Björnson, Emil and Popovski, Petar},
title = {{Frequency-Mixing Intelligent Reflecting Surfaces for Nonlinear Wireless Propagation}},
journal = {IEEE Wireless Communications Letters},
year = {2021},
volume = {10},
number = {8},
pages = {1672--1676},
}
In overloaded Massive MIMO (mMIMO) systems, wherein the number K of user equipments (UEs) exceeds the number of base station antennas M, it has recently been shown that non-orthogonal multiple access (NOMA) can increase the sum spectral efficiency. This paper aims at identifying cases where code-domain NOMA can improve the spectral efficiency of mMIMO in the classical regime where K < M. Novel spectral efficiency expressions are provided for the uplink and downlink with arbitrary spreading signatures and spatial correlation matrices. Particular attention is devoted to the planar arrays that are currently being deployed in pre-5G and 5G networks (in sub-6 GHz bands), which are characterized by limited spatial resolution. Numerical results show that mMIMO with such planar arrays can benefit from NOMA in scenarios where the UEs are spatially close to each other. A two-step UE grouping scheme is proposed for NOMA-aided mMIMO systems that is applicable to the spatial correlation matrices of the UEs that are currently active in each cell. Numerical results are used to investigate the performance of the algorithm under different operating conditions and types of spreading signatures (orthogonal, sparse and random sets). The analysis reveals that orthogonal signatures provide the highest average spectral efficiency.
@article{diva2:1578372,
author = {Le, Mai T. P. and Sanguinetti, Luca and Björnson, Emil and Di Benedetto, Maria-Gabriella},
title = {{Code-Domain NOMA in Massive MIMO:
When Is It Needed?}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2021},
volume = {70},
number = {5},
pages = {4709--4723},
}
In cell-free massive multiple-input multiple-output (MIMO) the fluctuations of the channel gain from the access points to a user are large due to the distributed topology of the system. Because of these fluctuations, data decoding schemes that treat the channel as deterministic perform inefficiently. A way to reduce the channel fluctuations is to design a precoding scheme that equalizes the effective channel gain seen by the users. Conjugate beamforming (CB) poorly contributes to harden the effective channel at the users. In this work, we propose a variant of CB dubbed enhanced normalized CB (ECB), in that the precoding vector consists of the conjugate of the channel estimate normalized by its squared norm. For this scheme, we derive an exact closed-form expression for an achievable downlink spectral efficiency (SE), accounting for channel estimation errors, pilot reuse and users lack of channel state information (CSI), assuming independent Rayleigh fading channels. We also devise an optimal max-min fairness power allocation based only on large-scale fading quantities. ECB greatly boosts the channel hardening enabling the users to reliably decode data relying only on statistical CSI. As the provided effective channel is nearly deterministic, acquiring CSI at the users does not yield a significant gain.
@article{diva2:1562775,
author = {Interdonato, Giovanni and Ngo, Hien Quoc and Larsson, Erik G},
title = {{Enhanced Normalized Conjugate Beamforming for Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {5},
pages = {2863--2877},
}
We consider a practical cell-free massive multiple-input-multiple-output (MIMO) system with multi-antenna access points (APs) and spatially correlated Rician fading channels. The significant phase-shift of the line-of-sight component induced by the user equipment movement is modeled randomly. Furthermore, we investigate the uplink spectral efficiency (SE) with maximum ratio (MR)/local minimum mean squared error (L-MMSE) combining and optimal large-scale fading decoding based on the phase-aware MMSE, phase-aware element-wise MMSE and linear MMSE (LMMSE) estimators. Then new closed-form SE expressions with MR combining are derived. Numerical results validate our derived expressions and show that the SE benefits from the spatial correlation. It is important to observe that the performance gap between L-MMSE and MR combining increases with the number of antennas per AP and the SE of the LMMSE estimator is lower than that of other estimators due to the lack of phase-shifts knowledge.
@article{diva2:1556791,
author = {Wang, Zhe and Zhang, Jiayi and Björnson, Emil and Ai, Bo},
title = {{Uplink Performance of Cell-Free Massive MIMO Over Spatially Correlated Rician Fading Channels}},
journal = {IEEE Communications Letters},
year = {2021},
volume = {25},
number = {4},
pages = {1348--1352},
}
A realistic performance assessment of any wireless technology requires the use of a channel model that reflects its main characteristics. The independent and identically distributed Rayleigh fading channel model has been (and still is) the basis of most theoretical research on multiple antenna technologies in scattering environments. This letter shows that such a model is not physically appearing when using a reconfigurable intelligent surface (RIS) with rectangular geometry and provides an alternative physically feasible Rayleigh fading model that can be used as a baseline when evaluating RIS-aided communications. The model is used to revisit the basic RIS properties, e.g., the rank of spatial correlation matrices and channel hardening.
@article{diva2:1555277,
author = {Björnson, Emil and Sanguinetti, Luca},
title = {{Rayleigh Fading Modeling and Channel Hardening for Reconfigurable Intelligent Surfaces}},
journal = {IEEE Wireless Communications Letters},
year = {2021},
volume = {10},
number = {4},
pages = {830--834},
}
This paper considers wireless uplink information and downlink power transfer in cell-free massive multiple-input multiple-output systems. The single-antenna user equipments (UEs) utilize the energy harvested in the downlink to transmit uplink pilot and information signals to the multiple-antenna access points (APs). We consider Rician fading and maximum ratio processing based on either linear minimum mean-squared error (LMMSE) or least-squares (LS) channel estimation. We derive the average harvested energy by using a practical non-linear energy harvesting circuit model for both coherent and non-coherent transmission schemes. Furthermore, the uplink spectral efficiency (SE) is derived for all the considered methods and the max-min fairness problem is cast where the optimization variables are the AP and UE power control coefficients together with the large-scale fading decoding vectors. The objective is to maximize the minimum SE of the UEs under APs and UEs transmission power constraints. A novel alternating optimization algorithm with guaranteed convergence and improvement at each step is proposed to solve the highly-coupled non-convex problem.
@article{diva2:1546174,
author = {Tuğfe Demir, Özlem and Björnson, Emil},
title = {{Joint Power Control and LSFD for Wireless-Powered Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2021},
volume = {20},
number = {3},
pages = {1756--1769},
}
In this paper, we analyze the impact of caching on the performance of a cache enabled system with heterogeneous traffic where one of the users need to be served with confidential data. In this setup, a wireless helper system always serves a dedicated user and it can also serve a user requesting cached content. A cellular network access point is also available to serve the latter user if it cannot retrieve the requested data from the helper’s cache. The impact of caching and secrecy on throughput and delay performance for each user is then examined when the access point can deploy superposition coding to serve both users simultaneously. Two decoding schemes are considered in this work. The first decoding scheme treats interference from parallel transmissions as noise while the second one utilizes the parallel transmission to apply successive decoding for the intended data. Furthermore, network and cache related factors are identified and their impact on the overall performance of the system are analyzed. In order to find the optimal transmission power allocations, two distinct optimization problems are set in this context comparing the two decoding schemes. This will assist to identify the benefits of the considered decoding schemes for each user satisfying the secrecy requirements of the dedicated user and reducing its impact on the overall performance of the system.
@article{diva2:1543745,
author = {Smpokos, Georgios and Chen, Zheng and Mohapatra, Parthajit and Pappas, Nikolaos},
title = {{Performance Analysis of a Cache-Aided Wireless Heterogeneous Network With Secrecy Constraints}},
journal = {IEEE Access},
year = {2021},
volume = {9},
pages = {52442--52454},
}
In this work, we consider a random access Internet of Things IoT wireless network assisted by two aggregators collecting information from two disjoint groups of sensors. The nodes and the aggregators are transmitting in a random access manner under slotted time, the aggregators perform network-level cooperation for the data collection. The aggregators are equipped with queues to store data packets that are transmitted by the network nodes and relaying them to the destination node. We characterize the throughput performance of the IoT network and we obtain the stability conditions for the queues at the aggregators. We apply the theory of boundary value problems to analyze the delay performance. Our results show that the presence of the aggregators provides significant gains in the IoT network performance, in addition, we provide useful insights regarding the scalability of the IoT network. (C) 2021 Elsevier B.V. All rights reserved.
@article{diva2:1543715,
author = {Pappas, Nikolaos and Dimitriou, Ioannis and Chen, Zheng},
title = {{On the benefits of network-level cooperation in IoT networks with aggregators}},
journal = {Performance evaluation (Print)},
year = {2021},
volume = {147},
}
This second part of the two-part Special Issue (SI) on massive access for 5G and beyond starts with several papers on massive access techniques, then switches to coverage enhancement approaches, and finishes with a paper on the application of massive access in industrial Internet-of-Things (IoT).
@article{diva2:1541556,
author = {Chen, Xiaoming and Ng, Derrick Wing Kwan and Yu, Wei and Larsson, Erik G and Al-Dhahir, Naofal and Schober, Robert},
title = {{Guest Editorial Massive Access for 5G and Beyond-Part II}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2021},
volume = {39},
number = {4},
pages = {899--902},
}
How to meet the demand for increasing number of users, higher data rates, and stringent quality-of-service (QoS) in the beyond fifth-generation (B5G) networks? Cell-free massive multiple-input multiple-output (MIMO) is considered as a promising solution, in which many wireless access points cooperate to jointly serve the users by exploiting coherent signal processing. However, there are still many unsolved practical issues in cell-free massive MIMO systems, whereof scalable massive access implementation is one of the most vital. In this paper, we propose a new framework for structured massive access in cell-free massive MIMO systems, which comprises one initial access algorithm, a partial large-scale fading decoding (P-LSFD) strategy, two pilot assignment schemes, and one fractional power control policy. New closed-form spectral efficiency (SE) expressions with maximum ratio (MR) combining are derived. The simulation results show that our proposed framework provides high SE when using local partial minimum mean-square error (LP-MMSE) and MR combining. Specifically, the proposed initial access algorithm and pilot assignment schemes outperform their corresponding benchmarks, P-LSFD achieves scalability with a negligible performance loss compared to the conventional optimal large-scale fading decoding (LSFD), and scalable fractional power control provides a controllable trade-off between user fairness and the average SE.
@article{diva2:1541555,
author = {Chen, Shuaifei and Zhang, Jiayi and Björnson, Emil and Zhang, Jing and Ai, Bo},
title = {{Structured Massive Access for Scalable Cell-Free Massive MIMO Systems}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2021},
volume = {39},
number = {4},
pages = {1086--1100},
}
In this paper, we investigate optimal downlink power allocation in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays (DAAs) under correlated and uncorrelated channel fading. In DAA massive MIMO, a base station (BS) consists of multiple antenna sub-arrays. Notably, the antenna sub-arrays are deployed in arbitrary locations within a DAA massive MIMO cell. Consequently, the distance-dependent large-scale propagation coefficients are different from a user to these different antenna sub-arrays, which makes power control a challenging problem. We assume that the network operates in time-division duplex mode, where each BS obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum-ratio transmission in the downlink. We then derive a closed-form signal-to-interference-plus-noise ratio (SINR) expression, where the channels are subject to correlated fading. Based on the SINR expression, we propose a network-wide max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate the performance advantages offered by DAA massive MIMO. For some specific scenarios, DAA massive MIMO can improve the average per-user throughput up to 55%. Furthermore, we demonstrate that channel fading covariance is an important factor in determining the performance of DAA massive MIMO.
@article{diva2:1541509,
author = {Akbar, Noman and Björnson, Emil and Yang, Nan and Larsson, Erik G},
title = {{Max-Min Power Control in Downlink Massive MIMO With Distributed Antenna Arrays}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {2},
pages = {740--751},
}
Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. A typical application of massive access is the cellular Internet of Things (IoT). Different from conventional human-type communication, massive access aims at realizing efficient and reliable communications for a massive number of IoT devices. Hence, the main characteristics of massive access include low power, massive connectivity, and broad coverage, which require new concepts, theories, and paradigms for the design of next-generation cellular networks. This paper presents a comprehensive survey of massive access design for B5G wireless networks. Specifically, we provide a detailed review of massive access from the perspectives of theory, protocols, techniques, coverage, energy, and security. Furthermore, several future research directions and challenges are identified.
@article{diva2:1538760,
author = {Chen, Xiaoming and Ng, Derrick Wing Kwan and Yu, Wei and Larsson, Erik G and Al-Dhahir, Naofal and Schober, Robert},
title = {{Massive Access for 5G and Beyond}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2021},
volume = {39},
number = {3},
pages = {615--637},
}
Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. In the past few years, it has received considerable attention in academia and industry. This Special Issue (SI) of the IEEE Journal on Selected Areas in Communications (JSAC) on Massive Access for 5G and Beyond contains the latest results of researchers, industry practitioners, and individuals working on related research problems. Due to the extremely high response to the Call for Papers, this SI is split into two parts. The first part includes a guest editor-authored survey paper and 17 technical papers focusing on access models and access protocols, while the second part contains 18 papers focusing on access techniques and coverage enhancement approaches. We sincerely thank the authors, reviewers, JSAC staffs, and the Senior Editor, Prof. Wayne Stark, for their effort and time in preparing this SI.
@article{diva2:1538759,
author = {Chen, Xiaoming and Ng, Derrick Wing Kwan and Yu, Wei and Larsson, Erik G and Al-Dhahir, Naofal and Schober, Robert},
title = {{Guest Editorial Massive Access for 5G and Beyond-Part I}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2021},
volume = {39},
number = {3},
pages = {611--614},
}
The operation of an intelligent reflecting surface (IRS) under predictable receiver mobility is investigated. We develop a continuous time system model for multipath channels and discuss the optimal IRS configuration with respect to received power, Doppler spread, and delay spread. It is shown that the received power can be maximized without adding Doppler spread to the system. In a numerical case study, we show that an IRS having the size of just two large billboards can improve the link budget of ground to Low Earth Orbit (LEO) satellite links by up to 6dB. It also adds a second, almost equivalently strong, communication path that improves the link reliability.
@article{diva2:1537229,
author = {Matthiesen, Bho and Björnson, Emil and De Carvalho, Elisabeth and Popovski, Petar},
title = {{Intelligent Reflecting Surface Operation Under Predictable Receiver Mobility: A Continuous Time Propagation Model}},
journal = {IEEE Wireless Communications Letters},
year = {2021},
volume = {10},
number = {2},
pages = {216--220},
}
Average consensus algorithms have wide applications in distributed computing systems where all the nodes agree on the average value of their initial states by only exchanging information with their local neighbors. In this letter, we look into link-based network metrics which are polynomial functions of pair-wise node attributes defined over the links in a network. Different from node-based average consensus, such link-based metrics depend on both the distribution of node attributes and the underlying network topology. We propose a general algorithm using the weighted average consensus protocol for the distributed computation of link-based network metrics and provide the convergence conditions and convergence rate analysis.
@article{diva2:1535990,
author = {Chen, Zheng and Larsson, Erik G},
title = {{Consensus-Based Distributed Computation of Link-Based Network Metrics}},
journal = {IEEE Signal Processing Letters},
year = {2021},
volume = {28},
pages = {249--253},
}
This paper investigates the performance of limited-fronthaul cell-free massive multiple-input multiple-output (MIMO) taking account the fronthaul quantization and imperfect channel acquisition. Three cases are studied, which we refer to as Estimate&Quantize, Quantize&Estimate, and Decentralized, according to where channel estimation is performed and exploited. Maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) receivers are considered. The Max algorithm and the Bussgang decomposition are exploited to model optimum uniform quantization. Exploiting the optimal step size of the quantizer, analytical expressions for spectral and energy efficiencies are presented. Finally, an access point (AP) assignment algorithm is proposed to improve the performance of the decentralized scheme. Numerical results investigate the performance gap between limited fronthaul and perfect fronthaul cases, and demonstrate that exploiting relatively few quantization bits, the performance of limited-fronthaul cell-free massive MIMO closely approaches the perfect-fronthaul performance.
@article{diva2:1529962,
author = {Bashar, Manijeh and Ngo, Hien Quoc and Cumanan, Kanapathippillai and Burr, Alister G. and Xiao, Pei and Björnson, Emil and Larsson, Erik G},
title = {{Uplink Spectral and Energy Efficiency of Cell-Free Massive MIMO With Optimal Uniform Quantization}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {1},
pages = {223--245},
}
Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple PU receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.
@article{diva2:1529961,
author = {Yuan, Jie and Liang, Ying-Chang and Joung, Jingon and Feng, Gang and Larsson, Erik G},
title = {{Intelligent Reflecting Surface-Assisted Cognitive Radio System}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {1},
pages = {675--687},
}
Many of the systems in various signal processing applications are nonlinear due to, for example, hardware impairments, such as nonlinear amplifiers and finite-resolution quantization. The Bussgang decomposition is a popular tool used when analyzing the performance of systems that involve such nonlinear components. In a nutshell, the decomposition provides an exact probabilistic relationship between the output and the input of a nonlinearity: the output is equal to a scaled version of the input plus uncorrelated distortion. The decomposition can be used to compute either exact performance results or lower bounds, where the uncorrelated distortion is treated as independent noise. This lecture note explains the basic theory, provides key examples, extends the theory to complex-valued vector signals, and clarifies some potential misconceptions.
@article{diva2:1522767,
author = {Tugfe Demir, Özlem Tugfe and Björnson, Emil},
title = {{The Bussgang Decomposition of Nonlinear Systems: Basic Theory and MIMO Extensions [Lecture Notes]}},
journal = {IEEE signal processing magazine (Print)},
year = {2021},
volume = {38},
number = {1},
pages = {131--136},
}
In this paper, we evaluate the uplink spectral efficiency (SE) of a single-cell massive multiple-input-multiple-output (MIMO) system with distributed jammers. We define four different attack scenarios and compare their impact on the massive MIMO system as well as on a conventional single-input-multiple-output (SIMO) system. More specifically, the jammers attack the base station (BS) during both the uplink training phase and data phase. The BS uses either least squares (LS) or linear minimum mean square error (LMMSE) estimators for channel estimation and utilizes either maximum-ratio-combining (MRC) or zero-forcing (ZF) decoding vectors. We show that ZF gives higher SE than MRC but, interestingly, the performance is unaffected by the choice of the estimators. The simulation results show that the performance loss percentage of massive MIMO is less than that of the SIMO system. Moreover, we consider two types of power control algorithms: jamming-aware and jamming-ignorant. In both cases, we consider the max-min and proportional fairness criteria to increase the uplink SE of massive MIMO systems. We notice numerically that max-min fairness is not a good option because if one user is strongly affected by the jamming, it will degrade the other users’ SE as well. On the other hand, proportional fairness improves the sum SE of the system compared with the full power transmission scenario.
@article{diva2:1517052,
author = {Gülgün, Ziya and Björnson, Emil and Larsson, Erik G.},
title = {{Is Massive MIMO Robust Against Distributed Jammers?}},
journal = {IEEE Transactions on Communications},
year = {2021},
volume = {69},
number = {1},
pages = {457--469},
}
The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.
@article{diva2:1512942,
author = {You, Xiaohu and Wang, Cheng-Xiang and Huang, Jie and Gao, Xiqi and Zhang, Zaichen and Wang, Mao and Huang, Yongming and Zhang, Chuan and Jiang, Yanxiang and Wang, Jiaheng and Zhu, Min and Sheng, Bin and Wang, Dongming and Pan, Zhiwen and Zhu, Pengcheng and Yang, Yang and Liu, Zening and Zhang, Ping and Tao, Xiaofeng and Li, Shaoqian and Chen, Zhi and Ma, Xinying and I, Chih-Lin and Han, Shuangfeng and Li, Ke and Pan, Chengkang and Zheng, Zhimin and Hanzo, Lajos and Shen, Xuemin (Sherman) and Guo, Yingjie Jay and Ding, Zhiguo and Haas, Harald and Tong, Wen and Zhu, Peiying and Yang, Ganghua and Wang, Jun and Larsson, Erik G and Quoc Ngo, Hien and Hong, Wei and Wang, Haiming and Hou, Debin and Chen, Jixin and Chen, Zhe and Hao, Zhangcheng and Li, Geoffrey Ye and Tafazolli, Rahim and Gao, Yue and Poor, H. Vincent and Fettweis, Gerhard P. and Liang, Ying-Chang},
title = {{Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts}},
journal = {Science China Information Sciences},
year = {2021},
volume = {64},
number = {1},
}
This paper considers the joint impact of non-linear hardware impairments at the base station (BS) and user equipments (UEs) on the uplink performance of single-cell massive MIMO (multiple-input multiple-output) in practical Rician fading environments. First, Bussgang decomposition-based effective channels and distortion characteristics are analytically derived and the spectral efficiency (SE) achieved by several receivers are explored for third-order non-linearities. Next, two deep feedforward neural networks are designed and trained to estimate the effective channels and the distortion variance at each BS antenna, which are used in signal detection. We compare the performance of the proposed methods with state-of-the-art distortion-aware and -unaware Bayesian linear minimum mean-squared error (LMMSE) estimators. The proposed deep learning approach improves the estimation quality by exploiting impairment characteristics, while LMMSE methods treat distortion as noise. Using the data generated by the derived effective channels for general order of non-linearities at both the BS and UEs, it is shown that the deep learning-based estimator provides better estimates of the effective channels also for non-linearities more than order three.
@article{diva2:1599449,
author = {Demir, Özlem Tugfe and Björnson, Emil},
title = {{Channel Estimation in Massive MIMO Under Hardware Non-Linearities: Bayesian Methods Versus Deep Learning}},
journal = {IEEE Open Journal of the Communications Society},
year = {2020},
volume = {1},
pages = {109--124},
}
The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N whenusing Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs)have recently attracted attention since these can relay signals to achieve an SNR that grows as N2, whichseems like a major benefit. In this article, we use a deterministic propagation model for a planar arrayof arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws,only apply in the far-field. They cannot be used to study the regime where N → ∞. We derive an exactchannel gain expression that captures three essential near-field behaviors and use it to revisit the powerscaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely tobe approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR thanan equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how muchlarger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behaveas an “anomalous” mirror but can vastly outperform that benchmark
@article{diva2:1599444,
author = {Björnson, Emil and Sanguinetti, Luca},
title = {{Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces}},
journal = {IEEE Open Journal of the Communications Society},
year = {2020},
volume = {1},
pages = {1306--1324},
}
Imagine a coverage area where each mobile device is communicating with a preferred set of wireless access points (among many) that are selected based on its needs and cooperate to jointly serve it, instead of creating autonomous cells. This effectively leads to a user-centric post-cellular network architecture, which can resolve many of the interference issues and service-quality variations that appear in cellular networks. This concept is called User-centric Cellfree Massive MIMO (multiple-input multiple-output) and has its roots in the intersection between three technology components: Massive MIMO, coordinated multipoint processing, and ultra-dense networks. The main challenge is to achieve the benefits of cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to enable massively large networks with many mobile devices. This monograph covers the foundations of User-centric Cell-free Massive MIMO, starting from the motivation and mathematical definition. It continues by describing the state-of-the-art signal processing algorithms for channel estimation, uplink data reception, and downlink data transmission with either centralized or distributed implementation. The achievable spectral efficiency is mathematically derived and evaluated numerically using a running example that exposes the impact of various system parameters and algorithmic choices. The fundamental tradeoffs between communication performance, computational complexity, and fronthaul signaling requirements are thoroughly analyzed. Finally, the basic algorithms for pilot assignment, dynamic cooperation cluster formation, and power optimization are provided, while open problems related to these and other resource allocation problems are reviewed. All the numerical examples can be reproduced using the accompanying Matlab code.
@article{diva2:1530117,
author = {Tugfe Demir, Özlem Tugfe and Björnson, Emil and Sanguinetti, Luca},
title = {{Foundations of User-Centric Cell-Free Massive MIMO}},
journal = {FOUNDATIONS AND TRENDS IN SIGNAL PROCESSING},
year = {2020},
volume = {14},
number = {3-4},
pages = {162--472},
}
The search for physical layer technologies that can play a key role in beyond 5G systems has started. One option is reconfigurable intelligent surfaces (RISs), which can collect wireless signals from a transmitter and passively beamform them toward the receiver. The technology has exciting prospects and is quickly gaining traction in the communication community, but in the current hype we have witnessed how several myths and overstatements are spreading in the literature. In this article, we take a neutral look at the RIS technology. We first review the fundamentals and then explain specific features that can be easily misinterpreted. In particular, we debunk three myths: 1) current network technology can only control the transmitter and receiver, not the environment in between; 2) a better asymptotic array gain is achieved than with conventional beamforming; 3) the path loss is the same as with anomalous mirrors. To inspire further research, we conclude by identifying two critical questions that must be answered for RIS to become a successful technology: 1) What is a convincing use case for RIS?; 2) How can we estimate channels and control an RIS in real time?
@article{diva2:1524241,
author = {Björnson, Emil and Özdogan, Özgecan and Larsson, Erik G},
title = {{Reconfigurable Intelligent Surfaces: Three Myths and Two Critical Questions}},
journal = {IEEE Communications Magazine},
year = {2020},
volume = {58},
number = {12},
pages = {90--96},
}
This paper presents an application of the Sigma Delta modulation technique to the on-chip dynamic test for analog-to-digital converters (ADCs). The required stimulus such as a single- or two-tone signal is encoded into one-bit Sigma Delta sequence, which is applied to an ADC under test through a driving buffer and a simple low-pass reconstruction filter. By a systematic approach, we select the order and type of a Sigma Delta modulator and develop a frequency plan suitable for the spectral measurement. In this way, we achieve a high dynamic range suitable for spectral harmonic and intermodulation distortion tests for ADCs. For high frequency measurements (up to the Nyquist frequency), we propose a novel low-pass/band-pass modulation scheme that allows to avoid harmful effects of the low-frequency quantization noise. Also we address the distortion components which originate from the buffer imperfections for a nonreturn-to-zero waveform representing the encoded stimulus. We show that the low-frequency distortion components can be cancelled by using a simple iterative predistortion technique supported by measurements with a DC-calibrated ADC. By correlation between low- and high-frequency components also the high frequency distortions can be largely reduced. The presented techniques are illustrated by simulation results of an ADC under test.
@article{diva2:1515599,
author = {Ahmad, Shakeel and Dabrowski, Jerzy},
title = {{One-Bit Sigma Delta-Encoded Stimulus Generation for On-Chip ADC Test}},
journal = {Journal of Circuits, Systems and Computers},
year = {2020},
volume = {29},
number = {15},
}
Employing massively distributed antennas brings radio access points (RAPs) closer to users, enabling aggressive spectrum reuse that can bridge gaps between the scarce spectrum resource and extremely high connection densities in future wireless systems. Examples include the cloud radio access network (C-RAN), ultradense network (UDN), and cell-free massive multiple-input, multiple-output (CF-mMIMO) systems. These systems are usually designed in the form of fiber wireless communications (FWC), where distributed antennas or RAPs are connected to a central unit (CU) through optical fronthauls. A large number of densely deployed antennas or RAPs require an extensive infrastructure of optical fronthauls. Consequently, the cost, complexity, and power consumption of the network of optical fronthauls may dominate the performance of the entire system. This article provides an overview and outlook on the architecture, modeling, design, and performance of massively distributed antenna systems (DAS) with nonideal optical fronthauls. Complex interactions between optical fronthauls and wireless access links require optimum designs across the optical and wireless domains by jointly exploiting their unique characteristics. It is demonstrated that systems with analog radio-frequency-overfiber (RFoF) links outperform their baseband-overfiber (BBoF) or intermediate-frequency-overfiber (IFoF) counterparts for systems with shorte fiber length and more RAPs, which are all desired properties for future wireless communication systems.
@article{diva2:1515587,
author = {Yu, Lisu and Wu, Jingxian and Zhou, Andong and Larsson, Erik G and Fan, Pingzhi},
title = {{Massively Distributed Antenna Systems With Nonideal Optical Fiber Fronthauls: A Promising Technology for 6G Wireless Communication Systems}},
journal = {IEEE Vehicular Technology Magazine},
year = {2020},
volume = {15},
number = {4},
pages = {43--51},
}
The heterogenous wireless services and exponentially growing traffic call for novel spectrum- and energy-efficient wireless communication technologies. Recently, a new technique, called symbiotic radio (SR), is proposed to exploit the benefits and address the drawbacks of cognitive radio (CR) and ambient backscattering communications (AmBC), leading to mutualism spectrum sharing and highly reliable backscattering communications. In particular, the secondary transmitter (STx) in SR transmits messages to the secondary receiver (SRx) over the RF signals originating from the primary transmitter (PTx) based on cognitive backscattering communications, thus the secondary system shares not only the radio spectrum, but also the power, and infrastructure with the primary system. In return, the secondary transmission provides beneficial multipath diversity to the primary system, therefore the two systems form mutualism spectrum sharing. More importantly, joint decoding is exploited at SRx to achieve highly reliable backscattering communications. In this article, to exploit the full potential of SR, we provide a systematic view for SR and address three fundamental tasks in SR: (1) enhancing the backscattering link via active load; (2) achieving highly reliable communications through joint decoding; and (3) capturing PTxs RF signals using reconfigurable intelligent surfaces. Emerging applications, design challenges and open research problems will also be discussed.
@article{diva2:1512934,
author = {Liang, Ying-Chang and Zhang, Qianqian and Larsson, Erik G and Li, Geoffrey Ye},
title = {{Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks}},
journal = {IEEE Transactions on Cognitive Communications and Networking},
year = {2020},
volume = {6},
number = {4},
pages = {1242--1255},
}
In this paper, we propose a method of improving the channel estimates for non-coherent multi-antenna terminals, which are terminals that cannot control the relative phase between its antenna ports, with channels that can be considered constant over multiple time slots. The terminals have multiple antennas and are free to choose whichever antenna they want to use in each time slot. An unknown phase shift is introduced in each time slot as we cannot guarantee that the terminals are phase coherent across time slots. We compare three different clustering techniques that we use to detect the active antenna. We also compare a set of different statistical and heuristic estimators for the channels and the phase shifts. We evaluate the methods by using correlated Rayleigh fading and three different bounds on the uplink capacity. The accuracy of the capacity bounds are verified with bit-error-rate simulations. With our proposed methods we can have an SNR improvement of approximately 2 dB at 1 bit/s/Hz.
@article{diva2:1507464,
author = {Becirovic, Ema and Björnson, Emil and Larsson, Erik G},
title = {{Joint Antenna Detection and Bayesian Channel Estimation for Non-Coherent User Terminals}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {11},
pages = {7081--7096},
}
Large-scale distributed antenna systems with many access points (APs) that serve the users by coherent joint transmission is being considered for 5G-and-beyond networks. The technology is called Cell-free Massive MIMO and can provide a more uniform service level to the users than a conventional cellular topology. For a given user set, only a subset of the APs is likely needed to satisfy the users performance demands, particularly outside the peak traffic hours. To find achieve an energy-efficient load balancing, we minimize the total downlink power consumption at the APs, considering both the transmit powers and hardware dissipation. APs can be temporarily turned off to reduce the latter part. The formulated optimization problem is non-convex but, nevertheless, a globally optimal solution is obtained by solving a mixed-integer second-order cone program. Since the computational complexity is prohibitive for real-time implementation, we also propose two low-complexity algorithms that exploit the inherent group-sparsity and the optimized transmit powers in the problem formulation. Numerical results manifest that our optimization algorithms can greatly reduce the power consumption compared to keeping all APs turned on and only minimizing the transmit powers. Moreover, the low-complexity algorithms can effectively handle the power allocation and AP activation for large-scale networks.
@article{diva2:1485155,
author = {van Chien, Trinh and Björnson, Emil and Larsson, Erik G},
title = {{Joint Power Allocation and Load Balancing Optimization for Energy-Efficient Cell-Free Massive MIMO Networks}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {10},
pages = {6798--6812},
}
This letter develops an optimum beamforming method for downlink transmissions in cell-free massive multiple-input multiple-output (MIMO) systems, which employ a massive number of distributed access points to provide concurrent services to multiple users. The optimum design is formulated as a max-min problem that maximizes the minimum signal-to-interference-plus-noise ratio of all users. It is shown analytically that the problem is quasi-concave, and the optimum solution is obtained with the second-order cone programming. The proposed method identifies the best achievable beamforming performance in cell-free massive MIMO systems. The results can be used as benchmarks for the design of practical low complexity beamformers.
@article{diva2:1485146,
author = {Zhou, Andong and Wu, Jingxian and Larsson, Erik G and Fan, Pingzhi},
title = {{Max-Min Optimal Beamforming for Cell-Free Massive MIMO}},
journal = {IEEE Communications Letters},
year = {2020},
volume = {24},
number = {10},
pages = {2344--2348},
}
Modern society has been widely benefiting from the advances in wireless technology. During the past decade, extensive research efforts have been dedicated to develop the fifth-generation (5G) wireless mobile networks. This resulted in enabling technologies for the three generic connectivity types in 5G (broadband, massive Internet-of-things connectivity and ultra-reliable low latency communication) as well as their coexistence. The final look of what will be called 5G is decided by the standardization process and it will not necessarily match the original ambitious vision of 5G. Due to this, as well as the extended time that will be required to deploy 5G ubiquitously, there are already initiatives to carry out research on 6G wireless networks. Those would have to respond to the exponential growth of mobile traffic due to AR/VR, holographic communications, V2X, autonomous driving, networked intelligence, and other, yet unknown use cases of Internet-of-Everything (IoE). These demanding use cases call for revolutionary design and novel enabling technologies on spectrum-, energy-, and cost-efficient communications for the sixth-generation (6G) mobile networks.
@article{diva2:1485025,
author = {Liang, Ying-Chang and Niyato, Dusit and Larsson, Erik G and Popovski, Petar},
title = {{6G mobile networks:
Emerging technologies and applications}},
journal = {China Communications},
year = {2020},
volume = {17},
number = {9},
pages = {90--91},
}
This paper considers the sum spectral efficiency (SE) optimization problem in multi-cell Massive MIMO systems with a varying number of active users. This is formulated as a joint pilot and data power control problem. Since the problem is non-convex, we first derive a novel iterative algorithm that obtains a stationary point in polynomial time. To enable real-time implementation, we also develop a deep learning solution. The proposed neural network, PowerNet, only uses the large-scale fading information to predict both the pilot and data powers. The main novelty is that we exploit the problem structure to design a single neural network that can handle a dynamically varying number of active users; hence, PowerNet is simultaneously approximating many different power control functions with varying number inputs and outputs. This is not the case in prior works and thus makes PowerNet an important step towards a practically useful solution. Numerical results demonstrate that PowerNet only loses 2% in sum SE, compared to the iterative algorithm, in a nine-cell system with up to 90 active users per in each coherence interval, and the runtime was only 0.03 ms on a graphics processing unit (GPU). When good data labels are selected for the training phase, PowerNet can yield better sum SE than by solving the optimization problem with one initial point.
@article{diva2:1471716,
author = {Van Chien, Trinh and Canh, Thuong Nguyen and Björnson, Emil and Larsson, Erik G.},
title = {{Power Control in Cellular Massive MIMO With Varying User Activity:
A Deep Learning Solution}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {9},
pages = {5732--5748},
}
Multiple-input multiple-output (MIMO) is a favorable technique that can improve system capacity and performance through spatial multiplexing. However, the performance gets degraded over the correlated wireless channels. In this letter, we consider a point-to-point MIMO system and jointly optimize both the precoding matrix and the difference between two transmit vectors to resist transmit correlation. The simulation results demonstrate that the proposed method can get average 75% gain comparing with the existing method in terms of the minimum pairwise error probability.
@article{diva2:1471698,
author = {Li, Gen and Mishra, Deepak and Hao, Li and Ma, Zheng and Larsson, Erik G.},
title = {{Optimal Open-Loop MIMO Precoder Design}},
journal = {IEEE Communications Letters},
year = {2020},
volume = {24},
number = {9},
pages = {2075--2079},
}
We consider joint beamforming of data to scheduled terminals (STs) and broadcast of system information (SI) to idle terminals (ITs) on the same time-frequency resource in multi-cell multi-user massive MIMO systems. We consider two different types of SI broadcast, i) synchronous broadcast of common (i.e., same) SI symbols from all cells, and ii) synchronous broadcast of cell-specific SI symbols from each cell. Through analysis we derive expressions for the achievable sum rate to STs in each cell and the rate of SI transmission to an IT for both these types of SI broadcast. We also derive expressions for the sum rate to STs and the rate to an IT for traditional orthogonal access (OA) where a fraction of physical resource is reserved for broadcast of SI. Simulations reveal that, just as in the single-cell scenario, for the multi-cell scenario also, joint beamforming and broadcasting (JBB) is more energy efficient than OA.
@article{diva2:1471683,
author = {Jayachandran, Jinu and Biswas, Kamal and Mohammed, Saif Khan and Larsson, Erik G.},
title = {{Efficient Techniques for In-Band System Information Broadcast in Multi-cell Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {10},
pages = {6157--6173},
}
n/a
@article{diva2:1471104,
author = {Björnson, Emil and Giselsson, Pontus},
title = {{Two Applications of Deep Learning in the Physical Layer of Communication Systems}},
journal = {IEEE signal processing magazine (Print)},
year = {2020},
volume = {37},
number = {5},
pages = {134--140},
}
n/a
@article{diva2:1471036,
author = {Zhang, Jiayi and Björnson, Emil and Matthaiou, Michail and Ng, Derrick Wing Kwan and Yang, Hong and Love, David J.},
title = {{Special Issue on Multiple Antenna Technologies for Beyond 5G-Part II}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2020},
volume = {38},
number = {9},
pages = {1941--1944},
}
In this paper, we study joint power control and scheduling in uplink massive multiple-input-multiple-output (MIMO) systems with randomly arriving data traffic. We consider both co-located and Cell-Free (CF) Massive MIMO, where the difference lies in whether the antennas are co-located at the base station or spread over a wide network area. The data is generated at each user according to an individual stochastic process. Using Lyapunov optimization techniques, we develop a dynamic scheduling algorithm (DSA), which decides at each time slot the amount of data to admit to the transmission queues and the transmission rates over the wireless channel. The proposed algorithm optimizes the long-term user throughput under various fairness policies while keeping the transmission queues stable. Simulation results show that the state-of-the-art power control schemes developed for Massive MIMO with infinite backlogs can fail to stabilize the system even when the data arrival rates are within the network capacity region. Our proposed DSA shows advantage in providing finite delay with performance optimization whenever the network can be stabilized. © 2017 IEEE.
@article{diva2:1468895,
author = {Chen, Zheng and Björnson, Emil and Larsson, Erik G},
title = {{Dynamic Resource Allocation in Co-Located and Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Green Communications and Networking},
year = {2020},
volume = {4},
number = {1},
pages = {209--220},
}
Multiple antenna technologies have attracted much research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are adopted. Since multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna technologies to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. Radically new approaches are required to achieve orders-of-magnitude improvements in these metrics. There will be large technical challenges, many of which are yet to be identified. In this paper, we survey three new multiple antenna technologies that can play key roles in beyond 5G networks: cell-free massive MIMO, beamspace massive MIMO, and intelligent reflecting surfaces. For each of these technologies, we present the fundamental motivation, key characteristics, recent technical progresses, and provide our perspectives for future research directions. The paper is not meant to be a survey/tutorial of a mature subject, but rather serve as a catalyst to encourage more research and experiments in these multiple antenna technologies.
@article{diva2:1466616,
author = {Zhang, Jiayi and Björnson, Emil and Matthaiou, Michail and Ng, Derrick Wing Kwan and Yang, Hong and Love, David J.},
title = {{Prospective Multiple Antenna Technologies for Beyond 5G}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2020},
volume = {38},
number = {8},
pages = {1637--1660},
}
n/a
@article{diva2:1466615,
author = {Zhang, Jiayi and Björnson, Emil and Matthaiou, Michail and Ng, Derrick Wing Kwan and Yang, Hong and Love, David J.},
title = {{Guest Editorial Special Issue on Multiple Antenna Technologies for Beyond 5G-Part-I}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2020},
volume = {38},
number = {8},
pages = {1633--1636},
}
Imagine a coverage area with many wireless access points that cooperate to jointly serve the users, instead of creating autonomous cells. Such a cell-free network operation can potentially resolve many of the interference issues that appear in current cellular networks. This ambition was previously called Network MIMO (multiple-input multiple-output) and has recently reappeared under the name Cell-Free Massive MIMO. The main challenge is to achieve the benefits of cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to large networks with many users. We propose a new framework for scalable Cell-Free Massive MIMO systems by exploiting the dynamic cooperation cluster concept from the Network MIMO literature. We provide a novel algorithm for joint initial access, pilot assignment, and cluster formation that is proved to be scalable. Moreover, we adapt the standard channel estimation, precoding, and combining methods to become scalable. A new uplink and downlink duality is proved and used to heuristically design the precoding vectors on the basis of the combining vectors. Interestingly, the proposed scalable precoding and combining outperform conventional maximum ratio (MR) processing and also performs closely to the best unscalable alternatives.
@article{diva2:1460226,
author = {Björnson, Emil and Sanguinetti, Luca},
title = {{Scalable Cell-Free Massive MIMO Systems}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {7},
pages = {4247--4261},
}
We consider backward crosstalk in 2 x 2 transmitters, which is caused by crosstalk from the outputs of the transmitter to the inputs or by the combination of output crosstalk and impedance mismatch. We analyze its impact via feedback networks together with third-order power amplifier non-linearities. We utilize the Bussgang decomposition to express the distorted output signals of the transmitter as a linear transformation of the input plus uncorrelated distortion. The normalized mean-square errors (NMSEs) between the distorted and desired amplified signals are expressed analytically and the optimal closed-form power back-off that minimizes the worst NMSE of the two branches is derived. In the second part of the paper, an achievable spectral efficiency (SE) is presented for the communication from this "dirty" transmitter to another single-antenna receiver. The SE-maximizing precoder is optimally found by exploiting the hardware characteristics. Furthermore, the optimal power back-off is analyzed for two sub-optimal precoders, which either do not exploit any hardware knowledge or only partial knowledge. The simulation results show that the performance of these sub-optimal precoders is close-to-optimal. We also discuss how the analysis in this paper can be extended to transmitters with an arbitrary number of antenna branches.
@article{diva2:1460220,
author = {Handel, Peter and Tugfe Demir, Özlem Tugfe and Björnson, Emil and Ronnow, Daniel},
title = {{Impact of Backward Crosstalk in 2 x 2 MIMO Transmitters on NMSE and Spectral Efficiency}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {7},
pages = {4277--4292},
}
Cell-free Massive MIMO (multiple-input multiple-output) is a promising distributed network architecture for 5G-and-beyond systems. It guarantees ubiquitous coverage at high spectral efficiency (SE) by leveraging signal co-processing at multiple access points (APs), aggressive spatial user multiplexing and extraordinary macro-diversity gain. In this study, we propose two distributed precoding schemes, referred to as local partial zero-forcing (PZF) and local protective partial zero-forcing (PPZF), that further improve the spectral efficiency by providing an adaptable trade-off between interference cancelation and boosting of the desired signal, with no additional front-hauling overhead, and implementable by APs with very few antennas. We derive closed-form expressions for the achievable SE under the assumption of independent Rayleigh fading channel, channel estimation error and pilot contamination. PZF and PPZF can substantially outperform maximum ratio transmission and zero-forcing, and their performance is comparable to that achieved by regularized zero-forcing (RZF), which is a benchmark in the downlink. Importantly, these closed-form expressions can be employed to devise optimal (long-term) power control strategies that are also suitable for RZF, whose closed-form expression for the SE is not available.
@article{diva2:1460199,
author = {Interdonato, Giovanni and Karlsson, Marcus and Björnson, Emil and Larsson, Erik G},
title = {{Local Partial Zero-Forcing Precoding for Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {7},
pages = {4758--4774},
}
In this paper, we consider how the uplink transmission of a spatially correlated massive multiple-input multiple-output (MIMO) system can be protected from a jamming attack. To suppress the jamming, we propose a novel framework including a new optimal linear estimator in the training phase and a bilinear equalizer in the data phase. The proposed estimator is optimal in the sense of maximizing the spectral efficiency of the legitimate system attacked by a jammer, and its implementation needs the statistical knowledge about the jammers channel. We derive an efficient algorithm to estimate the jamming information needed for implementation of the proposed framework. Furthermore, we demonstrate that optimized power allocation at the legitimate users can improve the performance of the proposed framework regardless of the jamming power optimization. Our proposed framework can be exploited to combat jamming in scenarios with either ideal or non-ideal hardware at the legitimate users and the jammer. Numerical results reveal that using the proposed framework, the jammer cannot dramatically affect the performance of the legitimate system.
@article{diva2:1454707,
author = {Akhlaghpasand, Hossein and Björnson, Emil and Razavizadeh, S. Mohammad},
title = {{Jamming-Robust Uplink Transmission for Spatially Correlated Massive MIMO Systems}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {6},
pages = {3495--3504},
}
In this paper, we consider a downlink non-orthogonal multiple access (NOMA) enabled heterogeneous small cells network (HSCN), where the macro base station simultaneously communicates with multiple small cell base stations (SBSs) through wireless backhaul. In each small cell, users are grouped by NOMA bases and then served by their respective SBS. The proposed framework considers the realistic imperfect channel state information and quality of service requirements of users. The goal is to investigate an energy-efficient joint power, and bandwidth allocation scheme, which aims to maximize the energy efficiency (EE) of the small cells in downlink NOMA-HSCN constrained by the maximum transmit power and the minimum required data rate simultaneously. The optimization problem is non-convex due to the fractional objective function and non-convex constraint and thus challenging to obtain an exact solution efficiently. To this end, the joint optimization is first decomposed into two subproblems. Then, an iterative algorithm to solve the power optimization subproblem is proposed with guaranteed convergence. Furthermore, we derive a closed-form solution for the bandwidth allocation subproblem. Simulation results reveal that the effectiveness of the proposed schemes in terms of EE compared to the existing NOMA and the orthogonal multiple access schemes.
@article{diva2:1454705,
author = {Muhammed, Alemu Jorgi and Ma, Zheng and Zhang, Zhengquan and Fan, Pingzhi and Larsson, Erik G},
title = {{Energy-Efficient Resource Allocation for NOMA Based Small Cell Networks With Wireless Backhauls}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {6},
pages = {3766--3781},
}
This paper studies the transmit power optimization in multi-cell Massive multiple-input multiple-output (MIMO) systems. Network-wide max-min fairness (NW-MMF) and network-wide proportional fairness (NW-PF) are two well-known power control schemes in the literature. The NW-MMF focus on maximizing the fairness among users at the cost of penalizing users with good channel conditions. On the other hand, the NW-PF focuses on maximizing the sum SE, thereby ignoring fairness, but gives some extra attention to the weakest users. However, both of these schemes suffer from a scalability issue which means that for large networks, it is highly probable that one user has a very poor channel condition, pushing the spectral efficiency (SE) of all users towards zero. To overcome the scalability issue of NW-MMF and NW-PF, we propose a novel power control scheme that is provably scalable. This scheme maximizes the geometric mean (GM) of the per-cell max-min SE. To solve this new optimization problem, we prove that it can be rewritten in a convex optimization form and then solved using standard tools. The simulation results highlight the benefits of our model which is balancing between NW-PF and NW-MMF.
@article{diva2:1454697,
author = {Ghazanfari, Amin and Cheng, Hei Victor and Björnson, Emil and Larsson, Erik G},
title = {{Enhanced Fairness and Scalability of Power Control Schemes in Multi-Cell Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {5},
pages = {2878--2890},
}
In this work, the performance evaluation and the optimization of dual-hop LoRa network are investigated. In particular, the coverage probability (Pcov) of edge end-devices (EDs) is computed in closed-form expressions under various fading channels, i.e., Nakagami-m and Rayleigh fading. The Pcov under Nakagami-m fading is computed in the approximated closed-form expressions; the Pcov under Rayleigh fading, on the other hand, is calculated in the exact closed-form expressions. In addition, we also investigate the impact of different kinds of interference on the performance of the Pcov, i.e., intra-SF interference, inter-SF interference (or capture effect) and both intra- and inter-SF interference. Our findings show that the impact of imperfect orthogonality is not non-negligible, along with the intra-SF interference. Moreover, based on the proposed mathematical framework, we formulate an optimization problem, which finds the optimal location of the relay to maximize the coverage probability. Since it is a mixed integer program with a non-convex objective function, we decompose the original problem with discrete optimization variables into sub-problems with a convex feasible set. After that, each sub-problem is effectively solved by utilizing the gradient descent approach. Monte Carlo simulations are supplied to verify the correctness of our mathematical framework. In addition, the results manifest that our proposed optimization algorithm converges rapidly, and the coverage probability is significantly improved when the location of relay is optimized.
@article{diva2:1454687,
author = {Hoa Nguyen, Tien and Jung, Woo-Sung and Thanh Tu, Lam and van Chien, Trinh and Yoo, Daeseung and Ro, Soonghwan},
title = {{Performance Analysis and Optimization of the Coverage Probability in Dual Hop LoRa Networks With Different Fading Channels}},
journal = {IEEE Access},
year = {2020},
volume = {8},
pages = {107087--107102},
}
We consider the performance of time-division duplex (TDD) massive multiple-input multiple-output (MIMO) with imperfect calibration of the transmit and receive radio frequency chains. By deriving the achievable signal-to-interference-plus-noise ratio & x00A0;(SINR) and the per-user bit error rate & x00A0;(BER) for constant modulus constellations, we establish that, under linear precoding, reciprocity imperfections can result in substantial reduction of the array gain. To mitigate this loss, we propose an algorithm for blind estimation of the effective channel gain at each user. We show that, with sufficiently many downlink data symbols, our blind channel estimation algorithm restores the array gain. In addition, the proposed blind gain estimation algorithm can improve performance compared to standard hardening-based receivers even under perfect reciprocity. Following this, we derive the BERs for non-constant modulus constellations, viz.& x00A0;-PAM and -QAM. We corroborate all our derived results using numerical simulations.
@article{diva2:1454684,
author = {Chopra, Ribhu and Murthy, Chandra R. and Suraweera, Himal A. and Larsson, Erik G},
title = {{Blind Channel Estimation for Downlink Massive MIMO Systems With Imperfect Channel Reciprocity}},
journal = {IEEE Transactions on Signal Processing},
year = {2020},
volume = {68},
pages = {3132--3145},
}
Reconfigurable intelligent surfaces (RIS) is a promising solution to build a programmable wireless environment via steering the incident signal in fully customizable ways with reconfigurable passive elements. In this paper, we consider a RIS-aided multiuser multiple-input single-output (MISO) downlink communication system. Our objective is to maximize the weighted sum-rate (WSR) of all users by joint designing the beamforming at the access point (AP) and the phase vector of the RIS elements, while both the perfect channel state information (CSI) setup and the imperfect CSI setup are investigated. For perfect CSI setup, a low-complexity algorithm is proposed to obtain the stationary solution for the joint design problem by utilizing the fractional programming technique. Then, we resort to the stochastic successive convex approximation technique and extend the proposed algorithm to the scenario wherein the CSI is imperfect. The validity of the proposed methods is confirmed by numerical results. In particular, the proposed algorithm performs quite well when the channel uncertainty is smaller than 10%.
@article{diva2:1444124,
author = {Guo, Huayan and Liang, Ying-Chang and Chen, Jie and Larsson, Erik G},
title = {{Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {5},
pages = {3064--3076},
}
Intelligent reflecting surfaces can improve the communication between a source and a destination. The surface contains metamaterial that is configured to "reflect" the incident wave from the source towards the destination. Two incompatible pathloss models have been used in prior work. In this letter, we derive the far-field pathloss using physical optics techniques and explain why the surface consists of many elements that individually act as diffuse scatterers but can jointly beamform the signal in a desired direction with a certain beamwidth. We disprove one of the previously conjectured pathloss models.
@article{diva2:1444122,
author = {Özdogan, Özgecan and Björnson, Emil and Larsson, Erik G},
title = {{Intelligent Reflecting Surfaces: Physics, Propagation, and Pathloss Modeling}},
journal = {IEEE Wireless Communications Letters},
year = {2020},
volume = {9},
number = {5},
pages = {581--585},
}
We correct the achievable rates (42) and (47) for small cells in "Cell-free massive MIMO versus small cells," IEEE Trans. Wireless Commun., vol. 16, 2017.
@article{diva2:1444123,
author = {Ngo, Hien Quoc and Ashikhmin, Alexei and Yang, Hong and Larsson, Erik G and Marzetta, Thomas L.},
title = {{Correction: Cell-Free Massive MIMO Versus Small Cells (vol 16, pg 1834, 2017)}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {5},
pages = {3623--3624},
}
Mismatches affect the dynamic performance of time-interleaved analog-to-digital converters (TIADCs). Linear mismatches can be calibrated by many mature methods, but if higher performance is required, nonlinearity mismatches have to be suppressed. The background calibration method based on input-free band (IFB) functions poorly for narrow-band signals. This brief proposes a correlation-based calibration method for nonlinearity mismatches in dual-channel TIADCs which behaves well for both wide-band and narrow-band signals. The output samples are calibrated by reducing the residual distortions which are approximated by multiplying the pseudo distortions and the estimated mismatch coefficients. The pseudo distortions are acquired by using a frequency-shifter, a differentiator, and multipliers. The coefficients which indicate the mismatch strength are estimated by eliminating the cross-correlation of the calibrated output samples and the calibrated pseudo distortions at zero lag. Simulations show that the proposed method can improve the SFDR by dozens of dBc for narrow-band input signals, compared with the IFB method. For the 16-QAM signal, the error vector magnitude improvement over the IFB method is 35.48 dB.
@article{diva2:1428583,
author = {Liu, Xiangyu and Xu, Hui and Johansson, Håkan and Wang, Yinan and Li, Nan},
title = {{Correlation-Based Calibration for Nonlinearity Mismatches in Dual-Channel TIADCs}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2020},
volume = {67},
number = {3},
pages = {585--589},
}
Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.
@article{diva2:1423721,
author = {Ucuncu, Ali Bulut and Björnson, Emil and Johansson, Håkan and Yilmaz, Ali Ozgur and Larsson, Erik G},
title = {{Performance Analysis of Quantized Uplink Massive MIMO-OFDM With Oversampling Under Adjacent Channel Interference}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {2},
pages = {871--886},
}
5G wireless communication networks are currently being deployed, and B5G networks are expected to be developed over the next decade. AI technologies and, in particular, ML have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G. This article studies how AI and ML can be leveraged for the design and operation of B5G networks. We first provide a comprehensive survey of recent advances and future challenges that result from bringing AI/ML technologies into B5G wireless networks. Our survey touches on different aspects of wireless network design and optimization, including channel measurements, modeling, and estimation, physical layer research, and network management and optimization. Then ML algorithms and applications to B5G networks are reviewed, followed by an overview of standard developments of applying AI/ML algorithms to B5G networks. We conclude this study with future challenges on applying AI/ML to B5G networks.
@article{diva2:1417686,
author = {Wang, Cheng-Xiang and Di Renzo, Marco and Stanczak, Slawomir and Wang, Sen and Larsson, Erik G},
title = {{Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges}},
journal = {IEEE wireless communications},
year = {2020},
volume = {27},
number = {1},
pages = {16--23},
}
Global navigation satellite systems (GNSS) are being the target of various jamming, spoofing, and meaconing attacks. This paper proposes a new statistical test for the presence of multiple spoofers based on range measurements observed by a plurality of receivers located on a rigid body platform. The relative positions of the receivers are known, but the location and orientation of the platform are unknown. The test is based on the generalized likelihood ratio test (GLRT) paradigm and essentially performs a consistency check between the set of observed range measurements and known information about the satellite topology and the geometry of the receiver constellation. Optimal spoofing locations and optimal artificial time delays (as induced by the spoofers) are also determined.Exact evaluation of the GLRT requires the maximum-likelihood estimates of all parameters, which proves difficult. Instead, approximations based on iterative algorithms and the squared-range least squares algorithm are derived. The accuracy of these approximations is benchmarked against Cramer-Rao lower bounds.Numerical examples demonstrate the effectiveness of the proposed algorithm and show that increasing the number of GNSS receivers makes the attack easier to detect. We also show that using multiple GNSS receivers limits the availability of optimal attack positions.
@article{diva2:1417565,
author = {Kalantari, Ashkan and Larsson, Erik G},
title = {{Statistical test for GNSS spoofing attack detection by using multiple receivers on a rigid body}},
journal = {EURASIP Journal on Advances in Signal Processing},
year = {2020},
volume = {2020},
number = {1},
}
The rate and energy efficiency of wireless channels can be improved by deploying software-controlled metasurfaces to reflect signals from the source to the destination, especially when the direct path is weak. While previous works mainly optimized the reflections, this letter compares the new technology with classic decode-and-forward (DF) relaying. The main observation is that very high rates and/or large metasurfaces are needed to outperform DF relaying, both in terms of minimizing the total transmit power and maximizing the energy efficiency, which also includes the dissipation in the transceiver hardware.
@article{diva2:1417552,
author = {Björnson, Emil and Özdogan, Özgecan and Larsson, Erik G},
title = {{Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces are Needed to Beat Relaying?}},
journal = {IEEE Wireless Communications Letters},
year = {2020},
volume = {9},
number = {2},
pages = {244--248},
}
Cell-free Massive MIMO is considered as a promising technology for satisfying the increasing number of users and high rate expectations in beyond-5G networks. The key idea is to let many distributed access points (APs) communicate with all users in the network, possibly by using joint coherent signal processing. The aim of this paper is to provide the first comprehensive analysis of this technology under different degrees of cooperation among the APs. Particularly, the uplink spectral efficiencies of four different cell-free implementations are analyzed, with spatially correlated fading and arbitrary linear processing. It turns out that it is possible to outperform conventional Cellular Massive MIMO and small cell networks by a wide margin, but only using global or local minimum mean-square error (MMSE) combining. This is in sharp contrast to the existing literature, which advocates for maximum-ratio combining. Also, we show that a centralized implementation with optimal MMSE processing not only maximizes the SE but largely reduces the fronthaul signaling compared to the standard distributed approach. This makes it the preferred way to operate Cell-free Massive MIMO networks. Non-linear decoding is also investigated and shown to bring negligible improvements.
@article{diva2:1393697,
author = {Björnson, Emil and Sanguinetti, Luca},
title = {{Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation}},
journal = {IEEE Transactions on Wireless Communications},
year = {2020},
volume = {19},
number = {1},
pages = {77--90},
}
Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key concepts are adopted into the 5G New Radio Standard and base stations (BSs) with $M=64$ fully digital transceivers have been commercially deployed in sub-6GHz bands. The fast progress was enabled by many solid research contributions of which the vast majority assume spatially uncorrelated channels and signal processing schemes developed for single-cell operation. These assumptions make the performance analysis and optimization of Massive MIMO tractable but have three major caveats: 1) practical channels are spatially correlated; 2) large performance gains can be obtained by multicell processing, without BS cooperation; 3) the interference caused by pilot contamination creates a finite capacity limit, as $M\to \infty $ . There is a thin line of papers that avoided these caveats, but the results are easily missed. Hence, this tutorial article explains the importance of considering spatial channel correlation and using signal processing schemes designed for multicell networks. We present recent results on the fundamental limits of Massive MIMO, which are not determined by pilot contamination but the ability to acquire channel statistics. These results will guide the journey towards the next level of Massive MIMO, which we call "Massive MIMO 2.0".
@article{diva2:1393685,
author = {Sanguinetti, Luca and Björnson, Emil and Hoydis, Jakob},
title = {{Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {1},
pages = {232--257},
}
In this brief, we propose a framework for protecting the uplink transmission of a massive multiple-input multiple-output (mMIMO) system from a jamming attack. Our framework includes a novel minimum mean-squared error-based jamming suppression (MMSE-JS) estimator for channel training and a linear zero-forcing jamming suppression (ZFJS) detector for uplink combining. The MMSE-JS exploits some intentionally unused pilots to reduce the pilot contamination caused by the jammer. The ZFJS suppresses the jamming interference during the detection of the legitimate users data symbols. The proposed framework is implementable, since the complexities of computing the MMSE-JS and the ZFJS are linear (not exponential) with respect to the number of antennas at the base station and can be fabricated using 28-nm fully depleted silicon on insulator technology and for the mMIMO systems. Our analysis shows that the jammer cannot dramatically affect the performance of an mMIMO system equipped with the combination of MMSE-JS and ZFJS. Numerical results confirm our analysis.
@article{diva2:1391034,
author = {Akhlaghpasand, Hossein and Björnson, Emil and Razavizadeh, S. Mohammad},
title = {{Jamming Suppression in Massive MIMO Systems}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2020},
volume = {67},
number = {1},
pages = {182--186},
}
Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers from data interference that reduces the SE gains. This paper proposes the Massive-MIMO Iterative Channel Estimation and Decoding (MICED) algorithm where partially decoded data is used as side-information to improve the channel estimation and increase SE. We show that users with precise data estimates can help users with poor data estimates to decode. Numerical results with QPSK modulation and LDPC codes show that the MICED algorithm increases the SE and reduces the block-error-rate with RP and SP compared to conventional methods. The MICED algorithm with SP delivers the highest SE and it is especially effective in scenarios with short coherence blocks like high mobility or high frequencies.
@article{diva2:1385654,
author = {Verenzuela, Daniel and Björnson, Emil and Wang, Xiaojie and Arnold, Maximilian and Brink, Stephan ten},
title = {{Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink}},
journal = {IEEE Transactions on Communications},
year = {2020},
volume = {68},
number = {2},
pages = {854--870},
}
Full-duplex two-way relay (FD-TWR) system has potential to increase the spectral efficiency in the future 5G wireless system. Full-duplex transceiver suffers from inevitable self-interference (SI) which can be alleviated by active self-interference cancellation (SIC) method. However, the mitigation capability of SIC mechanism is limited specifically due to inherent non-linearities of transmitter and receiver front end. As a consequence, residual self-interference (RSI) will degrade the systems signal-to-noise ratio (SNR) and throughput. Non-linearity in RF power amplifier in collusion with time-variant channel results is a great challenge in efficient signal detection and successful SI suppression. In contrast to classical schemes, which consider non-linear distortion at the transmitter, we present a semi-blind data detection and non-linear channel estimation in the presence of RSI at the receiver. Attributed to non-linearity, the target posterior probability density function is mathematically intractable. In this paper, a sequential importance sampling based particle filtering is used for joint data detection and estimation. Intractable distribution is approximated by using weighted random measures. A Taylors series expansion is used to locally linearize the non-analytic form of distribution. Numerical results validate the joint detection and channel estimation scheme. The robustness of the scheme is verified in presence of RSI under high mobility.
@article{diva2:1571515,
author = {Chakraborty, Sucharita and Sen, Debarati},
title = {{Semi-Blind Data Detection and Non-Linear Equalization in Full-Duplex TWR-OFDM Systems With High Mobility}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {12},
pages = {6000--6014},
}
The achievable rates are investigated for multicell multi-user massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing. A general pilot sharing scheme and two pilot sequence designs (PSDs) are investigated via fully shared (PSD-1) and partially shared (PSD-2) uplink pilots. The number of simultaneously served primary users and secondary users (SUs) in the same time-frequency resource block by the PSD-1 is higher than that of PSD-2. The transmit power constraints for the SUs are derived to mitigate the secondary co-channel interference (CCI) inflicted at the primary base-station (PBS) subject to a predefined primary interference temperature (PIT). The optimal transmit power control coefficients for the SUs with max-min fairness and the common achievable rates are derived. The cumulative detrimental effects of channel estimation errors, CCI and intra-cell/inter-cell pilot contamination are investigated. The secondary transmit power constraint and the achievable rates for the perfect channel state information (CSI) case become independent of the PIT when the number of PBS antennas grows unbounded. Therefore, the primary and secondary systems can be operated independent of each other as both intra-cell and inter-cell interference can be asymptotically mitigated at the massive MIMO PBS and secondary base-station. Nevertheless, the achievable rates and secondary power constraints for the imperfect CSI case with PSD-1 are severely degraded due to the presence of intra-cell and inter-cell pilot contamination. These performance metrics depend on the PIT even in the asymptotic PBS antenna regime. Hence, the primary and secondary systems can no longer be operated independently for imperfect CSI with PSD-1. However, PSD-2 provides an achievable rate gain over PSD-1 despite the requirement of lengthier pilot sequences of the former than that of the latter.
@article{diva2:1468909,
author = {Al-Hraishawi, Hayder and Baduge, Gayan Amarasuriya Aruma and Ngo, Hien Quoc and Larsson, Erik G},
title = {{Multi-Cell Massive MIMO Uplink With Underlay Spectrum Sharing}},
journal = {IEEE Transactions on Cognitive Communications and Networking},
year = {2019},
volume = {5},
number = {1},
pages = {119--137},
}
Green low power networking with the least requirement of dedicated radio resources is need of the hour which has led to the upsurge of backscatter communication (BSC) technology. However, this inherent potential of BSC is challenged by hardware constraints of the underlying tags. We address this timely concern by investigating the practical efficacy of multiple-input-multiple-output (MIMO) technology in overcoming the fundamental limitations of BSC. Specifically, we first introduce a novel least-squares based channel estimation (CE) protocol for multi-tag BSC settings that takes care of both the unintended ambient reflections and the inability of tags in performing estimation by themselves. Then using it, a nontrivial low-complexity algorithm is proposed to obtain the optimal transceiver designs for the multiantenna reader to maximize the minimum value of the lower-bounded backscattered throughput among the single-antenna semi-passive tags. Additional analytical insights on both individually and jointly-optimal precoding vector and detector matrix at the reader are provided by exploring the asymptotically-optimal transceiver designs. Lastly detailed numerical investigation is carried out to validate the theoretical results and quantify the practically realizable throughput fairness. Specifically, more than seven-fold increase in the common-backscattered-throughput among tags as achieved by the proposed designs over the relevant benchmarks corroborates their practical significance.
@article{diva2:1468907,
author = {Mishra, Deepak and Larsson, Erik G},
title = {{Multi-Tag Backscattering to MIMO Reader: Channel Estimation and Throughput Fairness}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {12},
pages = {5584--5599},
}
A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points (APs) are connected to a central processing unit (CPU) through limited-capacity wireless microwave links. The quantized version of the weighted signals are available at the CPU, by exploiting the Bussgang decomposition to model the effect of quantization. A closed-form expression for spectral efficiency is derived taking into account the effects of channel estimation error and quantization distortion. The energy efficiency maximization problem is considered with per-user power, backhaul capacity and throughput requirement constraints. To solve this non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design, and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas a successive convex approximation (SCA) and a heuristic sub-optimal scheme are exploited to convert the power allocation problem into a standard geometric programming (GP) problem. An iterative algorithm is proposed to alternately solve each sub-problem. Complexity analysis and convergence of the proposed schemes are investigated. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation.
@article{diva2:1468894,
author = {Bashar, Manijeh and Cumanan, Kanapathippillai and Burr, Alister G and Ngo, Hien Quoc and Larsson, Erik G and Xiao, Pei},
title = {{Energy Efficiency of the Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization}},
journal = {IEEE Transactions on Green Communications and Networking},
year = {2019},
volume = {3},
number = {4},
pages = {971--987},
}
What will it take for drones, and the whole associated ecosystem, to take off? Arguably, infallible Camp;C channels for safe and autonomous flying, and high-throughput links for multi-purpose live video streaming. And indeed, meeting these aspirations may entail full cellular support, provided through 5G-and-beyond hardware and software upgrades by both mobile operators and manufacturers of these UAVs. In this article, we vouch for massive MIMO as the key building block to realize 5G-connected UAVs. Through the sheer evidence of 3GPP-compliant simulations, we demonstrate how massive MIMO can be enhanced by complementary network-based and UAV-based solutions, resulting in consistent UAV Camp;C support, large UAV uplink data rates, and harmonious coexistence with legacy ground users.
@article{diva2:1382350,
author = {Garcia-Rodriguez, Adrian and Geraci, Giovanni and Lopez-Perez, David and Galati Giordano, Lorenzo and Ding, Ming and Björnson, Emil},
title = {{The Essential Guide to Realizing 5G-Connected UAVs with Massive MIMO}},
journal = {IEEE Communications Magazine},
year = {2019},
volume = {57},
number = {12},
pages = {84--90},
}
Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO is essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design. (C) 2019 Elsevier B.V. All rights reserved.
@article{diva2:1380720,
author = {Bana, Alexandru-Sabin and de Carvalho, Elisabeth and Soret, Beatriz and Abrao, Taufik and Marinello, Jose Carlos and Larsson, Erik G and Popovski, Petar},
title = {{Massive MIMO for Internet of Things (IoT) connectivity}},
journal = {Physical Communication},
year = {2019},
volume = {37},
}
In this paper, we study the uplink (UL) and downlink (DL) spectral efficiency (SE) of a cell-free massive multiple-input-multiple-output (MIMO) system over Rician fading channels. The phase of the line-of-sight (LoS) path is modeled as a uniformly distributed random variable to take the phase-shifts due to mobility and phase noise into account. Considering the availability of prior information at the access points (APs), the phase-aware minimum mean square error (MMSE), non-aware linear MMSE (LMMSE), and least-square (LS) estimators are derived. The MMSE estimator requires perfectly estimated phase knowledge whereas the LMMSE and LS are derived without it. In the UL, a two-layer decoding method is investigated in order to mitigate both coherent and non-coherent interference. Closed-form UL SE expressions with phase-aware MMSE, LMMSE, and LS estimators are derived for maximum-ratio (MR) combining in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. In the DL, two different transmission modes are studied: coherent and non-coherent. Closed-form DL SE expressions for both transmission modes with MR precoding are derived for the three estimators. Numerical results show that the LSFD improves the UL SE performance and coherent transmission mode performs much better than non-coherent transmission in the DL. Besides, the performance loss due to the lack of phase information depends on the pilot length and it is small when the pilot contamination is low.
@article{diva2:1379782,
author = {Özdogan, Özgecan and Björnson, Emil and Zhang, Jiayi},
title = {{Performance of Cell-Free Massive MIMO With Rician Fading and Phase Shifts}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {11},
pages = {5299--5315},
}
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks-in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies-once viewed prohibitively complicated and costly-is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO. (C) 2019 Elsevier Inc. All rights reserved.
@article{diva2:1371361,
author = {Björnson, Emil and Sanguinetti, Luca and Wymeersch, Henk and Hoydis, Jakob and Marzetta, Thomas L.},
title = {{Massive MIMO is a reality-What is next? Five promising research directions for antenna arrays}},
journal = {Digital signal processing (Print)},
year = {2019},
volume = {94},
}
Cell-free Massive MIMO (multiple-input multipleoutput) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works 1, 2 demonstrated that, unlike co-located Massive MIMO, the channel hardening is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the analysis in 1 to non-orthogonal uplink and downlink pilots. Assuming singleantenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the peruser achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacitybounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.
@article{diva2:1366418,
author = {Interdonato, Giovanni and Ngo, Hien Quoc and Frenger, Pål and Larsson, Erik G.},
title = {{Downlink Training in Cell-Free Massive MIMO:
A Blessing in Disguise}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {11},
pages = {5153--5169},
}
n/a
@article{diva2:1365715,
author = {Gao, Feifei and Tian, Zhi and Larsson, Erik G and Pesavento, Marius and Jin, Shi},
title = {{Introduction to the Special Issue on Array Signal Processing for Angular Models in Massive MIMO Communications}},
journal = {IEEE Journal on Selected Topics in Signal Processing},
year = {2019},
volume = {13},
number = {5},
pages = {882--885},
}
In this paper, multi-group multicast beamforming is considered for the full digital and hybrid beamforming. The wireless system comprises of a multiple-antenna base station and single-antenna users. Quality-of-service (QoS)-aware design is investigated where the optimization objective is to minimize the total transmitted power subject to the signal-to-interference-plus-noise ratio (SINR) constraint at each user. In addition to the SINR constraints, per-antenna power constraint is included for each antenna of the base station. The original optimization problem for full digital beamforming is transformed into an equivalent form such that the alternating direction method of multipliers (ADMM) can be applied in an effective and computationally inexpensive manner for the large-scale antenna systems. In this new formulation, the beamformer weight vectors are decomposed into two subspaces in order to decrease the number of dual variables and multiplications. The optimum update equations are obtained for the proposed ADMM algorithm. This new reformulation is used for two different hybrid beamforming structures employing phase shifters and vector modulators. Optimum updates are derived for each system. The proposed algorithms decrease computational complexity of the existing ADMM algorithms due to the effective reformulation as well as the direct solution of the nonconvex problem. In the simulation results, it is shown that the proposed methods have better convergence behavior and less computational time than the benchmark algorithms. Furthermore, the proposed method for hybrid beamforming with vector modulators performs better than its counterpart in the literature in terms of transmitted power. (C) 2019 Elsevier Inc. All rights reserved.
@article{diva2:1362731,
author = {Tugfe Demir, Özlem Tugfe and Tuncer, Temel Engin},
title = {{Improved ADMM-based algorithms for multi-group multicasting in large-scale antenna systems with extension to hybrid beamforming}},
journal = {Digital signal processing (Print)},
year = {2019},
volume = {93},
pages = {43--57},
}
Backscatter communication (BSC) is being realized as the core technology for pervasive sustainable Internet-of-Things applications. However, owing to the resource limitations of passive tags, the efficient usage of multiple antennas at the reader is essential for both downlink excitation and uplink detection. This paper targets at maximizing the achievable sum-backscattered throughput by jointly optimizing the transceiver (TRX) design at the reader and backscattering coefficients (BCs) at the tags. Since this joint problem is nonconvex, we first present individually optimal designs for the TRX and BC. We show that with precoder and combiner designs at the reader, respectively, targeting downlink energy beamforming and uplink Wiener filtering operations, the BC optimization at tags can be reduced to a binary power control problem. Next, the asymptotically optimal joint-TRX-BC designs are proposed for both low- and high-signal-to-noise ratio regimes. Based on these developments, an iterative low-complexity algorithm is proposed to yield an efficient jointly suboptimal design. Thereafter, we discuss the practical utility of the proposed designs to other application settings, such as wireless powered communication networks and BSC with imperfect channel state information. Finally, selected numerical results, validating the analysis and shedding novel insights, demonstrate that the proposed designs can yield significant enhancement in the sum-backscattered throughput over existing benchmarks.
@article{diva2:1360251,
author = {Mishra, Deepak and Larsson, Erik G},
title = {{Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {8},
pages = {5689--5705},
}
Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users and hence increases the spectral and energy efficiency (see references herein). It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguish ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.
@article{diva2:1343893,
author = {Interdonato, Giovanni and Björnson, Emil and Quoc Ngo, Hien and Frenger, Pal and Larsson, Erik G},
title = {{Ubiquitous cell-free Massive MIMO communications}},
journal = {EURASIP Journal on Wireless Communications and Networking},
year = {2019},
}
Regularized zero forcing (RZF) precoding is an efficient linear precoding scheme for combating interference in a single-cell massive multiple-input-multiple-output (MIMO) systems. Inaccurate channel state information (CSI) due to channel aging will reduce the performance of the precoder over time. The channel aging determines how often we need to estimate the channels, and thus how frequently we need to send pilots in order to maximize the overall data rate. Channel prediction is one way to improve the CSI accuracy in the downlink, without having to send new pilots but it requires frequent re-computation of the matrix inverse in the RZF precoder, which has high-computational complexity. In this paper, we consider massive MIMO-OFDM systems and propose an algorithm called inverse extrapolation that extrapolates the channel and inverse matrix coefficients separately. The RZF coefficients are then obtained with comparably low complexity with no need for matrix inversion. We compare this algorithm with the traditional way of computing the RZF coefficients through prediction of the channel matrix followed by matrix inversion. The simulation results show that the two predictors have the same performance when the number of antennas is large, and thus the proposed scheme is preferable since it can reduce the complexity. For example, a scenario is shown, where the complexity is reduced by 61.84% without a significant degradation in performance.
@article{diva2:1343848,
author = {Wu, Shijuan and Björnson, Emil and Mollen, Christopher and Tao, Xiaofeng and Larsson, Erik G},
title = {{Inverse Extrapolation for Efficient Precoding in Time-Varying Massive MIMO-OFDM Systems}},
journal = {IEEE Access},
year = {2019},
volume = {7},
pages = {91105--91119},
}
Unmanned aerial vehicles (UAVs), also known as drones, are proliferating. Applications, such as surveillance, disaster management, and drone racing, place high requirements on the communication with the drones in terms of throughput, reliability, and latency. The existing wireless technologies, notably Wi-Fi, that are currently used for drone connectivity are limited to short ranges and low-mobility situations. New, scalable technology is needed to meet future demands on long connectivity ranges, support for fast-moving drones, and the possibility to simultaneously communicate with entire swarms of drones. Massive multiple-input and multiple-output (MIMO), the main technology component of emerging 5G standards, has the potential to meet these requirements.
@article{diva2:1343849,
author = {Chandhar, Prabhu and Larsson, Erik G},
title = {{Massive MIMO for Connectivity With Drones: Case Studies and Future Directions}},
journal = {IEEE Access},
year = {2019},
volume = {7},
pages = {94676--94691},
}
Nonlinearities in various stages of a transmitter may hinder and restrict the transmission rate. As observed in many studies, outermost constellation points are usually more adversely affected by these impairments. To observe these effects, we utilize two power amplifier models that have different effects on transmitted signals. The Rapp model considers only amplitude deformation and the resultant in-phase and quadrature errors can be assumed to be independent on the receiver side. Unlike the Rapp model, the Saleh model exerts both amplitude and phase deformations and the phase deformation introduces correlation between the in-phase and quadrature errors according to our observations. In addition to the correlation, the variances of in-phase and quadrature errors may not be equal to each other. In this paper, we propose receivers that consider error variances of each quadrature amplitude modulation (QAM) symbol. We compare the performances of the receivers with those of other receivers that take average error variances into account for decoding. Furthermore, we propose a practical receiver that directly works on digitized observations based on a look-up table that keeps log-likelihood ratios of the quantized regions in order to reduce computational complexity.
@article{diva2:1342290,
author = {Gülgün, Ziya and Yılmaz, Ali Özgür},
title = {{Detection Schemes for High Order M-Ary QAM Under Transmit Nonlinearities}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {7},
pages = {4825--4834},
}
We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas M becomes sufficiently large. In addition, we study how the transmit power reduces with M to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to 1/M-alpha, 1/M beta, and 1/M-gamma for certain combinations of a, beta, and gamma, respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE.
@article{diva2:1342284,
author = {Kong, Chuili and Zhong, Caijun and Matthaiou, Michail and Björnson, Emil and Zhang, Zhaoyang},
title = {{Spectral Efficiency of Multipair Massive MIMO Two-Way Relaying With Imperfect CSI}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2019},
volume = {68},
number = {7},
pages = {6593--6607},
}
Usage of low-cost hardware in large antenna arrays and low-power wireless devices in Internet of Things (IoT) has led to the degradation of practical beamforming gains due to the underlying hardware impairments, such as in-phase and quadrature-phase imbalance (IQI). To address this timely concern, we present a new nontrivial closed-form expression for the globally optimal least squares estimator (LSE) for the IQI-influenced channel between a multiantenna transmitter and single-antenna IoT device. Thereafter, to maximize the realistic transmit beamforming gains, a novel precoder design is derived that accounts for the underlying IQI for maximizing received power in both single and multiuser settings. Finally, the simulation results, demonstrating a significant -8 dB improvement in the mean squared error of the proposed LSE over existing benchmarks, show that the optimal precoder designing is more critical than accurately estimating IQI-impaired channels. Also, the proposed jointly optimal LSE and beamformer outperforms the existing designs by providing 24% enhancement in mean signal power received under IQI.
@article{diva2:1339674,
author = {Mishra, Deepak and Johansson, Håkan},
title = {{Optimal Least Squares Estimator and Precoder for Energy Beamforming Over IQ-Impaired Channels}},
journal = {IEEE Signal Processing Letters},
year = {2019},
volume = {26},
number = {8},
pages = {1207--1211},
}
Smart multiantenna wireless power transmission can enable perpetual operation of energy harvesting (EH) nodes in the Internet-of-Things. Moreover, to overcome the increased hardware cost and space constraints associated with having large antenna arrays at the radio frequency (RF) energy source, the hybrid energy beamforming (EBF) architecture with single RF chain can be adopted. Using the recently proposed hybrid EBF architecture modeling the practical analog phase shifter impairments (API), we derive the optimal least-squares estimator for the energy source to an EH user channel. Next, the average harvested power at the user is derived while considering the nonlinear RF EH model and a tight analytical approximation for it is also presented by exploring the practical limits on the API. Using these developments, the jointly global optimal transmit power and time allocation for channel estimation (CE) and EBF phases, that maximizes the average energy stored at the EH user is derived in closed form. Numerical results validate the proposed analysis and present nontrivial design insights on the impact of API and CE errors on the achievable EBF performance. It is shown that the optimized hybrid EBF protocol with joint resource allocation yields an average performance improvement of 37% over benchmark fixed allocation scheme.
@article{diva2:1337579,
author = {Mishra, Deepak and Johansson, Håkan},
title = {{Optimal Channel Estimation for Hybrid Energy Beamforming Under Phase Shifter Impairments}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {6},
pages = {4309--4325},
}
This paper considers multi-cell massive multiple-input multiple-output systems, where the channels are spatially correlated Rician fading. The channel model is composed of a deterministic line-of-sight path and a stochastic non-line-of-sight component describing a practical spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE), element-wise MMSE, and least-square channel estimates for this model. Using these estimates for maximum ratio combining and precoding, rigorous closed-form uplink (UL) and downlink (DL) achievable spectral efficiency (SE) expressions are derived and analyzed. The asymptotic SE behavior, when using the different channel estimators, are also analyzed. The numerical results show that the SE is higher when using the MMSE estimator than that of the other estimators, and the performance gap increases with the number of antennas.
@article{diva2:1333832,
author = {Özdogan, Özgecan and Björnson, Emil and Larsson, Erik G.},
title = {{Massive MIMO With Spatially Correlated Rician Fading Channels}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {5},
pages = {3234--3250},
}
The use of base stations (BSs) and access points (APs) with a large number of antennas, called Massive MIMO (multiple-input multiple-output), is a key technology for increasing the capacity of 5G networks and beyond. While originally conceived for conventional sub-6 GHz frequencies, Massive MIMO (mMIMO) is also ideal for frequency bands in the range 30-300 GHz, known as millimeter wave (mmWave). Despite conceptual similarities, the way in which mMIMO can be exploited in these bands is radically different, due to their specific propagation behaviors and hardware characteristics. This article reviews these differences and their implications, while dispelling common misunderstandings. Building on this foundation, we suggest appropriate signal processing schemes and use cases to efficiently exploit mMIMO in both frequency bands.
@article{diva2:1333620,
author = {Björnson, Emil and Van der Perre, Liesbet and Buzzi, Stefano and Larsson, Erik G},
title = {{Massive MIMO in Sub-6 GHz and mmWave:
Physical, Practical, and Use-Case Differences}},
journal = {IEEE wireless communications},
year = {2019},
volume = {26},
number = {2},
pages = {100--108},
}
This paper seeks to answer a simple but fundamental question: what role can non-orthogonal multiple access (NOMA) play in massive multi-in multi-out (MIMO)? It is well established that power-domain NOMA schemes can outperform conventional orthogonal multiple access schemes in cellular networks. However, this fact does not imply that NOMA is the most efficient way to communicate in massive MIMO setups, where the base stations have many more antennas than there are users in the cell. These setups are becoming the norm in future networks and are usually studied by assuming spatial multiplexing of the users using linear multi-user beamforming. To answer the above-mentioned question, we analyze and compare the performance achieved by NOMA and multi-user beamforming in both non-line-of-sight and line-of-sight scenarios. We reveal that the latter scheme gives the highestaverage sum rate in massive MIMO setups. We also identify specific cases where NOMA is the better choice in massive MIMO and explain how NOMA plays an essential role in creating a hybrid of NOMA and multi-user beamforming that is shown to perform better than two standalone schemes do.
@article{diva2:1329199,
author = {Senel, Kamil and Cheng, Victor and Björnson, Emil and Larsson, Erik G},
title = {{What Role can NOMA Play in Massive MIMO?}},
journal = {IEEE Journal on Selected Topics in Signal Processing},
year = {2019},
volume = {13},
number = {3},
pages = {597--611},
}
Having lower quantization resolution, has been introduced in the literature, to reduce the power consumption of massive MIMO and millimeter wave MIMO systems. Here, we analyze the bit error rate (BER) performance of quantized uplink massive MIMO employing few-bit resolution ADCs. Considering ZF detection, we derive a signal-to-interference, quantization and noise ratio (SIQNR) to achieve an analytical BER approximation for coarsely quantized M-QAM massive MIMO systems, by using a linear quantization model. The proposed expression is a function of the quantization resolution in bits. We further numerically investigate the effects of different quantization levels, from 1-bit to 4-bits, on the BER of three modulation types QPSK, 16-QAM, and 64-QAM. The uniform and non-uniform quantizers are employed in our simulation. Monte Carlo simulation results reveal that our approximate formula gives a tight upper bound on the BER performance of b-bit resolution quantized systems using non-uniform quantizers, whereas the use of uniform quantizers cause a lower performance. We also found a small BER performance degradation in coarsely quantized systems, for example 2-3 bits QPSK and 3-4 bits 16-QAM, compared to the full-precision (unquantized) case. However, this performance degradation can be compensated by increasing the number of antennas at the BS. (C) 2019 Published by Elsevier B.V.
@article{diva2:1328797,
author = {Azizzadeh, Azad and Mohammadkhani, Reza and Makki, Seyed Vahab Al-Din and Björnson, Emil},
title = {{BER performance analysis of coarsely quantized uplink massive MIMO}},
journal = {Signal Processing},
year = {2019},
volume = {161},
pages = {259--267},
}
Massive MIMO network deployments are expected to be a key feature of the upcoming 5G communication systems. Such networks are able to achieve a high level of channel quality and can simultaneously serve multiple users with the same resources. In this paper, realistic massive MIMO channels are evaluated both in single and multi-cell environments. The favorable propagation property is evaluated in the single-cell scenario and provides perspectives on the minimal criteria required to achieve such conditions. The dense multi-cell urban scenario provides a comparison between linear, planar, circular, and cylindrical arrays to evaluate a large-scale multi-cell massive MIMO network. The system-level performance is predicted using two different kinds of channel models. First, a ray-based deterministic tool is utilized in a real North American city environment. Second, an independent and identically distributed (i.i.d.) Rayleigh fading channel model is considered, as often used in previously published massive MIMO studies. The analysis is conducted in a 16-macro-cell network with both randomly distributed outdoor and indoor users. It is shown that the physical array properties like the shape and configuration have a large impact on the throughput statistics. Although the system-level performance with i.i.d. Rayleigh fading can be close to the deterministic prediction in some situations (e.g., with large linear arrays), significant differences are noticed when considering other types of arrays. The differences in the performance of the various arrays utilizing the exact same network parameters and the same number of total antenna elements provide insights into the selection of these physical parameters for upcoming 5G networks.
@article{diva2:1328779,
author = {Aslam, Mohammed Zahid and Corre, Yoann and Björnson, Emil and Larsson, Erik G},
title = {{Performance of a dense urban massive MIMO network from a simulated ray-based channel}},
journal = {EURASIP Journal on Wireless Communications and Networking},
year = {2019},
}
We show that end-to-end learning of communication systems through deep neural network autoencoders can be extremely vulnerable to physical adversarial attacks. Specifically, we elaborate how an attacker can craft effective physical black-box adversarial attacks. Due to the openness (broadcast nature) of the wireless channel, an adversary transmitter can increase the block-error-rate of a communication system by orders of magnitude by transmitting a well-designed perturbation signal over the channel. We reveal that the adversarial attacks are more destructive than the jamming attacks. We also show that classical coding schemes are more robust than the autoencoders against both adversarial and jamming attacks.
@article{diva2:1328681,
author = {Sadeghi, Meysam and Larsson, Erik G},
title = {{Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems}},
journal = {IEEE Communications Letters},
year = {2019},
volume = {23},
number = {5},
pages = {847--850},
}
n/a
@article{diva2:1328666,
author = {Björnson, Emil},
title = {{Reproducible Research: Best Practices and Potential Misuse}},
journal = {IEEE signal processing magazine (Print)},
year = {2019},
volume = {36},
number = {3},
pages = {106--+},
}
In this paper, we consider device-to-device (D2D) communication that is underlaid in a multi-cell massive multiple-input multiple-output (MIMO) system and proposes a new framework for power control and pilot allocation. In this scheme, the cellular users (CUs) in each cell get orthogonal pilots which are reused with reuse factor one across cells, while all the D2D pairs share another set of orthogonal pilots. We derive a closed-form capacity lower bound for the CUs with different receive processing schemes. In addition, we derive a capacity lower bound for the D2D receivers and a closed-form approximation of it. We provide power control algorithms to maximize the minimum spectral efficiency (SE) and to maximize the product of the signal-to-interference-plus-noise ratios in the network. Different from prior works, in our proposed power control schemes, we consider joint pilot and data transmission optimization. Finally, we provide a numerical evaluation, where we compare our proposed power control schemes with the maximum transmit power case and the case of conventional multi-cell massive MIMO without D2D communication. Based on the provided results, we conclude that our proposed scheme increases the sum SE of multi-cell massive MIMO networks.
@article{diva2:1324206,
author = {Ghazanfari, Amin and Björnson, Emil and Larsson, Erik G},
title = {{Optimized Power Control for Massive MIMO With Underlaid D2D Communications}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {4},
pages = {2763--2778},
}
In this letter, we consider optimal hybrid beamforming design to minimize the transmission power under individual signal-to-interference-plus-noise ratio (SINR) constraints in a multiuser massive multiple-input-multiple-output (MIMO) system. This results in a challenging non-convex optimization problem. We consider two cases. In the case where the number of users is smaller than or equal to that of radio frequency (RF) chains, we propose a low-complexity method to obtain a globally optimal solution and show that it achieves the same transmission power as an optimal fully-digital beamformer. In the case where the number of users is larger than that of RF chains, we propose a low-complexity globally convergent alternating algorithm to obtain a stationary point.
@article{diva2:1324201,
author = {Zang, Guangda and Cui, Ying and Cheng, Victor and Yang, Feng and Ding, Lianghui and Liu, Hui},
title = {{Optimal Hybrid Beamforming for Multiuser Massive MIMO Systems With Individual SINR Constraints}},
journal = {IEEE Wireless Communications Letters},
year = {2019},
volume = {8},
number = {2},
pages = {532--535},
}
In modern mixed-signal systems, it is important to build the conversion components with a flat frequency response over their full Nyquist frequency band. However, with increasing circuit speed, it is becoming more difficult to achieve this, due to limitations of the analog front-end circuits. This paper considers finite-length impulse-response (FIR) filters, designed in the least-squares sense, for the bandwidth extension of analog-to-digital converters, which is one of the most important applications in frequency response equalization. The main contributions of this paper are as follows: Firstly, based on extensive simulations, filter order-estimation expressions of the least-squares designed equalizers are derived. It appears to be the first time that order-estimation expressions are presented for any least-squares designed FIR filter. These expressions accurately estimate the order required for given specifications on the targeted extended bandwidth systems. Secondly, based on the derived order-estimation expressions, systematic design procedures are presented, which contribute to reducing the design time. Finally, a relation between the dynamic-range degradation and the system parameters is also derived and verified in the paper.
@article{diva2:1318714,
author = {Wang, Yinan and Johansson, Håkan and Li, Nan and Li, Qingjiang},
title = {{Analysis, Design, and Order Estimation of Least-Squares FIR Equalizers for Bandwidth Extension of ADCs}},
journal = {Circuits, systems, and signal processing},
year = {2019},
volume = {38},
number = {5},
pages = {2165--2186},
}
Massive multiple-input–multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed form expression is then obtained for correlated Rayleigh fading, maximum-ratio combining, and the proposed large-scale fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.
@article{diva2:1313614,
author = {Van Chien, Trinh and Moll\'{e}n, Christopher and Björnson, Emil},
title = {{Large-scale-fading decoding in cellular Massive MIMO systems with spatially correlated channels}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {4},
pages = {2746--2762},
}
In this paper a built-in-self-test (BiST) aimed at the third and second intercept point (IP3/IP2) characterization of RF receiver is discussed with a focus on a stimulus generator. The generator is designed based on a specialized phase-lock loop (PLL) architecture with two voltage controlled oscillators (VCOs) operating in GHz frequency range. The objective of PLL is to keep the VCOs frequency spacing under control. According to the test requirements the phase noise and nonlinear distortion of the two-tone generator are considered as a merit for the design of VCOs and analog adder. The PLL reference spurs, critical for the IP3 measurement, are avoided by means of a frequency doubling technique. The circuit is designed in 65nm CMOS. A highly linear analog adder with OIP3amp;gt;+15dBm and ring VCOs with phase noise amp;lt; -104 dBc/Hz at 1MHz offset are used to generate the RF stimulus of total power greater than -22dBm. In simulations a performance sufficient for IP3/IP2 test of a typical RF CMOS receiver is demonstrated.
@article{diva2:1302128,
author = {Ahmad, Shakeel and Dabrowski, Jerzy},
title = {{Design of Two-Tone RF Generator for On-Chip IP3/IP2 Test}},
journal = {Journal of electronic testing},
year = {2019},
volume = {35},
number = {1},
pages = {77--85},
}
Self-sustainability of low power wireless sensor nodes is the need of the hour to realize ubiquitous wireless networks. To address this requirement we investigate the practical feasibility of sustainable green sensor network with solar-powered nodes. We propose simple yet efficient (i) analytical circuit model for solar panel assisted supercapacitor charging and (ii) statistical model for characterizing the solar intensity distribution. Combining these circuit and statistical models, we derive a novel solar charging rate distribution for the solar-powered supercapacitor. To gain analytical insights, we also propose an ideal diode based tight approximation for the practical supercapacitor charging circuit model. The accuracy of these proposed analytical models have been validated by extensive numerical simulations based on the real-world data, i.e., solar intensity profile and solar panel characteristics. The derived solar charging rate distribution is used to investigate the supported sampling rate of the node with different varying number of on-board sensors for a given energy outage probability. Results suggest that for an energy outage probability of 0.1, at New Delhi, a 40 F supercapacitor and a 3 W solar panel can support the operation of Waspmote with 6 on-board toxic gas sensors with a sampling rate of 65 samples per day. Further, we use the proposed models to estimate the practical supercapacitor and solar panel sizes required to ensure sustainability of sensor node operation at different geographical locations with varying sensing rate.
@article{diva2:1301608,
author = {De, Swades and Kaushik, K. and Mishra, Deepak},
title = {{Stochastic Solar Harvesting Characterization for Sustainable Sensor Node Operation}},
journal = {IET Wireless Sensor Systems},
year = {2019},
volume = {9},
number = {4},
pages = {208--217},
}
In this paper, we consider the full-duplex decode-and-forward wireless-powered relaying system, which employs energy harvesting protocol with power splitting. The robust joint optimum relay transmit beamformer and power splitting factor are obtained for the quality of service (QoS)-aware problem for the first time in the literature. The optimum solution is found by analyzing the Karush-Kuhn-Tucker conditions, thanks to the effective reformulation of the problem in an equivalent and simplified manner. In addition, the signal-to-interference-plus-noise ratio (SINR) maximization problem is investigated in order to find the robust optimum solution. The simulation results verify the optimality of the proposed method compared with the sub-optimum one which is presented by Zhao et al.. In the next part of this paper, the considered system is generalized by employing multiple receive antennas at the relay. Both QoS-aware and SINR maximization problems are considered. The near-optimum relay transmit and receive beamformers as well as power splitting factor are found by optimizing the variables alternately. First, transmit beamformer and power splitting factor are found optimally for a given initial receive beamformer. Then, the optimum receive beamformer is obtained. Relay with multiple-receive antennas is shown to perform better than the single receive antenna relay in terms of SINR and transmission power.
@article{diva2:1301573,
author = {Tugfe Demir, Özlem Tugfe and Tuncer, Temel Engin},
title = {{Robust Optimum and Near-Optimum Beamformers for Decode-and-Forward Full-Duplex Multi-Antenna Relay With Self-Energy Recycling}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {3},
pages = {1566--1580},
}
In this paper, we consider the downlink of a multi-cell multiple-input multiple-output system and find the jointly optimal number of base station (BS) antennas and transmission powers that minimize the power consumption while satisfying each users effective signal-to-interference-and-noise-ratio constraint and the BSs power constraints. Different from prior work, we consider a power consumption model that takes both transmitted and hardware-consumed power into account. We formulate the joint optimization problem for both single-cell and multi-cell systems. The closed-form expressions for the optimal number of BS antennas and transmission powers are derived for the single-cell case. The analysis for the multi-cell case reveals that increasing the number of BS antennas in any cell always improves the performance of the overall system in terms of both feasibility and total radiated power. A key contribution of this paper is to show that the joint optimization problem can be relaxed as a geometric programming problem that can be solved efficiently. The solution can be utilized in practice to turn on and off antennas depending on the traffic load variations. The substantial power savings are demonstrated by simulation.
@article{diva2:1301572,
author = {Senel, Kamil and Björnson, Emil and Larsson, Erik G},
title = {{Joint Transmit and Circuit Power Minimization in Massive MIMO With Downlink SINR Constraints: When to Turn on Massive MIMO?}},
journal = {IEEE Transactions on Wireless Communications},
year = {2019},
volume = {18},
number = {3},
pages = {1834--1846},
}
We investigate the effect of bursty traffic in a long term evolution (LTE) and Wi-Fi aggregation (LWA)-enabled network. The LTE base station routes packets of the same IP flow through the LIE and Wi-Fi links independently. We motivate the use of superposition coding at the LWA-mode Wi-Fi access point (AP) so that it can serve LWA users and Wi-Fi users simultaneously. A random access protocol is applied in such system, which allows the native-mode AP to access the channel with probabilities that depend on the queue size of the LWA-mode AP to avoid impeding the performance of the LWA-enabled network. We analyze the throughput of the native Wi-Fi network and the delay experienced by the LWA users, accounting for the native-mode AP access probability, the traffic flow splitting between LTE and Wi-Fi, and the operating mode of the LWA user with both LIE and Wi-Fi interfaces. Our results show some fundamental tradeoffs in the throughput and delay behavior of LWA-enabled networks, which provide meaningful insight into the operation of such aggregated systems.
@article{diva2:1301285,
author = {Chen, Bolin and Pappas, Nikolaos and Chen, Zheng and Yuan, Di and Zhang, Jie},
title = {{Throughput and Delay Analysis of LWA With Bursty Traffic and Randomized Flow Splitting}},
journal = {IEEE Access},
year = {2019},
volume = {7},
pages = {24667--24678},
}
This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with a focus on massive multiple input multiple output (MIMO). This distortion is correlated across the antennas but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of distortion correlation are first uncovered. Then, we separately analyze the distortion correlation caused by third-order non-linearities and by quantization. Finally, we study the SE numerically and show that the distortion correlation can be safely neglected in massive MIMO when there are sufficiently many users. Under independent identically distributed Rayleigh fading and equal signal-to-noise ratios (SNRs), this occurs for more than five transmitting users. Other channel models and SNR variations have only minor impact on the accuracy. We also demonstrate the importance of taking the distortion characteristics into account in the receive combining.
@article{diva2:1297514,
author = {Björnson, Emil and Sanguinetti, Luca and Hoydis, Jakob},
title = {{Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {2},
pages = {1085--1098},
}
Backscatter communication (BSC) technology can enable ubiquitous deployment of low-cost sustainable wireless devices. In this paper, we investigate the efficacy of a full-duplex multiple-input-multiple-output reader for enhancing the limited communication range of monostatic BSC systems. As this performance is strongly influenced by the channel estimation (CE) quality, we first derive a novel least-squares estimator for the forward and backward links between the reader and the tag, assuming that reciprocity holds and K orthogonal pilots are transmitted from the first K antennas of an N antenna reader. We also obtain the corresponding linear minimum-mean square-error estimate for the backscattered channel. After defining the transceiver design at the reader using these estimates, we jointly optimize the number of orthogonal pilots and energy allocation for the CE and information decoding phases to maximize the average backscattered signal-to-noise ratio (SNR) for efficiently decoding the tags messages. The unimodality of this SNR in optimization variables along with a tight analytical approximation for the jointly global optimal design is also discoursed. Lastly, the selected numerical results validate the proposed analysis, present key insights into the optimal resource utilization at reader, and quantify the achievable gains over the benchmark schemes.
@article{diva2:1293671,
author = {Mishra, Deepak and Larsson, Erik G},
title = {{Optimal Channel Estimation for Reciprocity-Based Backscattering With a Full-Duplex MIMO Reader}},
journal = {IEEE Transactions on Signal Processing},
year = {2019},
volume = {67},
number = {6},
pages = {1662--1677},
}
The capacity of the MIMO channel taking into account both a limitation on total consumed power, and per-antenna radiated power constraints is considered. The total consumed power takes into account the traditionally used sum radiated power, and also the power dissipation in the amplifiers. For a fixed channel with full CSI at both the transmitter and the receiver, maximization of the mutual information is formulated as an optimization problem. Lower and upper bounds on the capacity are provided by numerical algorithms based on partitioning of the feasible region. Both bounds are shown to converge and give the exact capacity when number of regions increases. The bounds are also used to construct a monotonic optimization algorithm based on the branch-and-bound approach. An efficient suboptimal algorithm based on successive convex approximation performing close to the capacity is also presented. Numerical results show that the performance of the solution obtained from the suboptimal algorithm is close to that of the global optimal solution. Simulation results also show that in the low SNR regime, antenna selection provides performance that is close to the optimal scheme while at high SNR, uniform power allocation performs close to the optimal scheme.
@article{diva2:1292627,
author = {Cheng, Victor and Persson, Daniel and Larsson, Erik G},
title = {{Optimal MIMO Precoding Under a Constraint on the Amplifier Power Consumption}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {1},
pages = {218--229},
}
We consider transmission of system information in a cell-free massive MIMO system, when the transmitting access points do not have any channel state information and the receiving terminal has to estimate the channel based on downlink pilots. We analyze the system performance in terms of outage rate and coverage probability and use space-time block codes to increase performance. We propose a heuristic method for pilot/data power optimization that can be applied without any channel state information at the access points. We also analyze the problem of grouping the access points, which is needed when the single-antenna access points jointly transmit a space-time block code.
@article{diva2:1292626,
author = {Karlsson, Marcus and Björnson, Emil and Larsson, Erik G},
title = {{Techniques for System Information Broadcast in Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Communications},
year = {2019},
volume = {67},
number = {1},
pages = {244--257},
}
Joint resource allocation involving optimization of subcarrier allocation, subcarrier pairing (SCP), and power allocation in a cooperative secure orthogonal frequency division multiple access (OFDMA) communication system with untrusted users is considered. Both amplify and forward (AF), and decode and forward (DF) modes of operations are considered with individual power budget constraints for source and relay. After finding optimal subcarrier allocation for an AF relayed system, we prove the joint power allocation as a generalized convex problem, and solve it optimally. Compared to the conventional channel gain matching view, the optimal SCP is emphasized as a novel concept of channel gain tailoring. We prove that the optimal SCP pairs subcarriers such that the variance among the effective channel gains is minimized. For a DF relayed system, we show that depending on the power budgets of source and relay, SCP can either be in a subordinate role where it improves the energy efficiency, or in a main role where it improves the spectral efficiency of the system. In an AF relayed system we confirm that SCP plays a crucial role, and improves the spectral efficiency of the system. The channel gain tailoring property of SCP, various roles of SCP in improving the spectral and energy efficiency of a cooperative communication system are validated with the help of simulation results. (C) 2018 Elsevier B.V. All rights reserved.
@article{diva2:1290511,
author = {Saini, Ravikant and Mishra, Deepak and De, Swades},
title = {{Subcarrier pairing as channel gain tailoring: Joint resource allocation for relay-assisted secure OFDMA with untrusted users}},
journal = {Physical Communication},
year = {2019},
volume = {32},
pages = {217--230},
}
We analyze the effect of channel aging on the achievable rate of time division duplexed massive multiple input multiple output systems serving a number of users under aging channels, using nonorthogonal multiple access (NOMA) and orthogonal multiple access (OMA). Using the recently proposed shared uplink pilot based channel estimation for NOMA, we derive bounds on the channel estimation error variance for the two schemes. We then derive the achievable spectral efficiencies of the two schemes. Using numerical results, we show that, in slowly varying channels, using NOMA with shared pilots is preferable over OMA, while the reverse is true under fast varying channels.
@article{diva2:1285537,
author = {Chopra, Ribhu and Murthy, Chandra R. and Suraweera, Himal A. and Larsson, Erik G},
title = {{Analysis of Nonorthogonal Training in Massive MIMO Under Channel Aging With SIC Receivers}},
journal = {IEEE Signal Processing Letters},
year = {2019},
volume = {26},
number = {2},
pages = {282--286},
}
Hybrid energy beamforming (HEB) can reduce the hardware cost, energy consumption, and space constraints associated with massive antenna array transmitter (TX). With a single radio frequency chain having N digitally controlled phase shifter pairs, one per antenna element, theoretically achieving the same performance as a fully digital beamforming architecture with N RF chains, this letter investigates the practical efficacy of the HEB. First adopting the proposed analog phase shifter impairments model and exploiting the channel reciprocity along with the available statistical information, we present a novel approach to obtain an accurate minimum mean-square error estimate for the wireless channel between TX and energy receiver (RX). Then, tight analytical approximation for the global optimal time allocation between uplink channel estimation and downlink energy transfer operations is derived to maximize the mean net harvested energy at RX. Numerical results, validating the analysis and presenting key design insights, show that with an average improvement of 58% over the benchmark scheme, the optimized HEB can help in practically realizing the fully digital array gains.
@article{diva2:1274650,
author = {Mishra, Deepak and Johansson, Håkan},
title = {{Efficacy of Hybrid Energy Beamforming With Phase Shifter Impairments and Channel Estimation Errors}},
journal = {IEEE Signal Processing Letters},
year = {2019},
volume = {26},
number = {1},
pages = {99--103},
}
Deep learning (DL), despite its enormous success in many computer vision and language processing applications, is exceedingly vulnerable to adversarial attacks. We consider the use of DL for radio signal (modulation) classification tasks, and present practical methods for the crafting of white-box and universal black-box adversarial attacks in that application. We show that these attacks can considerably reduce the classification performance, with extremely small perturbations of the input. In particular, these attacks are significantly more powerful than classical jamming attacks, which raises significant security and robustness concerns in the use of DL-based algorithms for the wireless physical layer.
@article{diva2:1245700,
author = {Sadeghi, Meysam and Larsson, Erik G.},
title = {{Adversarial Attacks on Deep-Learning Based Radio Signal Classification}},
journal = {IEEE Wireless Communications Letters},
year = {2019},
volume = {8},
number = {1},
pages = {213--216},
}
This work aims to design the uplink (UL) of a cellular network for maximal energy efficiency (EE). Each base station (BS) is randomly deployed within a given area and is equipped with M antennas to serve K user equipments (UEs). A multislope (distance-dependent) path loss model is considered and linear processing is used, under the assumption that channel state information is acquired by using pilot sequences (reused across the network). Within this setting, a lower bound on the UL spectral efficiency and a realistic circuit power consumption model are used to evaluate the network EE. Numerical results are first used to compute the optimal BS density and pilot reuse factor for a Massive MIMO network with three different detection schemes, namely, maximum ratio combining, zero-forcing (ZF) and multicell minimum mean-squared error. The numerical analysis shows that the EE is a unimodal function of BS density and achieves its maximum for a relatively small density of BS, irrespective of the employed detection scheme. This is in contrast to the single-slope (distance-independent) path loss model, for which the EE is a monotonic non-decreasing function of BS density. Then, we concentrate on ZF and use stochastic geometry to compute a new lower bound on the spectral efficiency, which is then used to optimize, for a given BS density, the pilot reuse factor, number of BS antennas and UEs. Closed-form expressions are computed from which valuable insights into the interplay between optimization variables, hardware characteristics, and propagation environment are obtained.
@article{diva2:1367932,
author = {Pizzo, Andrea and Verenzuela, Daniel and Sanguinetti, Luca and Björnson, Emil},
title = {{Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss}},
journal = {IEEE Transactions on Green Communications and Networking},
year = {2018},
volume = {2},
number = {3},
pages = {735--750},
}
In this paper, we investigate the joint optimization of base station (BS) location, its density, and transmit power allocation to minimize the overall network operational cost required to meet an underlying coverage constraint at each user equipment (UE), which is randomly deployed following the binomial point process (BPP). As this joint optimization problem is nonconvex and combinatorial in nature, we propose a non-trivial solution methodology that effectively decouples it into three individual optimization problems. Firstly, by using the distance distribution of the farthest UE from the BS, we present novel insights on optimal BS location in an optimal sectoring type for a given number of BSs. After that we provide a tight approximation for the optimal transmit power allocation to each BS. Lastly, using the latter two results, the optimal number of BSs that minimize the operational cost is obtained. Also, we have investigated both circular and square field deployments. Numerical results validate the analysis and provide practical insights on optimal BS deployment. We observe that the proposed joint optimization framework, that solves the coverage probability versus operational cost tradeoff, can yield a significant reduction of about 65% in the operational cost as compared to the benchmark fixed allocation scheme.
@article{diva2:1299024,
author = {Prasad, Ganesh and Mishra, Deepak and Hossain, Ashraf},
title = {{Joint Optimization Framework for Operational Cost Minimization in Green Coverage-Constrained Wireless Networks}},
journal = {IEEE Transactions on Green Communications and Networking},
year = {2018},
volume = {2},
number = {3},
pages = {693--706},
}
We develop refinements of the Levenshtein bound in q-ary Hamming spaces by taking into account the discrete nature of the distances versus the continuous behavior of certain parameters used by Levenshtein. We investigate the first relevant cases and present new bounds. In particular, we derive generalizations and q-ary analogs of the MacEliece bound. Furthermore, we provide evidence that our approach is as good as the complete linear programming and discuss how faster are our calculations. Finally, we present a table with parameters of codes which, if exist, would attain our bounds.
@article{diva2:1283681,
author = {Boyvalenkov, P. and Danev, Danyo and Stoyanova, M.},
title = {{Refinements of Levenshtein Bounds in q-ary Hamming Spaces}},
journal = {Problems of Information Transmission},
year = {2018},
volume = {54},
number = {4},
pages = {329--342},
}
In massive multiple-input-multiple-output base stations, power consumption and cost of the low-noise amplifiers (LNAs) can be substantial because of the many antennas. We investigate the feasibility of inexpensive, power efficient LNAs, which inherently are less linear. A polynomial model is used to characterize the nonlinear LNAs and to derive the second-order statistics and spatial correlation of the distortion. We show that, with spatial matched filtering (maximum-ratio combining) at the receiver, some distortion terms combine coherently, and that the signal-to-interference-and-noise ratio of the symbol estimates therefore is limited by the linearity of the LNAs. Furthermore, it is studied how the power from a blocker in the adjacent frequency band leaks into the main band and creates distortion. The distortion term that scales cubically with the power received from the blocker has a spatial correlation that can be filtered out by spatial processing and only the coherent term that scales quadratically with the power remains. When the blocker is in free-space line-of-sight and the LNAs are identical, this quadratic term has the same spatial direction as the desired signal, and hence cannot be removed by linear receiver processing.
@article{diva2:1276231,
author = {Moll\'{e}n, Christopher and Gustavsson, Ulf and Eriksson, Thomas and Larsson, Erik G},
title = {{Impact of Spatial Filtering on Distortion From Low-Noise Amplifiers in Massive MIMO Base Stations}},
journal = {IEEE Transactions on Communications},
year = {2018},
volume = {66},
number = {12},
pages = {6050--6067},
}
A key challenge of massive MTC (mMTC), is the joint detection of device activity and decoding of data. The sparse characteristics of mMTC makes compressed sensing (CS) approaches a promising solution to the device detection problem. However, utilizing CS-based approaches for device detection along with channel estimation, and using the acquired estimates for coherent data transmission is suboptimal, especially when the goal is to convey only a few bits of data. First, we focus on the coherent transmission and demonstrate that it is possible to obtain more accurate channel state information by combining conventional estimators with CS-based techniques. Moreover, we illustrate that even simple power control techniques can enhance the device detection performance in mMTC setups. Second, we devise a new non-coherent transmission scheme for mMTC and specifically for grant-free random access. We design an algorithm that jointly detects device activity along with embedded information bits. The approach leverages elements from the approximate message passing (AMP) algorithm, and exploits the structured sparsity introduced by the non-coherent transmission scheme. Our analysis reveals that the proposed approach has superior performance compared with application of the original AMP approach.
@article{diva2:1276230,
author = {Senel, Kamil and Larsson, Erik G},
title = {{Grant-Free Massive MTC-Enabled Massive MIMO: A Compressive Sensing Approach}},
journal = {IEEE Transactions on Communications},
year = {2018},
volume = {66},
number = {12},
pages = {6164--6175},
}
The purpose of this paper is to bestow the reader with a timely study of UAV cellular communications, bridging the gap between the 3GPP standardization status quo and the more forward-looking research. Special emphasis is placed on the downlink command and control (Camp;C) channel to aerial users, whose reliability is deemed of paramount technological importance for the commercial success of UAV cellular communications. Through a realistic side-by-side comparison of two network deployments - a present-day cellular infrastructure versus a next-generation massive MIMO system - a plurality of key facts are cast light upon, with the three main ones summarized as follows: 1) UAV cell selection is essentially driven by the secondary lobes of a base stations radiation pattern, causing UAVs to associate to far-flung cells; 2) over a 10 MHz bandwidth, and for UAV heights of up to 300 m, massive MIMO networks can support 100 kbps Camp;C channels in 74% of the cases when the uplink pilots for channel estimation are reused among base station sites, and in 96% of the cases without pilot reuse across the network; and 3) supporting UAV Camp;C channels can considerably affect the performance of ground users on account of severe pilot contamination, unless suitable power control policies are in place.
@article{diva2:1273174,
author = {Geraci, Giovanni and Garcia-Rodriguez, Adrian and Giordano, Lorenzo Galati and Lopez-Perez, David and Björnson, Emil},
title = {{Understanding UAV Cellular Communications: From Existing Networks to Massive MIMO}},
journal = {IEEE Access},
year = {2018},
volume = {6},
pages = {67853--67865},
}
Cell-free (CF) massive multiple-input multiple-output (MIMO) is an alternative topology for future wireless networks, where a large number of single-antenna access points (APs) are distributed over the coverage area. There are no cells but all users are jointly served by the APs using network MIMO methods. Prior works have claimed that the CF massive MIMO inherits the basic properties of cellular massive MIMO, namely, channel hardening and favorable propagation. In this paper, we evaluate if one can rely on these properties when having a realistic stochastic AP deployment. Our results show that channel hardening only appears in special cases, for example, when the pathloss exponent is small. However, by using 5-10 antennas per AP, instead of one, we can substantially improve the hardening. Only spatially well-separated users will exhibit favorable propagation, but when adding more antennas and/or reducing the pathloss exponent, it becomes more likely for favorable propagation to occur. The conclusion is that we cannot rely on the channel hardening and the favorable propagation when analyzing and designing the CF massive MIMO networks, but we need to use achievable rate expressions and resource allocation schemes that work well also in the absence of these properties. Some options are reviewed in this paper.
@article{diva2:1267275,
author = {Chen, Zheng and Björnson, Emil},
title = {{Channel Hardening and Favorable Propagation in Cell-Free Massive MIMO With Stochastic Geometry}},
journal = {IEEE Transactions on Communications},
year = {2018},
volume = {66},
number = {11},
pages = {5205--5219},
}
In conventional cooperative non-orthogonal multiple access (NOMA) networks, spectral efficiency loss occurs due to a half-duplex constraint. To address this issue, we propose an incremental cooperative NOMA (ICN) protocol for a two-user downlink network. In particular, this protocol allows the source to adaptively switch between a direct NOMA transmission mode and a cooperative NOMA transmission mode according to a 1-bit feedback from the far user. We analytically prove that the proposed ICN protocol outperforms the conventional cooperative NOMA protocol. In addition, an optimal power allocation strategy at the source is studied to minimize the asymptotic system outage probability. Finally, numerical results validate our theoretical analysis. present insights, and quantify the enhancement achieved over the benchmark scheme.
@article{diva2:1267276,
author = {Li, Guoxin and Mishra, Deepak and Jiang, Hai},
title = {{Cooperative NOMA With Incremental Relaying: Performance Analysis and Optimization}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2018},
volume = {67},
number = {11},
pages = {11291--11295},
}
Next-generation wireless networks aim at providing substantial improvements in spectral efficiency (SE) and energy efficiency (EE). Massive MIMO has been proved to be a viable technology to achieve these goals by spatially multiplexing several users using many base station (BS) antennas. A potential limitation of massive MIMO in multicell systems is pilot contamination, which arises in the channel estimation process from the interference caused by reusing pilots in neighboring cells. A standard method to reduce pilot contamination, known as regular pilot (RP), is to adjust the length of pilot sequences while transmitting data and pilot symbols disjointly. An alternative method, called superimposed pilot (SP), sends a superposition of pilot and data symbols. This allows use of longer pilots which, in turn, reduces pilot contamination. We consider the uplink of a multicell massive MIMO network, with i.i.d. Rayleigh fading channels, using maximum ratio combining and compare RP and SP in terms of SE and EE. To this end, we derive rigorous closed-form achievable rates with SP under a practical random BS deployment. We prove that the reduction of pilot contamination with SP is outweighed by the additional coherent and non-coherent interference. Numerical results show that when both methods are optimized, RP achieves comparable SE and EE to SP in practical scenarios.
@article{diva2:1267274,
author = {Verenzuela, Daniel and Björnson, Emil and Sanguinetti, Luca},
title = {{Spectral and Energy Efficiency of Superimposed Pilots in Uplink Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {11},
pages = {7099--7115},
}
In this paper, we propose a decentralized access control scheme for interference management in device-to-device (D2D) underlaid cellular networks. Our method combines signal-to-interference ratio (SIR)-aware link activation with cellular guard zones in a system, where D2D links opportunistically access the licensed cellular spectrum when the activation conditions are satisfied. Analytical expressions for the success/coverage probability of both cellular and D2D links are derived. We characterize the impact of the guard zone radius and the SIR threshold on the D2D potential throughput and cellular coverage. A tractable approach is proposed to find the SIR threshold and guard zone radius that maximize the potential throughput of the D2D communication while ensuring sufficient coverage probability for the cellular uplink users. Simulations validate the accuracy of our analytical results and show the performance gain of the proposed scheme compared to prior state-of-the-art solutions.
@article{diva2:1262087,
author = {Chen, Zheng and Kountouris, Marios},
title = {{Decentralized Opportunistic Access for D2D Underlaid Cellular Networks}},
journal = {IEEE Transactions on Communications},
year = {2018},
volume = {66},
number = {10},
pages = {4842--4853},
}
As an interesting network architecture for future wireless communication systems, cell-free (CF) massive multiple-input multiple-output (MIMO) distributes an excess number of access points (APs) with single or multiple antennas to cooperatively communicate with several user equipments (UEs). To realize CF massive MIMO in production, hardware impairments become a crucial problem since cheaper and low-quality antennas are needed to ensure economic and energy feasibility. In this paper, we propose a framework for performance analysis in the CF massive MIMO with classical hardware distortion models. For both uplink and downlink, closed-form spectral and energy efficiency expressions are derived, respectively. Based on these results, we provide significant insights into the practical impact of hardware impairments on CF massive MIMO. For example, the impact of hardware distortion at the APs asymptotically vanishes. Furthermore, in order to ensure uniformly good service to the users, we propose a max-min power control algorithm to maximize the minimum UE rate. Via analytical and numerical results, we prove that CF massive MIMO can tolerate hardware impairments without performance reduction.
@article{diva2:1262063,
author = {Zhang, Jiayi and Wei, Yinghua and Björnson, Emil and Han, Yu and Jin, Shi},
title = {{Performance Analysis and Power Control of Cell-Free Massive MIMO Systems with Hardware Impairments}},
journal = {IEEE Access},
year = {2018},
volume = {6},
pages = {55302--55314},
}
The distortion from massive multiple-input multiple-output base stations with nonlinear amplifiers is studied and its radiation pattern is derived. The distortion is analyzed both in-band and out-of-band. By using an orthogonal Hermite representation of the amplified signal, the spatial cross-correlation matrix of the nonlinear distortion is obtained. It shows that, if the input signal to the amplifiers has a dominant beam, the distortion is beamformed in the same way as that beam. When there are multiple beams without any one being dominant, it is shown that the distortion is practically isotropic. The derived theory is useful to predict how the nonlinear distortion will behave, to analyze the out-of-band radiation, to do reciprocity calibration, and to schedule users in the frequency plane to minimize the effect of in-band distortion.
@article{diva2:1259613,
author = {Moll\'{e}n, Christopher and Gustavsson, Ulf and Eriksson, Thomas and Larsson, Erik G},
title = {{Spatial Characteristics of Distortion Radiated From Antenna Arrays With Transceiver Nonlinearities}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {10},
pages = {6663--6679},
}
This letter investigates the achievable rate region in massive multiple-input-multiple-output systems with two users, with a focus on the i.i.d. Rayleigh fading and line-of-sight (LoS) scenarios. If the rate region is convex, spatial multiplexing is preferable to orthogonal scheduling, while the opposite is true for non-convex regions. We prove that the uplink and downlink rate regions with i.i.d. Rayleigh fading are convex, while the convexity in LoS depends on parameters such as angular user separation, number of antennas, and signal-to-noise ratio (SNR).
@article{diva2:1259612,
author = {Chen, Zheng and Björnson, Emil and Larsson, Erik G},
title = {{When Is the Achievable Rate Region Convex in Two-User Massive MIMO Systems?}},
journal = {IEEE Wireless Communications Letters},
year = {2018},
volume = {7},
number = {5},
pages = {796--799},
}
One of the main goals of the future wireless networks is improving the users quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells antennas in the network leads to a higher user satisfaction.
@article{diva2:1256328,
author = {Abarghouyi, Hadis and Razavizadeh, S. Mohammad and Björnson, Emil},
title = {{QoE-Aware Beamforming Design for Massive MIMO Heterogeneous Networks}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2018},
volume = {67},
number = {9},
pages = {8315--8323},
}
In this paper, we analyze a shared access network with a fixed primary node and randomly distributed secondary nodes whose spatial distribution follows a poisson point process. The secondary nodes use a random access protocol allowing them to access the channel with probabilities that depend on the queue size of the primary node. Assuming a system with multipacket reception receivers, having bursty packet arrivals at the primary and saturated traffic at the secondary nodes, our protocol can be tuned to alleviate congestion at the primary. We analyze the throughput of the secondary network and the primary average delay, as well as the impact of the secondary node access probability and transmit power. We formulate an optimization problem to maximize the throughput of the secondary network under delay constraints for the primary node; in the case of no congestion control, the optimal access probability can be provided in closed form. Our numerical results illustrate the effect of network operating parameters on the performance of the proposed priority-based shared access protocol.
@article{diva2:1254019,
author = {Chen, Zheng and Pappas, Nikolaos and Kountouris, Marios and Angelakis, Vangelis},
title = {{Throughput With Delay Constraints in a Shared Access Network With Priorities}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {9},
pages = {5885--5899},
}
If we assume line-of-sight propagation and perfect channel state information at the base station - consistent with slow moving terminals - then a direct performance comparison between Massive MIMO at PCS and mmWave frequency bands is straightforward and highly illuminating. Line-of-sight propagation is considered favorable for mmWave because of minimal attenuation and its facilitation of hybrid beamforming to reduce the required number of active transceivers. We quantify the number of mmWave (60 GHz) service antennas that are needed to duplicate the performance of a specified number of PCS (1.9 GHz) service antennas. As a baseline we consider a modest PCS deployment of 128 antennas serving 18 terminals. At one extreme, we find that, to achieve the same per-terminal maxmin 95 percent-likely downlink throughput in a single-cell system, 20,000 mmWave antennas are needed. To match the total antenna area of the PCS array would require 128,000 half-wavelength mmWave antennas, but a much reduced number is adequate because the large number of antennas also confers greater channel orthogonality. At the other extreme, in a highly interference-limited multi-cell environment, only 215 mmWave antennas are needed; in this case, increasing the transmitted power yields little improvement in service quality.
@article{diva2:1253328,
author = {Larsson, Erik G and Marzetta, Thomas L. and Ngo, Hien Quoc and Yang, Hong},
title = {{Antenna Count for Massive MIMO: 1.9 GHz vs. 60 GHz}},
journal = {IEEE Communications Magazine},
year = {2018},
volume = {56},
number = {9},
pages = {132--137},
}
The next wave of wireless technologies will proliferate in connecting sensors, machines, and robots for myriad new applications, thereby creating the fabric for the Internet of Things (IoT). A generic scenario for IoT connectivity involves a massive number of machine-type connections, but in a typical application, only a small (unknown) subset of devices are active at any given instant; therefore, one of the key challenges of providing massive IoT connectivity is to detect the active devices first and then decode their data with low latency. This article advocates the usage of grant-free, rather than grant-based random access schemes to overcome the challenge of massive IoT access. Several key signal processing techniques that promote the performance of the grant-free strategies are outlined, with a primary focus on advanced compressed sensing techniques and their applications for the efficient detection of active devices. We argue that massive multiple-input, multiple-output (MIMO) is especially well suited for massive IoT connectivity because the device detection error can be driven to zero asymptotically in the limit as the number of antennas at the base station (BS) goes to infinity by using the multiple-measurement vector (MMV) compressed sensing techniques. This article also provides a perspective on several related important techniques for massive access, such as embedding short messages onto the device-activity detection process and the coded random access.
@article{diva2:1250695,
author = {Liu, Liang and Larsson, Erik G and Yu, Wei and Popovski, Petar and Stefanovic, Cedomir and de Carvalho, Elisabeth},
title = {{Sparse Signal Processing for Grant-Free Massive Connectivity A future paradigm for random access protocols in the Internet of Things}},
journal = {IEEE signal processing magazine (Print)},
year = {2018},
volume = {35},
number = {5},
pages = {88--99},
}
Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: 1) transmitting distinct data streams to groups of users and 2) applying precoding on a symbol-persymbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: 1) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding and 2) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area.(1)
@article{diva2:1250584,
author = {Alodeh, Maha and Spano, Danilo and Kalantari, Ashkan and Tsinos, Christos G. and Christopoulos, Dimitrios and Chatzinotas, Symeon and Ottersten, Bjorn},
title = {{Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges}},
journal = {IEEE Communications Surveys and Tutorials},
year = {2018},
volume = {20},
number = {3},
pages = {1733--1757},
}
Non-linearities in radio-frequency transceiver hardware, particularly in power amplifiers, cause distortion in-band and out-of-band. Contrary to claims made in recent literature, in a multiple-antenna system this distortion is correlated across the antennas in the array. A significant implication of this fact is that out-of-band emissions caused by non-linearities are beamformed, in some cases into the same direction as the useful signal.
@article{diva2:1248034,
author = {Larsson, Erik G. and Van der Perre, Liesbet},
title = {{Out-of-Band Radiation From Antenna Arrays Clarified}},
journal = {IEEE Wireless Communications Letters},
year = {2018},
volume = {7},
number = {4},
pages = {610--613},
}
Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, and multiplexing of 8 terminals). Coarse and even errorprone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.
@article{diva2:1245923,
author = {Van der Perre, Liesbet and Liu, Liang and Larsson, Erik G},
title = {{Efficient DSP and Circuit Architectures for Massive MIMO: State of the Art and Future Directions}},
journal = {IEEE Transactions on Signal Processing},
year = {2018},
volume = {66},
number = {18},
pages = {4717--4736},
}
This letter minimizes outage probability in a single decode-and-forward relay-assisted underwater acoustic network without direct source-to-destination link availability. Specifically, a joint global-optimal design for relay positioning and allocating power to source and relay is proposed. For analytical insights, a novel low-complexity tight approximation method is also presented. Selected numerical results validate the analysis and quantify the comparative gains achieved using optimal power allocation and relay placement strategies.
@article{diva2:1245897,
author = {Prasad, Ganesh and Mishra, Deepak and Hossain, Ashraf},
title = {{Joint Optimal Design for Outage Minimization in DF Relay-Assisted Underwater Acoustic Networks}},
journal = {IEEE Communications Letters},
year = {2018},
volume = {22},
number = {8},
pages = {1724--1727},
}
Self-sustainability of wireless nodes in Internet-of-Things applications can be realized with the help of controlled radio frequency energy transfer (RF-ET). However, due to significant energy loss in wireless dissipation, there is a need for novel schemes to improve the end-to-end RF-ET efficiency. In this paper, first we propose a new channel model for accurately characterizing the harvested dc power at the receiver. This model incorporates the effects of nonline of sight (NLOS) component along with the other factors, such as radiation pattern of transmit and receive antennas, losses associated with different polarization of transmitting field, and efficiency of power harvester circuit. Accuracy of the model is verified via experimental studies in an anechoic chamber (a controlled environment). Supported by experiments in controlled environment, we also formulate an optimization problem by accounting for the effect of NLOS component to maximize the RF-ET efficiency, which cannot be captured by the Friis formula. To solve this nonconvex problem, we present a computationally efficient golden section-based iterative algorithm. Finally, through extensive RF-ET measurements in different practical field environments we obtain the statistical parameters for Rician fading as well as path loss factor associated with shadow fading model, which also asserts the fact that Rayleigh fading is not well suited for RF-ET due to presence of a strong line of sight component.
@article{diva2:1245888,
author = {Kumar, Sidharth and De, Swades and Mishra, Deepak},
title = {{RF Energy Transfer Channel Models for Sustainable IoT}},
journal = {IEEE Internet of Things Journal},
year = {2018},
volume = {5},
number = {4},
pages = {2817--2828},
}
Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data rate demands of low power network devices. In this paper, we consider a multiple input single output (MISO) multicasting system comprising of a multiantenna transmitter (TX) simultaneously transferring information and power to data hungry IoT nodes. Each IoT device is assumed to be equipped with power splitting (PS) hardware that enables energy harvesting (EH) and imposes an individual quality of service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO simultaneous wireless information and power transfer multicasting system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and PS ratios are also presented. Representative numerical results including comparisons with benchmark designs corroborate the utility of proposed framework and provide useful insights on the interplay of key system parameters.
@article{diva2:1245887,
author = {Mishra, Deepak and Alexandropoulos, George C. and De, Swades},
title = {{Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting}},
journal = {IEEE Internet of Things Journal},
year = {2018},
volume = {5},
number = {4},
pages = {2856--2867},
}
We study the joint unicast and multi-group multicast transmission in massive multiple-input-multiple-output (MIMO) systems. We consider a system model that accounts for channel estimation and pilot contamination, and derive achievable spectral efficiencies (SEs) for unicast and multicast user terminals (UTs), under maximum ratio transmission and zero-forcing precoding. For unicast transmission, our objective is to maximize the weighted sum SE of the unicast UTs, and for the multicast transmission, our objective is to maximize the minimum SE of the multicast UTs. These two objectives are coupled in a conflicting manner, due to their shared power resource. Therefore, we formulate a multiobjective optimization problem (MOOP) for the two conflicting objectives. We derive the Pareto boundary of the MOOP analytically. As each Pareto optimal point describes a particular efficient trade-off between the two objectives of the system, we determine the values of the system parameters (uplink training powers, downlink transmission powers, etc.) to achieve any desired Pareto optimal point. Moreover, we prove that the Pareto region is convex, hence the system should serve the unicast and multicast UTs at the same time-frequency resource. Finally, we validate our results using numerical simulations.
@article{diva2:1245677,
author = {Sadeghi, Meysam and Björnson, Emil and Larsson, Erik G. and Yuen, Chau and Marzetta, Thomas L.},
title = {{Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {10},
pages = {6375--6388},
}
We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.
@article{diva2:1233125,
author = {Ngo, Hien Quoc and Tran, Le-Nam and Duong, Trung Q. and Matthaiou, Michail and Larsson, Erik G.},
title = {{On the Total Energy Efficiency of Cell-Free Massive MIMO}},
journal = {IEEE Transactions on Green Communications and Networking},
year = {2018},
volume = {2},
number = {1},
pages = {25--39},
}
This paper analyzes the performance of linearly precoded time division duplex based multi-user massive MIMO downlink system under joint impacts of channel non-reciprocity (NRC) and imperfect channel state information. We consider a generic and realistic NRC model that accounts for transceiver frequency-response as well as mutual coupling mismatches at both user equipment (UE) and base station (BS) sides. The analysis covers two most prominent forms of linear precoding schemes, namely, zero-forcing (ZF) and maximum-ratio transmission (MRT), and assumes that only the statistical properties of the beamformed channel are used at the UE side to decode the received signal. Under the approximation of i.i.d. Gaussian channels, closed-form analytical expressions are derived for the effective signal to interference and noise ratios (SINRs) and the corresponding capacity lower bounds. The expressions show that, in moderate to high SNR, the additional interference caused by imperfect NRC calibration can degrade the performance of both precoders significantly. Moreover, ZF is shown to be more sensitive to NRC than MRT. Numerical evaluations with practical NRC levels indicate that this performance loss in the spectral efficiency can be as high as 42% for ZF, whereas it is typically less than 13% for MRT. It is also shown that due to the NRC, the asymptotic large-antenna performance of both precoders saturate to an identical finite level. The derived analytical expressions provide useful tools and valuable technical insight, e.g., into calculating the NRC calibration requirements in BSs and UEs for any given specific performance targets in terms of effective SINR or the system capacity bound.
@article{diva2:1231042,
author = {Raeesi, Orod and Gokceoglu, Ahmet and Zou, Yaning and Björnson, Emil and Valkama, Mikko},
title = {{Performance Analysis of Multi-User Massive MIMO Downlink Under Channel Non-Reciprocity and Imperfect CSI}},
journal = {IEEE Transactions on Communications},
year = {2018},
volume = {66},
number = {6},
pages = {2456--2471},
}
This paper considers a two-way half-duplex decode-and-forward relaying system, where multiple pairs of single-antenna users exchange information via a multiple-antenna relay. Assuming that the channel knowledge is nonideal and the relay employs maximum ratio processing, we derive a large-scale approximation of the sum spectral efficiency (SE) that is tight when the number of relay antennas M becomes very large. Furthermore, we study how the transmit power scales with M to maintain a desired SE. In particular, three special power-scaling cases are discussed and the corresponding asymptotic SE is deduced with clear insights. Our elegant power-scaling laws reveal a tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, we formulate a power allocation problem in terms of maximizing the sum SE and obtain a local optimum by solving a sequence of geometric programming problems.
@article{diva2:1211307,
author = {Kong, Chuili and Zhong, Caijun and Matthaiou, Michail and Björnson, Emil and Zhang, Zhaoyang},
title = {{Multipair Two-Way Half-Duplex DF Relaying With Massive Arrays and Imperfect CSI}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {5},
pages = {3269--3283},
}
Massive MIMO (MM) is one of the leading technologies that can cater for very high capacity demand. However, energy consumption of MM systems needs to be load adaptive in order to cope with the significant temporal load variations (TLV) over a day. In this paper, we propose a game-theoretic model for studying load adaptive multicell massive MIMO system where each base station (BS) adapts the number of antennas to the TLV in order to maximize the downlink energy efficiency (EE). The utility function considered here is defined as the number of bits transferred per Joule of energy. In order to incorporate the TLV, the load at each BS is modeled as an M/G/m/m state dependent queue under the assumption that the network is dimensioned to serve a maximum number of users at the peak load. The EE maximization problem is formulated in a game theoretic framework where the number of antennas to be used by a BS is determined through the best response iteration. This load adaptive system achieves around 24% higher EE and saves around 40% energy compared to a baseline system where the BSs always run with the fixed number of antennas that is most energy efficient at the peak load and that can be switched OFF when there is no traffic.
@article{diva2:1206536,
author = {Hossain, M. M. Aftab and Cavdar, Cicek and Björnson, Emil and Jantti, Riku},
title = {{Energy Saving Game for Massive MIMO: Coping With Daily Load Variation}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2018},
volume = {67},
number = {3},
pages = {2301--2313},
}
The OOB radiation from large arrays with nonlinear hardware has a different radiation pattern than the beamformed in-band signal. This is the main difference between the OOB radiation from large arrays and from well-studied legacy systems. Beamforming might focus the OOB radiation in certain directions but also significantly reduce the total power that has to be transmitted. For cost and power-consumption reasons, large arrays might have to be built from low-complexity hardware without advanced pre-compensation for linearization, which increases the relative amount of OOB radiation. Given that large arrays will be used in future base stations, a correct understanding of the OOB radiation is crucial to specify appropriate linearity requirements for the hardware. We show that the OOB radiation from large arrays varies little between coherence times; it is isotropic in many cases; and when it is beamformed, it is directed toward the served user in a very narrow beam with an array gain equal to or less than that of the in-band signal. We draw the conclusion that, compared to legacy systems, less stringent linearity requirements can be used in many systems with large arrays by virtue of the lower transmit power needed to upkeep the same received signal-to-noise ratio.
@article{diva2:1205630,
author = {Moll\'{e}n, Christopher and Larsson, Erik G and Gustavsson, Ulf and Eriksson, Thomas and Heath, Robert W. Jr.},
title = {{Out-of-Band Radiation from Large Antenna Arrays}},
journal = {IEEE Communications Magazine},
year = {2018},
volume = {56},
number = {4},
pages = {196--203},
}
In this letter, we introduce a novel pilot designapproach that minimizes the total mean square errors of theminimum mean square error estimators of all base stations (BSs)subject to the transmit power constraints of individual users inthe network, while tackling the pilot contamination in multicellmassive MIMO systems. First, we decompose the originalnon-convex problem into distributed optimization sub-problemsat individual BSs, where each BS can optimize its own pilotsignals given the knowledge of pilot signals from the remainingBSs. We then introduce a successive optimization approach totransform each optimization sub-problem into a linear matrixinequality form, which is convex and can be solved by availableoptimization packages. Simulation results confirm the fast convergenceof the proposed approach and prevails a benchmarkscheme in terms of providing higher accuracy.
@article{diva2:1204956,
author = {Al-Salihi, Hayder and Van Chien, Trinh and Le, Tuan Anh and Nakhai, Mohammad Reza},
title = {{A Successive Optimization Approach to Pilot Design for Multi-Cell Massive MIMO Systems}},
journal = {IEEE Communications Letters},
year = {2018},
volume = {22},
number = {5},
pages = {1086--1089},
}
Downlink beamforming in Massive multiple-input and multiple-output (MIMO) either relies on uplink pilot measurements-exploiting reciprocity and time-division duplexing operation, or on the use of a predetermined grid of beams with user equipments reporting their preferred beams, mostly in frequency-division duplexing operation. Massive MIMO in its originally conceived form uses the first strategy, with uplink pilots, whereas there is currently significant commercial interest in the second, grid-of-beams. It has been analytically shown that with isotropic scattering (independent Rayleigh fading) the first approach outperforms the second. Nevertheless, there remains controversy regarding their relative performance in practical channels. In this contribution, the performances of these two strategies are compared using measured channel data at 2.6 GHz.
@article{diva2:1201793,
author = {Flordelis, Jose and Rusek, Fredrik and Tufvesson, Fredrik and Larsson, Erik G and Edfors, Ove},
title = {{Massive MIMO Performance-TDD Versus FDD: What Do Measurements Say?}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {4},
pages = {2247--2261},
}
This letter considers the physical layer security of a pilot-based massive multiple-input multiple-output (MaMIMO) system in presence of a multi-antenna jammer. We propose a new jamming detection method that makes use of a generalized likelihood ratio tes
@article{diva2:1201791,
author = {Akhlaghpasand, Hossein and Razavizadeh, S. Mohammad and Björnson, Emil and Do, Tan Tai},
title = {{Jamming Detection in Massive MIMO Systems}},
journal = {IEEE Wireless Communications Letters},
year = {2018},
volume = {7},
number = {2},
pages = {242--245},
}
The joint design of spatial channel assignment and power allocation in multiple input multiple output (MIMO) systems capable of simultaneous wireless information and power transfer is studied. Assuming availability of channel state information at both communications ends, we maximize the harvested energy at the multi-antenna receiver, while satisfying a minimum information rate requirement for the MIMO link. We first derive the globally optimal eigenchannel assignment and power allocation design, and then present a practically motivated tight closed-form approximation for the optimal design parameters. Selected numerical results verify the validity of the optimal solution and provide useful insights on the proposed designs as well as the Pareto-optimal rate-energy tradeoff.
@article{diva2:1201792,
author = {Mishra, Deepak and Alexandropoulos, George C.},
title = {{Jointly Optimal Spatial Channel Assignment and Power Allocation for MIMO SWIPT Systems}},
journal = {IEEE Wireless Communications Letters},
year = {2018},
volume = {7},
number = {2},
pages = {214--217},
}
We illustrate the potential of Massive MIMO for communication with unmanned aerial vehicles (UAVs). We consider a scenario, where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Specifically, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight conditions. We develop a realistic geometric model, which incorporates an arbitrary orientation, of the GS and UAV antenna elements to characterize the polarization mismatch loss, which occurs due to the movement and orientation of the UAVs. A closed-form expression for a lower bound on the ergodic rate for a maximum-ratio combining receiver with estimated channel state information is derived. The optimal antenna spacing that maximizes the ergodic rate achieved by an UAV is also determined for uniform linear and rectangular arrays. It is shown that when the UAVs are spherically uniformly distributed around the GS, the ergodic rate per UAV is maximized for an antenna spacing equal to an integer multiple of one-half wavelength.
@article{diva2:1199523,
author = {Chandhar, Prabhu and Danev, Danyo and Larsson, Erik G.},
title = {{Massive MIMO for Communications With Drone Swarms}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {3},
pages = {1604--1629},
}
We consider transmission of system information in massive multiple-input multiple-output (MIMO). This information needs to be reliably delivered to inactive users in the cell without any channel state information at the base station. Downlink transmission entails the use of downlink pilots and a special type of precoding that aims to reduce the dimension of the downlink channel and the pilot overhead, which would otherwise scale with the number of base station antennas. We consider a scenario in which the base station transmits over a small number of coherence intervals, providing little time/frequency diversity. The system information is transmitted with orthogonal space-time block codes to increase reliability and performance is measured using outage rates. Several different codes are compared, both for spatially correlated and uncorrelated channels and for varying amounts of time/frequency diversity. We show that a massive MIMO base station can outperform a single-antenna base station in all considered scenarios.
@article{diva2:1199522,
author = {Karlsson, Marcus and Björnson, Emil and Larsson, Erik G},
title = {{Performance of In-Band Transmission of System Information in Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {3},
pages = {1700--1712},
}
In this paper, we study the effect of channel aging on the uplink and downlink performance of an FDD massive MIMO system, as the system dimension increases. Since the training duration scales linearly with the number of transmit dimensions, channel estimates become increasingly outdated in the communication phase, leading to performance degradation. To quantify this degradation, we first derive bounds on the mean squared channel estimation error. We use the bounds to derive deterministic equivalents of the receive SINRs, which yields a lower bound on the achievable uplink and downlink spectral efficiencies. For the uplink, we consider maximal ratio combining and MMSE detectors, while for the downlink, we consider matched filter and regularized zero forcing precoders. We show that the effect of channel aging can be mitigated by optimally choosing the frame duration. It is found that using all the base station antennas can lead to negligibly small achievable rates in high user mobility scenarios. Finally, numerical results are presented to validate the accuracy of our expressions and illustrate the dependence of the performance on the system dimension and channel aging parameters.
@article{diva2:1192845,
author = {Chopra, Ribhu and Murthy, Chandra R. and Suraweera, Himal A. and Larsson, Erik G},
title = {{Performance Analysis of FDD Massive MIMO Systems Under Channel Aging}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {2},
pages = {1094--1108},
}
This paper considers the downlink precoding for physical layer multicasting in massive multiple-input multiple-output (MIMO) systems. We study the max-min fairness (MMF) problem, where channel state information at the transmitter is used to design precoding vectors that maximize the minimum spectral efficiency (SE) of the system, given fixed power budgets for uplink training and downlink transmission. Our system model accounts for channel estimation, pilot contamination, arbitrary path-losses, and multi-group multicasting. We consider six scenarios with different transmission technologies (unicast and multicast), different pilot assignment strategies (dedicated or shared pilot assignments), and different precoding schemes (maximum ratio transmission and zero forcing), and derive achievable spectral efficiencies for all possible combinations. Then, we solve the MMF problem for each of these scenarios, and for any given pilot length, we find the SE maximizing uplink pilot and downlink data transmission policies, all in closed forms. We use these results to draw a general guideline for massive MIMO multicasting design, where for a given number of base station antennas, number of users, and coherence interval length, we determine the multicasting scheme that shall be used.
@article{diva2:1192588,
author = {Sadeghi, Meysam and Björnson, Emil and Larsson, Erik G and Yuen, Chau and Marzetta, Thomas L.},
title = {{Max-Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {2},
pages = {1358--1373},
}
n/a
@article{diva2:1192553,
author = {Pareschi, Fabio and Lustenberger, Felix and Johansson, Håkan and Cavallaro, Joseph},
title = {{Guest Editorial Special Issue on the 2017 IEEE International Symposium on Circuits and Systems (ISCAS 2017)}},
journal = {IEEE Transactions on Circuits and Systems Part 1},
year = {2018},
volume = {65},
number = {3},
pages = {857--858},
}
We consider a multipair massive multiple-input multiple-output (MIMO) two-way relaying system, where multiple pairs of single-antenna devices exchange data with the help of a relay employing a large number of antennas N. The relay consists of low-cost components that suffer from hardware impairments. A large-scale approximation of the spectral efficiency with maximum ratio processing is derived in closed form, and the approximation is tight as N -amp;gt; infinity. It is revealed that for a fixed hardware quality, the impact of the hardware impairments vanishes asymptotically when N grows large. Moreover, the impact of the impairments may even vanish when the hardware quality is gradually decreased with N, if a scaling law is satisfied. Finally, numerical results validate that multipair massive MIMO two-way relaying systems are robust to hardware impairments at the relay.
@article{diva2:1192409,
author = {Zhang, Jiayi and Xue, Xipeng and Björnson, Emil and Ai, Bo and Jin, Shi},
title = {{Spectral Efficiency of Multipair Massive MIMO Two-Way Relaying With Hardware Impairments}},
journal = {IEEE Wireless Communications Letters},
year = {2018},
volume = {7},
number = {1},
pages = {14--17},
}
This paper considers pilot design to mitigate pilot contamination and provide good service for everyone in multi-cell Massive multiple input multiple output (MIMO) systems. Instead of modeling the pilot design as a combinatorial assignment problem, as in prior works, we express the pilot signals using a pilot basis and treat the associated power coefficients as continuous optimization variables. We compute a lower bound on the uplink capacity for Rayleigh fading channels with maximum ratio detection that applies with arbitrary pilot signals. We further formulate the max-min fairness problem under power budget constraints, with the pilot signals and data powers as optimization variables. Because this optimization problem is non-deterministic polynomial-time hard due to signomial constraints, we then propose an algorithm to obtain a local optimum with polynomial complexity. Our framework serves as a benchmark for pilot design in scenarios with either ideal or non-ideal hardware. Numerical results manifest that the proposed optimization algorithms are close to the optimal solution obtained by exhaustive search for different pilot assignments and the new pilot structure and optimization bring large gains over the state-of-the-art suboptimal pilot design.
@article{diva2:1191346,
author = {Van Chien, Trinh and Björnson, Emil and Larsson, Erik G.},
title = {{Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {3},
pages = {2000--2015},
}
This paper considers the use of non-orthogonal-multiple-access (NOMA) in multiuser MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. A new NOMA scheme that uses shared pilots is proposed. Achievable rate analysis is carried out for different pilot signaling schemes, including both uplink and downlink pilots. The achievable rate performance of the proposed NOMA scheme with shared pilot within each group is compared with the traditional orthogonal access scheme with orthogonal pilots. Our proposed scheme is a generalization of the orthogonal scheme, and can be reduced to the orthogonal scheme when appropriate power allocation parameters are chosen. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms orthogonal schemes. However with more groups of users present in the cell, it is preferable to use multi-user beamforming instead of NOMA.
@article{diva2:1182413,
author = {Cheng, Victor and Björnson, Emil and Larsson, Erik G},
title = {{Performance Analysis of NOMA in Training-Based Multiuser MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {1},
pages = {372--385},
}
The capacity of cellular networks can be improved by the unprecedented array gain and spatial multiplexing offered by Massive MIMO. Since its inception, the coherent interference caused by pilot contamination has been believed to create a finite capacity limit, as the number of antennas goes to infinity. In this paper, we prove that this is incorrect and an artifact from using simplistic channel models and suboptimal precoding/combining schemes. We show that with multicell MMSE precoding/combining and a tiny amount of spatial channel correlation or large-scale fading variations over the array, the capacity increases without bound as the number of antennas increases, even under pilot contamination. More precisely, the result holds when the channel covariance matrices of the contaminating users are asymptotically linearly independent, which is generally the case. If also the diagonals of the covariance matrices are linearly independent, it is sufficient to know these diagonals (and not the full covariance matrices) to achieve an unlimited asymptotic capacity.
@article{diva2:1181671,
author = {Björnson, Emil and Hoydis, Jakob and Sanguinetti, Luca},
title = {{Massive MIMO Has Unlimited Capacity}},
journal = {IEEE Transactions on Wireless Communications},
year = {2018},
volume = {17},
number = {1},
pages = {574--590},
}
In this paper, we investigate the effect of bursty traffic and random availability of caching helpers in a wireless caching system. More explicitly, we consider a general system consisting of a caching helper with its dedicated user in proximity and another non-dedicated user requesting for content. Both the non-dedicated user and the helper have limited storage capabilities. When the user is not able to locate the requested content in its own cache, then its request shall be served either by the caching helper or by a large data center. Assuming bursty request arrivals at the caching helper from its dedicated destination, its availability to serve other users is affected by the request rate, which will further affect the system throughput and the delay experienced by the non-dedicated user. We characterize the maximum weighted throughput and the average delay per packet of the considered system, taking into account the request arrival rate of the caching helper, the request probability of the user and the availability of the data center. Our results provide fundamental insights in the throughput and delay behavior of such systems, which are essential for further investigation in larger topologies.
@article{diva2:1179618,
author = {Pappas, Nikolaos and Chen, Zheng and Dimitriou, Ioannis},
title = {{Throughput and Delay Analysis of Wireless Caching Helper Systems with Random Availability}},
journal = {IEEE Access},
year = {2018},
volume = {6},
pages = {9667--9678},
}
We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, the base station estimates not only the legitimate channel, but also the jamming channel by exploiting a purposely unused pilot sequence. The jamming channel estimate is used to construct linear receiver filters that reject the impact of the jamming signal. The performance of the proposed scheme is analytically evaluated using the asymptotic properties of massive MIMO. The best regularized zero-forcing receiver and the optimal power allocations for the legitimate system and the jammer are also studied. Numerical results are provided to verify our analysis and show that the proposed scheme greatly improves the achievable rates, as compared with conventional receivers. Interestingly, the proposed scheme works particularly well under strong jamming attacks, since the improved estimate of the jamming channel outweighs the extra jamming power.
@article{diva2:1170232,
author = {Do, Tan Tai and Björnson, Emil and Larsson, Erik G. and Mohammad Razavizadeh, S.},
title = {{Jamming-Resistant Receivers for the Massive MIMO Uplink}},
journal = {IEEE Transactions on Information Forensics and Security},
year = {2018},
volume = {13},
number = {1},
pages = {210--223},
}
A massive MIMO system, represented by a base station with hundreds of antennas, is capable of spatially multiplexing many devices and thus naturally suited to serve dense crowds of wireless devices in emerging applications, such as machine-type communications. Crowd scenarios pose new challenges in the pilot-based acquisition of channel state information and call for pilot access protocols that match the intermittent pattern of device activity. A joint pilot assignment and data transmission protocol based on random access is proposed in this paper for the uplink of a massive MIMO system. The protocol relies on the averaging across multiple transmission slots of the pilot collision events that result from the random access process. We derive new uplink sum rate expressions that take pilot collisions, intermittent device activity, and interference into account. Simplified bounds are obtained and used to optimize the device activation probability and pilot length. A performance analysis indicates how performance scales as a function of the number of antennas and the transmission slot duration.
@article{diva2:1172308,
author = {de Carvalho, Elisabeth and Björnson, Emil and Sorensen, Jesper H. and Larsson, Erik G. and Popovski, Petar},
title = {{Random Pilot and Data Access in Massive MIMO for Machine-Type Communications}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {12},
pages = {7703--7717},
}
We present a method for jamming a time-division duplex link using a transceiver with a large number of antennas. By utilizing beamforming, a jammer with M antennas can degrade the spectral efficiency of the primary link more than conventional omnidirectional jammers under the same power constraint, or perform equally well with approximately 1/M of the output power. The jammer operates without any prior knowledge of channels to the legitimate transmitters, or the legitimate signals by relying on channel reciprocity.
@article{diva2:1144798,
author = {Karlsson, Marcus and Björnson, Emil and Larsson, Erik G},
title = {{Jamming a TDD Point-to-Point Link Using Reciprocity-Based MIMO}},
journal = {IEEE Transactions on Information Forensics and Security},
year = {2017},
volume = {12},
number = {12},
pages = {2957--2970},
}
Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to the rates of multiple gigabit per second per user. Though mmWave can be readily used in stationary scenarios, such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult. To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed. This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond). We first summarize the recent channel measurement campaigns and modeling results. Then, we discuss in detail recent progresses in multiple input multiple output transceiver design for mmWave communications. After that, we provide an overview of the solution for multiple access and backhauling, followed by the analysis of coverage and connectivity. Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed.
@article{diva2:1140979,
author = {Xiao, Ming and Mumtaz, Shahid and Huang, Yongming and Dai, Linglong and Li, Yonghui and Matthaiou, Michail and Karagiannidis, George K. and Björnson, Emil and Yang, Kai and Chih-Lin, I and Ghosh, Amitabha},
title = {{Millimeter Wave Communications for Future Mobile Networks}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2017},
volume = {35},
number = {9},
pages = {1909--1935},
}
A new state-of-the-art multi-cell minimum mean square error (M-MMSE) scheme is proposed for massive multiple-input-multiple-output (MIMO) networks, which includes an uplink MMSE detector and a downlink MMSE precoder. Contrary to conventional single-cell schemes that suppress interference using only channel estimates for intra-cell users, our scheme shows the optimal way to suppress both intra-cell and inter-cell interference instantaneously by fully utilizing the available pilot resources. Specifically, let K and B denote the number of users per cell and the number of orthogonal pilot sequences in the network, respectively, where beta = B/K is the pilot reuse factor. Our scheme utilizes all B channel directions that can be estimated locally at each base station, to actively suppress both intra-cell and inter-cell interference. Our scheme is practical and general, since power control, imperfect channel estimation, and arbitrary pilot allocation are all accounted for. Simulations show that significant spectral efficiency (SE) gains are obtained over the conventional single-cell MMSE scheme and the multi-cell zero-forcing (ZF) scheme. Furthermore, large-scale approximations of the uplink and downlink signal-to-interference-and-noise ratios (SINRs) are derived, which are tight in the large-system limit. These approximations are easy to compute and very accurate even for small system dimensions. Using these SINR approximations, a low-complexity power control algorithm is further proposed to maximize the sum SE.
@article{diva2:1129881,
author = {Li, Xueru and Björnson, Emil and Larsson, Erik G and Zhou, Shidong and Wang, Jing},
title = {{Massive MIMO with multi-cell MMSE processing: exploiting all pilots for interference suppression}},
journal = {EURASIP Journal on Wireless Communications and Networking},
year = {2017},
}
n/a
@article{diva2:1129865,
author = {Xiao, Ming and Mumtaz, Shahid and Huang, Yongming and Dai, Linglong and Li, Yonghui and Matthaiou, Michail and Karagiannidis, George K. and Björnson, Emil and Yang, Kai and Chih-Lin, I. and Ghosh, Amitabha},
title = {{Editorial Material: Millimeter Wave Communications for Future Mobile Networks (Guest Editorial), Part I in IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, vol 35, issue 7, pp 1425-1431}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2017},
volume = {35},
number = {7},
pages = {1425--1431},
}
Proximity-based applications are becoming fast growing markets suggesting that device-to-device (D2D) communications is becoming an essential part of the future mobile data networks. We propose scalable admission and power control methods for D2D communications underlay cellular networks to increase the reuse of frequency resources and thus network capacity while maintaining QoS to all users. In practice, as D2D communications will generate a new layer of interference, it is essential to take D2D interference into account in inter-cell interference coordination for multi-cell communications. The aim of the proposed methods is to maximize the number of D2D links under QoS constraints, therefore maximizing network frequency reuse in a practical 5G multi-cell environment. Different schemes are designed for applications that have different levels of complexity and availability of channel state information. Numerical results show that by using D2D and the proposed multi-cell interference coordination and low power transmission method, the network spectral efficiency can be increased by as much as ten times, while low outage probability can be assured to provide QoS for all users.
@article{diva2:1120183,
author = {Verenzuela, Daniel and Miao, Guowang},
title = {{Scalable D2D Communications for Frequency Reuse 1 in 5G}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {6},
pages = {3435--3447},
}
5G wireless networks are expected to support new services with stringent requirements on data rates, latency and reliability. One novel feature is the ability to serve a dense crowd of devices, calling for radically new ways of accessing the network. This is the case in machine-type communications, but also in urban environments and hotspots. In those use cases, the high number of devices and the relatively short channel coherence interval do not allow per-device allocation of orthogonal pilot sequences. This article addresses the need for random access by the devices to pilot sequences used for channel estimation, and shows that Massive MIMO is a main enabler to achieve fast access with high data rates, and delay-tolerant access with different data rate levels. Three pilot access protocols along with data transmission protocols are described, fulfilling different requirements of 5G services.
@article{diva2:1109122,
author = {de Carvalho, Elisabeth and Björnson, Emil and Sorensen, Jesper H. and Popovski, Petar and Larsson, Erik G},
title = {{Random Access Protocols for Massive MIMO}},
journal = {IEEE Communications Magazine},
year = {2017},
volume = {55},
number = {5},
pages = {216--222},
}
We consider the Massive Multiple-Input MultipleOutput downlink with maximum-ratio and zero-forcing processing and time-division duplex operation. To decode, the users must know their instantaneous effective channel gain. Conventionally, it is assumed that by virtue of channel hardening, this instantaneous gain is close to its average and hence that users can rely on knowledge of that average (also known as statistical channel information). However, in some propagation environments, such as keyhole channels, channel hardening does not hold. We propose a blind algorithm to estimate the effective channel gain at each user, that does not require any downlink pilots. We derive a capacity lower bound of each user for our proposed scheme, applicable to any propagation channel. Compared with the case of no downlink pilots (relying on channel hardening), and compared with training-based estimation using downlink pilots, our blind algorithm performs significantly better. The difference is especially pronounced in environments that do not offer channel hardening.
@article{diva2:1109111,
author = {Ngo, Hien Quoc and Larsson, Erik G},
title = {{No Downlink Pilots Are Needed in TDD Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {5},
pages = {2921--2935},
}
Wireless content caching in small cell networks (SCNs) has recently been considered as an efficient way to reduce the data traffic and the energy consumption of the backhaul in emerging heterogeneous cellular networks. In this paper, we consider a cluster-centric SCN with combined design of cooperative caching and transmission policy. Small base stations (SBSs) are grouped into disjoint clusters, in which in-cluster cache space is utilized as an entity. We propose a combined caching scheme, where part of the cache space in each cluster is reserved for caching the most popular content in every SBS, while the remaining is used for cooperatively caching different partitions of the less popular content in different SBSs, as a means to increase local content diversity. Depending on the availability and placement of the requested content, coordinated multi-point technique with either joint transmission or parallel transmission is used to deliver content to the served user. Using Poisson point process for the SBS location distribution and a hexagonal grid model for the clusters, we provide analytical results on the successful content delivery probability of both transmission schemes for a user located at the cluster center. Our analysis shows an inherent tradeoff between transmission diversity and content diversity in our cooperation design. We also study the optimal cache space assignment for two objective functions: maximization of the cache service performance and the energy efficiency. Simulation results show that the proposed scheme achieves performance gain by leveraging cache-level and signal-level cooperation and adapting to the network environment and user quality-of-service requirements.
@article{diva2:1109109,
author = {Chen, Zheng and Lee, Jemin and Quek, Tony Q. S. and Kountouris, Marios},
title = {{Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {5},
pages = {3401--3415},
}
Although block compressive sensing (BCS) makes it tractable to sense large-sized images and video, its recovery performance has yet to be significantly improved because its recovered images or video usually suffer from blurred edges, loss of details, and high-frequency oscillatory artifacts, especially at a low subrate. This paper addresses these problems by designing a modified total variation technique that employs multi-block gradient processing, a denoised Lagrangian multiplier, and patch-based sparse representation. In the case of video, the proposed recovery method is able to exploit both spatial and temporal similarities. Simulation results confirm the improved performance of the proposed method for compressive sensing of images and video in terms of both objective and subjective qualities.
@article{diva2:1109085,
author = {Chien, Trinh Van and Dinh, Khanh Quoc and Jeon, Byeungwoo and Burger, Martin},
title = {{Block compressive sensing of image and video with nonlocal Lagrangian multiplier and patch-based sparse representation}},
journal = {Signal processing. Image communication},
year = {2017},
volume = {54},
pages = {93--106},
}
In this paper, we analyze the performance of the up-link communication of massive multicell multiple-input multiple-output (MIMO) systems under the effects of pilot contamination and delayed channels because of terminal mobility. The base stations (BSs) estimate the channels through the uplink training and then use zero-forcing (ZF) processing to decode the transmit signals from the users. The probability density function (pdf) of the signal-to-interference-plus-noise ratio (SINR) is derived for any finite number of antennas. From this pdf, we derive an achievable ergodic rate with a finite number of BS antennas in closed form. Insights into the impact of the Doppler shift (due to terminal mobility) at the low signal-to-noise ratio (SNR) regimes are exposed. In addition, the effects on the outage probability are investigated. Furthermore, the power scaling law and the asymptotic performance result by infinitely increasing the numbers of antennas and terminals (while their ratio is fixed) are provided. The numerical results demonstrate the performance loss for various Doppler shifts. Among the interesting observations revealed is that massive MIMO is favorable even under channel aging conditions.
@article{diva2:1098086,
author = {Papazafeiropoulos, Anastasios K. and Ngo, Hien Quoc and Ratnarajah, Tharmalingam},
title = {{Performance of Massive MIMO Uplink With Zero-Forcing Receivers Under Delayed Channels}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2017},
volume = {66},
number = {4},
pages = {3158--3169},
}
The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a challenging problem due to their nonconvex nature in interference channels. The aim of this paper is to develop a new and general framework to achieve globally optimal solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions with exponential complexity in the number of network links. To overcome the high complexity, we also propose a framework to compute suboptimal power control strategies with affordable complexity. This is achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed light on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the lower-complexity framework based on sequential programming. Numerical evidence is provided to show that the sequential fractional programming framework achieves global optimality in several practical communication scenarios.
@article{diva2:1097519,
author = {Zappone, Alessio and Björnson, Emil and Sanguinetti, Luca and Jorswieck, Eduard},
title = {{Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks}},
journal = {IEEE Transactions on Signal Processing},
year = {2017},
volume = {65},
number = {11},
pages = {2844--2859},
}
We consider a multi-way massive multiple-input multiple-output relay network with zero-forcing processing at the relay. By considering the time-division duplex protocol with channel estimation, we derive an analytical approximation of the spectral efficiency. This approximation is very tight and simple, which enables us to analyze the system performance, as well as to compare the spectral efficiency with zero-forcing and maximum-ratio processing. Our results show that by using a very large number of relay antennas and with the zero-forcing technique, we can simultaneously serve many active users in the same time-frequency resource, each with high spectral efficiency.
@article{diva2:1096672,
author = {Duc Ho, Chung and Ngo, Hien and Matthaiou, Michail and Duong, Trung Q.},
title = {{On the Performance of Zero-Forcing Processing in Multi-Way Massive MIMO Relay Networks}},
journal = {IEEE Communications Letters},
year = {2017},
volume = {21},
number = {4},
pages = {849--852},
}
The massive multiple-input multiple-output (MIMO) technology has great potential to manage the rapid growth of wireless data traffic. Massive MIMO achieves tremendous spectral efficiency by spatial multiplexing many tens of user equipments (UEs). These gains are only achieved in practice if many more UEs can connect efficiently to the network than today. As the number of UEs increases, while each UE intermittently accesses the network, the random access functionality becomes essential to share the limited number of pilots among the UEs. In this paper, we revisit the random access problem in the Massive MIMO context and develop a reengineered protocol, termed strongest-user collision resolution (SUCRe). An accessing UE asks for a dedicated pilot by sending an uncoordinated random access pilot, with a risk that other UEs send the same pilot. The favorable propagation of massive MIMO channels is utilized to enable distributed collision detection at each UE, thereby determining the strength of the contenders signals and deciding to repeat the pilot if the UE judges that its signal at the receiver is the strongest. The SUCRe protocol resolves the vast majority of all pilot collisions in crowded urban scenarios and continues to admit UEs efficiently in overloaded networks.
@article{diva2:1096670,
author = {Björnson, Emil and de Carvalho, Elisabeth and Sorensen, Jesper H. and Larsson, Erik G and Popovski, Petar},
title = {{A Random Access Protocol for Pilot Allocation in Crowded Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {4},
pages = {2220--2234},
}
Large-scale MIMO systems are well known for their advantages in communications, but they also have the potential for providing very accurate localization, thanks to their high angular resolution. A difficult problem arising indoors and outdoors is localizing users over multipath channels. Localization based on angle of arrival (AOA) generally involves a two-step procedure, where signals are first processed to obtain a users AOA at different base stations, followed by triangulation to determine the users position. In the presence of multipath, the performance of these methods is greatly degraded due to the inability to correctly detect and/or estimate the AOA of the line-of-sight (LOS) paths. To counter the limitations of this two-step procedure which is inherently suboptimal, we propose a direct localization approach in which the position of a user is localized by jointly processing the observations obtained at distributed massive MIMO base stations. Our approach is based on a novel compressed sensing framework that exploits channel properties to distinguish LOS from non-LOS signal paths, and leads to improved performance results compared to previous existing methods.
@article{diva2:1093287,
author = {Garcia, Nil and Wymeersch, Henk and Larsson, Erik G and Haimovich, Alexander M. and Coulon, Martial},
title = {{Direct Localization for Massive MIMO}},
journal = {IEEE Transactions on Signal Processing},
year = {2017},
volume = {65},
number = {10},
pages = {2475--2487},
}
Internet-of-Things (IoT) refers to a high-density network of low-cost, low-bitrate terminals and sensors where low energy consumption is also one central feature. As the power budget of classical receiver chains is dominated by the high-resolution analog-to-digital converters (ADCs), there is a growing interest toward deploying receiver architectures with reduced bit or even 1-bit ADCs. In this paper, we study waveform design, optimization, and detection aspects of multiuser massive MIMO downlink, where user terminals adopt very simple 1-bit ADCs with oversampling. In order to achieve spectral efficiency higher than 1 bit/s/Hz per real dimension, and per receiver antenna, we propose a two-stage precoding structure, namely, a novel quantization precoder followed by maximum-ratio transmission or zero-forcing-type spatial channel precoder which jointly form the multiuser multiantenna transmit waveform. The quantization precoder outputs are designed and optimized, under appropriate transmitter and receiver filter bandwidth constraints, to provide controlled intersymbol interference enabling the input symbols to be uniquely detected from 1-bit quantized observations with a low-complexity symbol detector in the absence of noise. An additional optimization constraint is also imposed in the quantization precoder design to increase the robustness against noise and residual interuser interference (IUI). The purpose of the spatial channel precoder, in turn, is to suppress the IUI and provide high beamforming gains such that good symbol error rates can be achieved in the presence of noise and interference. Extensive numerical evaluations illustrate that the proposed spatio-temporal precoder-based multiantenna waveform design can facilitate good multiuser link performance, despite the extremely simple 1-bitADCsin the receivers, hence being one possible enabling technology for the future low-complexity IoT networks.
@article{diva2:1089852,
author = {Gokceoglu, Ahmet and Björnson, Emil and Larsson, Erik G and Valkama, Mikko},
title = {{Spatio-Temporal Waveform Design for Multiuser Massive MIMO Downlink With 1-bit Receivers}},
journal = {IEEE Journal on Selected Topics in Signal Processing},
year = {2017},
volume = {11},
number = {2},
pages = {347--362},
}
Massive multiple input multiple output (MIMO) is one of the key technologies for fifth generation and can substantially improve energy and spectrum efficiencies. This paper explores the potential benefits of massive MIMO in spectrum sharing networks. We consider a multiuser MIMO primary network, with N-P-antenna primary base station (PBS) andK singleantenna primary users (PUs), and a multiple-input-single-output secondary network, with N-S-antenna secondary base station and a single-antenna secondary user. Using the proposed model, we derive a tight closed-form expression for the lower bound on the average achievable rate, which is applicable to arbitrary system parameters. By performing large-system analysis, we examine the impact of large number of PBS antennas and large number of PUs on the secondary network. It is shown that, when N-P and K grow large, N-S must be proportional to lnK or larger, to enable successful secondary transmission. In addition, we examine the impact of imperfect channel state information on the secondary network. It is shown that the detrimental effect of channel estimation errors is significantly mitigated as N-S grows large.
@article{diva2:1089851,
author = {Wang, Lifeng and Ngo, Hien and Elkashlan, Maged and Duong, Trung Q. and Wong, Kai-Kit},
title = {{Massive MIMO in Spectrum Sharing Networks: Achievable Rate and Power Efficiency}},
journal = {IEEE Systems Journal},
year = {2017},
volume = {11},
number = {1},
pages = {20--31},
}
This letter proposes anti-jamming strategies based on pilot retransmission for a single user uplink massive MIMO under jamming attack. A jammer is assumed to attack the system both in the training and data transmission phases. We first derive an achievable rate which enables us to analyze the effect of jamming attacks on the system performance. Counter-attack strategies are then proposed to mitigate this effect under two different scenarios: random and deterministic jamming attacks. Numerical results illustrate our analysis and benefit of the proposed schemes.
@article{diva2:1087898,
author = {Do, Tan Tai and Ngo, Hien and Duong, Trung Q. and Oechtering, Tobias J. and Skoglund, Mikael},
title = {{Massive MIMO Pilot Retransmission Strategies for Robustification Against Jamming}},
journal = {IEEE Wireless Communications Letters},
year = {2017},
volume = {6},
number = {1},
pages = {58--61},
}
Massive multiple-input, multiple-output (MIMO) is currently the most compelling wireless physical layer technology and a key component of fifth-generation (5G) systems. The understanding of its core principles has emerged during the last five years, and material is becoming available that is rigorously refined to focus on timeless fundamentals [1], facilitating the instruction of the topic to both master- and doctoral-level students [2]. Meaningful laboratory work that exposes the operational principles of massive MIMO is more difficult to accomplish. At Linköping University, Sweden, this was achieved through a project course, based on the conceive-design-implement-operate (CDIO) concept [3], and through the creation of a specially designed experimental setup using acoustic signals.
@article{diva2:1087803,
author = {Larsson, Erik G. and Danev, Danyo and Olofsson, Mikael and Sörman, Simon},
title = {{Teaching the Principles of Massive MIMO:
Exploring reciprocity-based multiuser MIMO beamforming using acoustic waves}},
journal = {IEEE signal processing magazine (Print)},
year = {2017},
volume = {34},
number = {1},
pages = {40--47},
}
This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple- output systems. Using the spectral efficiency (SE) as performance metric and setting a total energy budget per coherence interval, the power control is formulated as optimization problems for two different objective functions: the weighted minimum SE among the users and the weighted sum SE. A closed form solution for the optimal length of the pilot sequence is derived. The optimal power control policy for the former problem is found by solving a simple equation with a single variable. Utilizing the special structure arising from imperfect channel estimation, a convex reformulation is found to solve the latter problem to global optimality in polynomial time. The gain of the optimal joint power control is theoretically justified, and is proved to be large in the low-SNR regime. Simulation results also show the advantage of optimizing the power control over both pilot and data power, as compared to the cases of using full power and of only optimizing the data powers as done in previous work.
@article{diva2:1084903,
author = {Cheng, Victor and Björnson, Emil and Larsson, Erik G},
title = {{Optimal Pilot and Payload Power Control in Single-Cell Massive MIMO Systems}},
journal = {IEEE Transactions on Signal Processing},
year = {2017},
volume = {65},
number = {9},
pages = {2363--2378},
}
A Cell-Free Massive MIMO (multiple-input multiple-output) system comprises a very large number of distributed access points (APs), which simultaneously serve a much smaller number of users over the same time/frequency resources based on directly measured channel characteristics. The APs and users have only one antenna each. The APs acquire channel state information through time-division duplex operation and the reception of uplink pilot signals transmitted by the users. The APs perform multiplexing/de-multiplexing through conjugate beamforming on the downlink and matched filtering on the uplink. Closed-form expressions for individual user uplink and downlink throughputs lead to max-min power control algorithms. Max-min power control ensures uniformly good service throughout the area of coverage. A pilot assignment algorithm helps to mitigate the effects of pilot contamination, but power control is far more important in that regard. Cell-Free Massive MIMO has considerably improved performance with respect to a conventional small-cell scheme, whereby each user is served by a dedicated AP, in terms of both 95%-likely per-user throughput and immunity to shadow fading spatial correlation. Under uncorrelated shadow fading conditions, the cell-free scheme provides nearly fivefold improvement in 95%-likely per-user throughput over the small-cell scheme, and tenfold improvement when shadow fading is correlated.
@article{diva2:1084871,
author = {Ngo, Hien Quoc and Ashikhmin, Alexei and Yang, Hong and Larsson, Erik G and Marzetta, Thomas L.},
title = {{Cell-Free Massive MIMO Versus Small Cells}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {3},
pages = {1834--1850},
}
Analog-to-digital converters (ADCs) stand for a significant part of the total power consumption in a massive multiple-input multiple-output (MIMO) base station. One-bit ADCs are one way to reduce power consumption. This paper presents an analysis of the spectral efficiency of single-carrier and orthogonal-frequency-division-multiplexing (OFDM) transmission in massive MIMO systems that use one-bit ADCs. A closed-form achievable rate, i.e., a lower bound on capacity, is derived for a wideband system with a large number of channel taps that employ low-complexity linear channel estimation and symbol detection. Quantization results in two types of error in the symbol detection. The circularly symmetric error becomes Gaussian in massive MIMO and vanishes as the number of antennas grows. The amplitude distortion, which severely degrades the performance of OFDM, is caused by variations between symbol durations in received interference energy. As the number of channel taps grows, the amplitude distortion vanishes and OFDM has the same performance as single-carrier transmission. A main conclusion of this paper is that wideband massive MIMO systems work well with one-bit ADCs.
@article{diva2:1083712,
author = {Moll\'{e}n, Christopher and Choi, Junil and Larsson, Erik G. and Heath, Robert W.},
title = {{Uplink Performance of Wideband Massive MIMO With One-Bit ADCs}},
journal = {IEEE Transactions on Wireless Communications},
year = {2017},
volume = {16},
number = {1},
pages = {87--100},
}
Green cellular networking has become an important research area in recent years due to environmental and economical concerns. Switching OFF underutilized base stations (BSs) during oFF-peak traffic load conditions is a promising approach to reduce energy consumption in cellular networks. In practice, during initial cell planning, the BS locations and radio access network (RAN) parameters (BS transmit power, antenna height, and antenna tilt) are optimized to meet the basic system design requirements, such as coverage, capacity, overlap, quality of service (QoS), and so on. As these metrics are tightly coupled with each other due to co-channel interference, switching OFF certain BSs may affect the system requirements. Therefore, identifying a subset of large number of BSs, which are to be put into the sleep mode, is a challenging dynamic optimization problem. In this paper, we develop a multi-objective framework for dynamic optimization framework for orthogonal frequency division multiple access-based cellular systems. The objective is to identify the appropriate set of active sectors and RAN parameters that maximize coverage and area spectral efficiency, while minimizing overlap and area power consumption without violating the QoS requirements for a given traffic demand density. The objective functions and constraints are obtained using appropriate analytical models, which capture the traffic characteristics, propagation characteristics (path-loss, shadowing, and small-scale fading), as well as load condition in neighboring cells. A low-complexity evolutionary algorithm is used for identifying the global Pareto optimal solutions at a faster convergence rate. The inter-relationships between the system objectives are studied, and the guidelines are provided to find an appropriate network configuration that provides the best achievable tradeoffs. The results show that using the proposed framework, significant amount of energy saving can be achieved and with a low computational complexity while maintaining good tradeoffs among the other objectives.
@article{diva2:1109028,
author = {Chandhar, Prabhu and Sekhar Das, Suvra},
title = {{Multi-Objective Framework for Dynamic Optimization of OFDMA Cellular Systems}},
journal = {IEEE Access},
year = {2016},
volume = {4},
pages = {1889--1914},
}
In this paper, we investigate the coexistence of two technologies that have been put forward for the fifth generation (5G) of cellular networks, namely, network-assisted device-to-device (D2D) communications and massive MIMO (multiple-input multiple-output). Potential benefits of both technologies are known individually, but the tradeoffs resulting from their coexistence have not been adequately addressed. To this end, we assume that D2D users reuse the downlink resources of cellular networks in an underlay fashion. In addition, multiple antennas at the BS are used in order to obtain precoding gains and simultaneously support multiple cellular users using multiuser or massive MIMO technique. Two metrics are considered, namely the average sum rate (ASR) and energy efficiency (EE). We derive tractable and directly computable expressions and study the tradeoffs between the ASR and EE as functions of the number of BS antennas, the number of cellular users and the density of D2D users within a given coverage area. Our results show that both the ASR and EE behave differently in scenarios with low and high density of D2D users, and that coexistence of underlay D2D communications and massive MIMO is mainly beneficial in low densities of D2D users.
@article{diva2:1074364,
author = {Shalmashi, Serveh and Björnson, Emil and Kountouris, Marios and Won Sung, Ki and Debbah, Merouane},
title = {{Energy efficiency and sum rate tradeoffs for massive MIMO systems with underlaid device-to-device communications}},
journal = {EURASIP Journal on Wireless Communications and Networking},
year = {2016},
}
Transceiver hardware impairments (e.g., phase noise, inphase/quadrature-phase imbalance, amplifier nonlinearities, and quantization errors) have obvious degradation effects on the performance of wireless communications. While prior works have improved our knowledge of the influence of hardware impairments of single-user multiple-input multiple-output ( MIMO) systems over Rayleigh fading channels, an analysis encompassing the Rician fading channel is not yet available. In this paper, we pursue a detailed analysis of regular and large-scale (LS) MIMO systems over Rician fading channels by deriving new closed-form expressions for the achievable rate to provide several important insights for practical system design. More specifically, for regular MIMO systems with hardware impairments, there is always a finite achievable rate ceiling, which is irrespective of the transmit power and fading conditions. For LS-MIMO systems, it is interesting to find that the achievable rate loss depends on the Rician K-factor, which reveals that the favorable propagation in LS-MIMO systems can remove the influence of hardware impairments. However, we show that the nonideal LS-MIMO system can still achieve high spectral efficiency due to its huge degrees of freedom.
@article{diva2:1052401,
author = {Zhang, Jiayi and Dai, Linglong and Zhang, Xinlin and Björnson, Emil and Wang, Zhaocheng},
title = {{Achievable Rate of Rician Large-Scale MIMO Channels With Transceiver Hardware Impairments}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2016},
volume = {65},
number = {10},
pages = {8800--8806},
}
We consider the uplink of a cellular massive multiple-input multiple-output network. Acquiring channel state information at the base stations (BSs) requires uplink pilot signaling. Since the number of orthogonal pilot sequences is limited by the channel coherence, pilot reuse across cells is necessary to achieve high spectral efficiency. However, finding efficient pilot reuse patterns is non-trivial, especially in practical asymmetric BS deployments. We approach this problem using the coalitional game theory. Each BS has a few unique pilots and can form coalitions with other BSs to gain access to more pilots. The BSs in a coalition, thus, benefit from serving more users in their cells at the expense of higher pilot contamination and interference. Given that a cells average spectral efficiency depends on the overall pilot reuse pattern, the suitable coalitional game model is in the partition form. We develop a low-complexity distributed coalition formation based on individual stability. By incorporating a BS intercommunication budget constraint, we are able to control the overhead in message exchange between the BSs and ensure the algorithms convergence to a solution of the game called individually stable coalition structure. Simulation results reveal fast algorithmic convergence and substantial performance gains over the baseline schemes with no pilot reuse, full pilot reuse, or random pilot reuse pattern.
@article{diva2:1010364,
author = {Mochaourab, Rami and Björnson, Emil and Bengtsson, Mats},
title = {{Adaptive Pilot Clustering in Heterogeneous Massive MIMO Networks}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {8},
pages = {5555--5568},
}
In this paper, we investigate the secrecy performance of an energy harvesting relay system, where a legitimate source communicates with a legitimate destination via the assistance of multiple trusted relays. In the considered system, the source and relays deploy the time-switching-based radio frequency energy harvesting technique to harvest energy from a multi-antenna beacon. Different antenna selection and relay selection schemes are applied to enhance the security of the system. Specifically, two relay selection schemes based on the partial and full knowledge of channel state information, i. e., optimal relay selection and partial relay selection, and two antenna selection schemes for harvesting energy at source and relays, i. e., maximizing energy harvesting channel for the source and maximizing energy harvesting channel for the selected relay, are proposed. The exact and asymptotic expressions of secrecy outage probability in these schemes are derived. We demonstrate that applying relay selection approaches in the considered energy harvesting system can enhance the security performance. In particular, optimal relay selection scheme outperforms partial relay selection scheme and achieves full secrecy diversity order, regardless of energy harvesting scenarios.
@article{diva2:971866,
author = {Nguyen, Nam-Phong and Duong, Trung Q and Ngo, Hien Quoc and Hadzi-Velkov, Zoran and Shu, Lei},
title = {{Secure 5G Wireless Communications: A Joint Relay Selection and Wireless Power Transfer Approach}},
journal = {IEEE Access},
year = {2016},
volume = {4},
pages = {3349--3359},
}
This paper investigates the joint power allocationand user association problem in multi-cell Massive MIMO(multiple-input multiple-output) downlink (DL) systems. Thetarget is to minimize the total transmit power consumptionwhen each user is served by an optimized subset of the basestations (BSs), using non-coherent joint transmission. We firstderive a lower bound on the ergodic spectral efficiency (SE),which is applicable for any channel distribution and precodingscheme. Closed-form expressions are obtained for Rayleigh fadingchannels with either maximum ratio transmission (MRT) or zeroforcing (ZF) precoding. From these bounds, we further formulatethe DL power minimization problems with fixed SE constraintsfor the users. These problems are proved to be solvable aslinear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulatea max-min fairness problem which maximizes the worst SEamong the users, and we show that it can be solved as aquasi-linear program. Simulations manifest that the proposedmethods provide good SE for the users using less transmit powerthan in small-scale systems and the optimal user associationcan effectively balance the load between BSs when needed.Even though our framework allows the joint transmission frommultiple BSs, there is an overwhelming probability that only oneBS is associated with each user at the optimal solution.
@article{diva2:968009,
author = {Van Chien, Trinh and Björnson, Emil and Larsson, Erik G.},
title = {{Joint Power Allocation and User Association Optimization for Massive MIMO Systems}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {9},
pages = {6384--6399},
}
In massive multiple-input multiple-output (MIMO), most precoders result in downlink signals that suffer from high peak-to-average ratio (PAR), independently of modulation order and whether single-carrier or orthogonal frequency-division multiplexing (OFDM) transmission is used. The high PAR lowers the power efficiency of the base-station amplifiers. To increase the power efficiency, low-PAR precoders have been proposed. In this paper, we compare different transmission methods for massive MIMO in terms of the power consumed by the amplifiers. It is found that: 1) OFDM and single-carrier transmission have the same performance over a hardened massive MIMO channel and 2) when the higher amplifier power efficiency of low-PAR precoding is taken into account, conventional and low-PAR precoders lead to approximately the same power consumption. Since downlink signals with low PAR allow for simpler and cheaper hardware, than signals with high PAR, therefore, the results suggest that low-PAR precoding with either single-carrier or OFDM transmission should be used in a massive MIMO base station.
@article{diva2:952121,
author = {Moll\'{e}n, Christopher and Larsson, Erik G. and Eriksson, Thomas},
title = {{Waveforms for the Massive MIMO Downlink: Amplifier Efficiency, Distortion and Performance}},
journal = {IEEE Transactions on Communications},
year = {2016},
volume = {46},
number = {12},
pages = {5050--5063},
}
Simultaneous wireless information and power transfer techniques for multiway massive multiple-input multiple-output (MIMO) relay networks are investigated. By using two practically viable relay receiver designs, namely 1) the power splitting receiver and 2) the time switching receiver, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived for an unlimited number of antennas at the relay. These asymptotic SINRs are then used to derive asymptotic symmetric sum rate expressions in closed form. Notably, these asymptotic SINRs and sum rates become independent of radio frequency-to-direct current (RF-to-DC) conversion efficiency in the limit of infinitely many relay antennas. Moreover, tight average sum rate approximations are derived in closed form for finitely many relay antennas. The fundamental tradeoff between the harvested energy and the sum rate is quantified for both relay receiver structures. Notably, the detrimental impact of imperfect channel state information (CSI) on the MIMO detector/precoder is investigated, and thereby, the performance degradation caused by pilot contamination, which is the residual interference due to nonorthogonal pilot sequence usage in adjacent/cochannel systems, is quantified. The presence of cochannel interference (CCI) can be exploited to be beneficial for energy harvesting at the relay, and consequently, the asymptotic harvested energy is an increasing function of the number of cochannel interferers. Notably, in the genie-aided perfect CSI case, the detrimental impact of CCI for signal decoding can be cancelled completely whenever the number of relay antennas grows without bound. Nevertheless, the pilot contamination severely degrades the sum rate performance even for infinitely many relay antennas.
@article{diva2:950577,
author = {Amarasuriya, Gayan and Larsson, Erik G and Vincent Poor, H.},
title = {{Wireless Information and Power Transfer in Multiway Massive MIMO Relay Networks}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {6},
pages = {3837--3855},
}
We illustrate potential benefits of using massive antenna arrays for wireless energy transfer (WET). Specifically, we analyze probability of outage in WET over fading channels when a base station (BS) with multiple antennas beamforms energy to a wireless sensor node (WSN). Our analytical results show that by using massive antenna arrays, the range of WET can be increased for a given target outage probability. We prove that by using multiple-antenna arrays at the BS, a lower downlink energy is required to get the same outage performance, resulting in savings of radiated energy. We show that for energy levels used in WET, the outage performance with least-squares or minimum mean-square-error channel estimates is the same as that obtained based on perfect channel estimates. We observe that a strong line-of-sight component between the BS and WSN lowers outage probability. Furthermore, by deploying more antennas at the BS, a larger energy can be transferred reliably to the WSN at a given target outage performance for the sensor to be able to perform its main tasks. In our numerical examples, the RF power received at the input of the sensor is assumed to be on the order of a mW, such that the rectenna operates at an efficiency in the order of 50%.
@article{diva2:950562,
author = {Kashyap, Salil and Björnson, Emil and Larsson, Erik G},
title = {{On the Feasibility of Wireless Energy Transfer Using Massive Antenna Arrays}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {5},
pages = {3466--3480},
}
What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a "massive MIMO" fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.
@article{diva2:950493,
author = {Björnson, Emil and Sanguinetti, Luca and Kountouris, Marios},
title = {{Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO}},
journal = {IEEE Journal on Selected Areas in Communications},
year = {2016},
volume = {34},
number = {4},
pages = {832--847},
}
We consider uplink transmission of a massive multiuser multiple-input multiple-output (MU-MIMO) system in the presence of a smart jammer. The jammer aims to degrade the sum spectral efficiency of the legitimate system by attacking both the training and data transmission phases. First, we derive a closed-form expression for the sum spectral efficiency by taking into account the presence of a smart jammer. Then, we determine how a jammer with a given energy budget should attack the training and data transmission phases to induce the maximum loss to the sum spectral efficiency. Numerical results illustrate the impact of optimal jamming specifically in the large limit of the number of base station (BS) antennas.
@article{diva2:930953,
author = {Pirzadeh, Hessam and Razavizadeh, S. Mohammad and Björnson, Emil},
title = {{Subverting Massive MIMO by Smart Jamming}},
journal = {IEEE Wireless Communications Letters},
year = {2016},
volume = {5},
number = {1},
pages = {20--23},
}
The downlink of a massive MIMO system is considered for the case in which the base station must concurrently serve two categories of terminals: one group to which imperfect instantaneous channel state information (CSI) is available and one group to which no CSI is available. Motivating applications include broadcasting of public channels and control information in wireless networks. A new technique is developed and analyzed: joint beamforming and broadcasting (JBB), by which the base station beamforms to the group of terminals to which CSI is available, and broadcasts to the other group of terminals, to which no CSI is available. The broadcast information does not interfere with the beamforming as it is placed in the nullspace of the channel matrix collectively seen by the terminals targeted by the beamforming. JBB is compared to orthogonal access (OA) by which the base station partitions the time-frequency resources into two disjunct parts, one for each group of terminals. It is shown that JBB can substantially outperform OA in terms of required total radiated power for given rate targets.
@article{diva2:927613,
author = {Larsson, Erik G and Vincent Poor, H.},
title = {{Joint Beamforming and Broadcasting in Massive MIMO}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {4},
pages = {3058--3070},
}
The performance of multi-userMassiveMIMO-OFDMuplink systems in the presence of base station (BS) phase noise impairments is investigated. Closed-form achievable rate expressions are rigorously derived under two different operations, namely the case of a common oscillator (synchronous operation) at the BS and the case of independent oscillators at each BS antenna (non-synchronous operation). It is observed that the non-synchronous operation exhibits superior performance due to the averaging of intercarrier interference. Further, radiated power scaling lawsare derived, which are identical to the phase-noise-free case.
@article{diva2:923453,
author = {Pitarokoilis, Antonios and Björnson, Emil and Larsson, Erik G.},
title = {{Performance of the Massive MIMO Uplink with OFDM and Phase Noise}},
journal = {IEEE Communications Letters},
year = {2016},
volume = {20},
number = {8},
pages = {1595--1598},
}
Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively "antenna-efficient" regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.
@article{diva2:917195,
author = {Mueller, Axel and Kammoun, Abla and Björnson, Emil and Debbah, Merouane},
title = {{Linear precoding based on polynomial expansion: reducing complexity in massive MIMO}},
journal = {EURASIP Journal on Wireless Communications and Networking},
year = {2016},
number = {63},
}
Wireless communications is one of the most successful technologies in modern years, given that an exponential growth rate in wireless traffic has been sustained for over a century (known as Coopers law). This trend will certainly continue, driven by new innovative applications; for example, augmented reality and the Internet of Things. Massive MIMO has been identified as a key technology to handle orders of magnitude more data traffic. Despite the attention it is receiving from the communication community, we have personally witnessed that Massive MIMO is subject to several widespread misunderstandings, as epitomized by following (fictional) abstract: "The Massive MIMO technology uses a nearly infinite number of high-quality antennas at the base stations. By having at least an order of magnitude more antennas than active terminals, one can exploit asymptotic behaviors that some special kinds of wireless channels have. This technology looks great at first sight, but unfortunately the signal processing complexity is off the charts and the antenna arrays would be so huge that it can only be implemented in millimeter-wave bands." These statements are, in fact, completely false. In this overview article, we identify 10 myths and explain why they are not true. We also ask a question that is critical for the practical adoption of the technology and which will require intense future research activities to answer properly. We provide references to key technical papers that support our claims, while a further list of related overview and technical papers can be found at the Massive MIMO Info Point: http://massivemimo.eu
@article{diva2:913441,
author = {Björnson, Emil and Larsson, Erik G and Marzetta, Thomas L.},
title = {{Massive MIMO: Ten Myths and One Critical Question}},
journal = {IEEE Communications Magazine},
year = {2016},
volume = {54},
number = {2},
pages = {114--123},
}
We consider the multiple input single output (MISO) Gaussian broadcast channel with N-t antennas at the base station (BS) and N-u single-antenna users in the downlink. We propose a novel user grouping precoder which improves the sum rate performance of the zero-forcing (ZF) precoder specially when the channel is ill-conditioned. The proposed precoder partitions all the users into small groups of equal size. Downlink beamforming is then done in such a way that, at each users receiver, the interference from the signal intended for users not in its group is nulled out. Intragroup interference still remains, and is cancelled through successive interference presubtraction at the BS using dirty paper coding (DPC). The proposed user grouping method is different from user selection, since it is a method for precoding of information to the selected (scheduled) users, and not for selecting which users are to be scheduled. The proposed precoder is a generalization of two special cases, one where each group has only one user (ZF precoder) and another where all users are in a single group (ZF-DP precoder). A larger group size helps improve the sum rate performance but at the cost of greater complexity. The proposed generalization, therefore, allows for tradeoff between performance and complexity.
@article{diva2:913434,
author = {Khan Mohammed, Saif and Larsson, Erik G},
title = {{Improving the Performance of the Zero-Forcing Multiuser MISO Downlink Precoder Through User Grouping}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {2},
pages = {811--826},
}
Massive MIMO is a promising technique for increasing the spectral efficiency (SE) of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent transceiver processing. A common rule-of-thumb is that these systems should have an order of magnitude more antennas M than scheduled users K because the users channels are likely to be near-orthogonal when M/K > 10. However, it has not been proved that this rule-of-thumb actually maximizes the SE. In this paper, we analyze how the optimal number of scheduled users K-star depends on M and other system parameters. To this end, new SE expressions are derived to enable efficient system-level analysis with power control, arbitrary pilot reuse, and random user locations. The value of K-star in the large-M regime is derived in closed form, while simulations are used to show what happens at finite M, in different interference scenarios, with different pilot reuse factors, and for different processing schemes. Up to half the coherence block should be dedicated to pilots and the optimal M/K is less than 10 in many cases of practical relevance. Interestingly, K-star depends strongly on the processing scheme and hence it is unfair to compare different schemes using the same K.
@article{diva2:913429,
author = {Björnson, Emil and Larsson, Erik G and Debbah, Merouane},
title = {{Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {2},
pages = {1293--1308},
}
In order to enhance the effective resolution of time-interleaved analog-to-digital converters (TI-ADCs), both linear and nonlinear channel mismatches should be carefully calibrated. This paper concentrates on a bandwidth-efficient background calibration method for nonlinear errors in M-channel TI-ADCs. It utilizes the least-mean square algorithm as well as a certain degree of oversampling to achieve adaptive mismatch tracking. The calibration performance and computational complexity are investigated and evaluated through behavioral-level simulations. Furthermore, a calibration strategy for narrow-band input signals is proposed and verified as an improvement of the basic calibration structure for such signals.
@article{diva2:901797,
author = {Wang, Yinan and Johansson, Håkan and Xu, Hui and Diao, Jietao},
title = {{Bandwidth-efficient calibration method for nonlinear errors in M-channel time-interleaved ADCs}},
journal = {Analog Integrated Circuits and Signal Processing},
year = {2016},
volume = {86},
number = {2},
pages = {275--288},
}
A highly selective impedance transformation filtering technique suitable for tunable selective RF receivers is proposed in this paper. To achieve blocker rejection comparable to SAW filters, we use a two stage architecture based on a low noise trans-conductance amplifier (LNTA). The filter rejection is captured by a linear periodically varying (LPV) model that includes band limitation by the LNTA output impedance and the related parasitic capacitances of the impedance transformation circuit. This model is also used to estimate “back folding” by interferers placed at harmonic frequencies. Discussed is also the effect of thermal noise folding and phase noise on the circuit noise figure. As a proof of concept a chip design of a tunable RF front-end using 65 nm CMOS technology is presented. In measurements the circuit achieves blocker rejection competitive to SAW filters with noise figure 3.2-5.2 dB,out of bandIIP3 > +17 dBm and blocker P1dB > +5 dBm over frequency range of 0.5—3 GHz.
@article{diva2:871754,
author = {Qazi, Fahad and Duong, Quoc-Tai and Dabrowski, Jerzy},
title = {{Tunable Selective Receiver Front-End with Impedance Transformation Filtering}},
journal = {International journal of circuit theory and applications},
year = {2016},
volume = {44},
number = {5},
pages = {1071--1093},
}
The problem of maximum likelihood (ML) detection in training-assisted single-input multiple-output (SIMO) systems with phase noise impairments is studied for two different scenarios, i.e. the case when the channel is deterministic and known (constant channel) and the case when the channel is stochastic and unknown (fading channel). Further, two different operations with respect to the phase noise sources are considered, namely, the case of identical phase noise sources and the case of independent phase noise sources over the antennas. In all scenarios the optimal detector is derived for a very general parameterization of the phase noise distribution. Further, a high signal-to-noise-ratio (SNR) analysis is performed to show that symbol-error-rate (SER) floors appear in all cases. The SER floor in the case of identical phase noise sources (for both constant and fading channels) is independent of the number of antenna elements. In contrast, the SER floor in the case of independent phase noise sources is reduced when increasing the number of antenna elements (for both constant and fading channels). Finally, the system model is extended to multiple data channel uses and it is shown that the conclusions are valid for these setups, as well.
@article{diva2:868869,
author = {Pitarokoilis, Antonios and Björnson, Emil and Larsson, Erik G.},
title = {{ML Detection in Phase Noise Impaired SIMO Channels with Uplink Training}},
journal = {IEEE Transactions on Communications},
year = {2016},
volume = {64},
number = {1},
pages = {223--235},
}
Accurate and robust positioning in multipath environments can enable many applications, such as search-and-rescue and asset tracking. For this problem, ultra-wideband (UWB) technology can provide the most accurate range estimates, which are required for range-based positioning. However, UWB still faces a problem with non-line-of-sight (NLOS) measurements, in which the range estimates based on time-of-arrival (TOA) will typically be positively biased. There are many techniques that address this problem, mainly based on NLOS identification and NLOS error mitigation algorithms. However, these techniques do not exploit all available information in the UWB channel impulse response. Kernel-based machine learning methods, such as Gaussian Process Regression (GPR), are able to make use of all information, but they may be too complex in their original form. In this paper, we propose novel ranging methods based on kernel principal component analysis (kPCA), in which the selected channel parameters are projected onto a nonlinear orthogonal high-dimensional space, and a subset of these projections is then used as an input for ranging. We evaluate the proposed methods using real UWB measurements obtained in a basement tunnel, and found that one of the proposed methods is able to outperform state-of-the-art, even if little training samples are available.
@article{diva2:866356,
author = {Savic, Vladimir and Larsson, Erik G. and Ferrer-Coll, Javier and Stenumgaard, Peter},
title = {{Kernel Methods for Accurate UWB-Based Ranging with Reduced Complexity}},
journal = {IEEE Transactions on Wireless Communications},
year = {2016},
volume = {15},
number = {3},
pages = {1783--1793},
}
To ensure safety in confined environments such as mines or subway tunnels, a (wireless) sensor network can be deployed to monitor various environmental conditions. One of its most important applications is to track personnel, mobile equipment and vehicles. However, the state-of-the-art algorithms assume that the positions of the sensors are perfectly known, which is not necessarily true due to imprecise placement and/or dropping of sensors. Therefore, we propose an automatic approach for simultaneous refinement of sensors' positions and target tracking. We divide the considered area in a finite number of cells, define dynamic and measurement models, and apply a discrete variant of belief propagation which can efficiently solve this high-dimensional problem, and handle all non-Gaussian uncertainties expected in this kind of environments. Finally, we use ray-tracing simulation to generate an artificial mine-like environment and generate synthetic measurement data. According to our extensive simulation study, the proposed approach performs significantly better than standard Bayesian target tracking and localization algorithms, and provides robustness against outliers.
@article{diva2:789004,
author = {Savic, Vladimir and Wymeersch, Henk and Larsson, Erik G.},
title = {{Target Tracking in Confined Environments with Uncertain Sensor Positions}},
journal = {IEEE Transactions on Vehicular Technology},
year = {2016},
volume = {65},
number = {2},
pages = {870--882},
}
We propose a novel minimum mean square error estimator that estimates the channel power gain of the link from the secondary transmitter to the primary receiver (PRx). It lowers the root mean square error compared to several other estimators used in the underlay cognitive radio literature that first estimate the channel amplitude. We then analyze its system impact for two types of interference constraints. To this end, for the optimal binary transmit power control policy, we derive closed-form expressions for the average interference and the probability that the interference at the PRx violates a peak interference constraint with the proposed estimator. We show that the proposed estimator performs closer to the perfect channel state information scenario compared to the other estimators.
@article{diva2:954383,
author = {Kashyap, Salil and Mehta, Neelesh B.},
title = {{Power Gain Estimation and Its Impact on Binary Power Control in Underlay Cognitive Radio}},
journal = {IEEE Wireless Communications Letters},
year = {2015},
volume = {4},
number = {2},
pages = {193--196},
}
In recent years, the use of wireless systems in industrial applications has experienced spectacular growth. Unfortunately, industrial environments often present impulsive noise which degrades the reliability of wireless systems. OFDM is an enhanced technology used in industrial communication to monitor the work and movement of employees using high quality video. However, OFDM is sensitive to high amplitude impulsive noise because the noise energy spreads among all OFDM sub-carriers. This paper proposes a receiver structure consisting of two stages: a detector stage combining Fishers Quadratic discriminant and Gaussian Hypothesis techniques, and a suppression stage optimized by setting well defined thresholds. The receiver structure has been tested by simulations and measurements providing an increment in the probability of detection and improving the system performance.
@article{diva2:892931,
author = {Ferrer-Coll, Javier and Ben Slimane, Slimane and Chilo, Jose and Stenumgaard, Peter},
title = {{Detection and Suppression of Impulsive Noise in OFDM Receiver}},
journal = {Wireless personal communications},
year = {2015},
volume = {85},
number = {4},
pages = {2245--2259},
}
Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.
@article{diva2:892899,
author = {Gao, Xiang and Edfors, Ove and Tufvesson, Fredrik and Larsson, Erik G},
title = {{Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?}},
journal = {IEEE Transactions on Communications},
year = {2015},
volume = {63},
number = {11},
pages = {3917--3928},
}
To further enhance the dynamic performance of time-interleaved analog-to-digital converters (TI-ADCs), both linear and nonlinear mismatches should be estimated and compensated for. This paper introduces a method for joint calibration of several types of linear and nonlinear mismatch errors in two-channel TI-ADCs. To demonstrate the generality of this method, we take different scenarios into account, including static and dynamic mixed mismatch models. The proposed method utilizes a normalized least-mean square (N-LMS) algorithm as well as a certain low degree of oversampling for the overall converter to estimate and compensate for the mixed mismatch errors. The calibration performance and computational complexity are investigated and evaluated through simulations.
@article{diva2:842626,
author = {Wang, Yinan and Johansson, Håkan and Xu, Hui and Sun, Zhaolin},
title = {{Joint Blind Calibration for Mixed Mismatches in Two-Channel Time-Interleaved ADCs}},
journal = {IEEE Transactions on Circuits and Systems Part 1},
year = {2015},
volume = {62},
number = {6},
pages = {1508--1517},
}
This brief derives efficient two-stage-based polyphase structures for arbitrary-integer sampling rate conversion. For even-integer conversions, the overall structures correspond to parallelized conventional two-stage structures, but the derivations in this brief offer further insights when comparing the two cases of odd-and even-integer conversions. For the class of linear-phase finite-length impulse response Mth-band filters, it is then demonstrated through design examples that conversions by odd factors are in fact more efficient than by even factors.
@article{diva2:813051,
author = {Johansson, Håkan and Goeckler, Heinz},
title = {{Two-Stage-Based Polyphase Structures for Arbitrary-Integer Sampling Rate Conversion}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2015},
volume = {62},
number = {5},
pages = {486--490},
}
This brief proposes a method for designing modulated filter banks (FBs) with a large number of channels. The impulse response of the long prototype filter is parameterized in terms of a few short impulse responses, thus significantly reducing the number of unknown parameters. The proposed method starts by first obtaining an FB with a few channels. The solution of this FB is then partly reused as an initial (very close to final) solution in the design of FBs with a large number of channels. The number of unknown parameters hence drastically reduces. For example, we can first design a cosine modulated FB (CMFB) with three channels whose prototype filter has a stopband attenuation of about 40 dB. We can then reuse the solution of this CMFB in the design of a CMFB with 16 384 channels whose prototype filter has a similar stopband attenuation. With our proposed method, we need to reoptimize only 14 parameters to design the CMFB with 16 384 channels.
@article{diva2:811558,
author = {Eghbali, Amir and Johansson, Håkan},
title = {{Design of Modulated Filter Banks and Transmultiplexers With Unified Initial Solutions and Very Few Unknown Parameters}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2015},
volume = {62},
number = {4},
pages = {397--401},
}
Sub-Nyquist cyclic nonuniform sampling (CNUS) of a sparse multi-band signal generates a nonuniformly sampled signal. Assuming that the corresponding uniformly sampled signal satisfies the Nyquist sampling criterion, the sequence obtained via CNUS can be passed through a reconstructor to recover the missing uniform-grid samples. In order to recover the missing uniform-grid samples, the sequence obtained via CNUS is passed through a reconstructor. At present, these reconstructors have very high design and implementation complexity that offsets the gains obtained due to sub-Nyquist sampling. In this paper, we propose a scheme that reduces the design and implementation complexity of the reconstructor. In contrast to the existing reconstructors which use only a multi-channel synthesis filter bank (FB), the proposed reconstructor utilizes both analysis and synthesis FBs which makes it feasible to achieve an order-of-magnitude reduction of the complexity. The analysis filters are implemented using polyphase networks whose branches are allpass filters with distinct fractional delays and phase shifts. In order to reduce both the design and the implementation complexity of the synthesis FB, the synthesis filters are implemented using a cosine-modulated FB. In addition to the reduced complexity of the reconstructor, the proposed multi-channel recovery scheme also supports online reconfigurability which is required in flexible (multi-mode) systems where the user subband locations vary with time.
@article{diva2:810961,
author = {Pillai, Anu Kalidas Muralidharan and Johansson, Håkan},
title = {{Efficient Recovery of Sub-Nyquist Sampled Sparse Multi-Band Signals Using Reconfigurable Multi-Channel Analysis and Modulated Synthesis Filter Banks}},
journal = {IEEE Transactions on Signal Processing},
year = {2015},
volume = {63},
number = {19},
pages = {5238--5249},
}
This brief proposes a reconstruction scheme for the compensation of frequency-response mismatch errors at the output of a time-interleaved analog-to-digital converter (TI-ADC) with missing samples. The missing samples are due to sampling instants reserved for estimating the channel mismatch errors in the TI-ADC. Compared with previous solutions, the proposed scheme offers substantially lower computational complexity.
@article{diva2:810824,
author = {Muralidharan Pillai, Anu Kalidas and Johansson, Håkan},
title = {{Prefilter-Based Reconfigurable Reconstructor for Time-Interleaved ADCs With Missing Samples}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2015},
volume = {62},
number = {4},
pages = {392--396},
}
Due to channel mismatches in time-interleaved analog-to-digital converters (TIADCs), estimation and compensation methods are required to restore the resolution of the individual converters. Whereas several methods exist for linear mismatches, nonlinearity mismatches have not been widely investigated. This brief presents an adaptive background estimation method for nonlinearity mismatches in two-channel TIADCs. It utilizes a normalized least-mean-square algorithm and assumes slight oversampling as well as a polynomial nonlinearity model that is appropriate when smooth errors dominate. Furthermore, two implementation strategies are proposed to enhance its ability for different applications. The estimation performance of the proposed method is evaluated through behavioral-level simulations.
@article{diva2:802050,
author = {Wang, Yinan and Johansson, Håkan and Xu, Hui},
title = {{Adaptive Background Estimation for Static Nonlinearity Mismatches in Two-Channel TIADCs}},
journal = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
year = {2015},
volume = {62},
number = {3},
pages = {226--230},
}
This paper investigates linear precoding over nonsingular linear channels with additive white Gaussian noise, with lattice-type inputs. The aim is to maximize the minimum distance of the received lattice points, where the precoder is subject to an energy constraint. It is shown that the optimal precoder only produces a finite number of different lattices, namely perfect lattices, at the receiver. The well-known densest lattice packings are instances of perfect lattices, but are not always the solution. This is a counter-intuitive result as previous work in the area showed a tight connection between densest lattices and minimum distance. Since there are only finite many different perfect lattices, they can theoretically be enumerated offline. A new upper bound on the optimal minimum distance is derived, which significantly improves upon a previously reported bound, and is useful when actually constructing the precoders.
@article{diva2:791468,
author = {Kapetanovic, Dzevdan and Cheng, Hei Victor and Ho Mow, Wai and Rusek, Fredrik},
title = {{Lattice Structures of Precoders Maximizing the Minimum Distance in Linear Channels}},
journal = {IEEE Transactions on Information Theory},
year = {2015},
volume = {61},
number = {2},
pages = {908--916},
}
Books
Massive multiple-input multiple-output (Massive MIMO) is the latest technology that will improve the speed and throughput of wireless communication systems for years to come. Whilst there may be some debate over the origins of the term Massive MIMO and what it precisely means, this monograph describes in detail how the research conducted in the past decades lead to a scalable multiantenna technology that offers great throughput and energy efficiency under practical conditions. Written for students, practicing engineers and researchers who want to learn the conceptual and analytical foundations of Massive MIMO, in terms of spectral, energy, and/or hardware efficiency, as well as channel estimation and practical considerations, it provides a clear and tutorial like exposition of all the major topics. It also connects the dots of the research literature covering numerous topics not easily found therein. Massive MIMO Networks is the first monograph on the subject to cover the spatial chan el correlation and consider rigorous signal processing design essential for the complete understanding by its target audience.
@book{diva2:1220193,
author = {Björnson, Emil and Hoydis, Jakob and Sanguinetti, Luca},
title = {{Massive MIMO networks:
spectral, energy, and hardware efficiency}},
publisher = {Now Publishers Inc.},
year = {2017},
address = {Boston - Delft},
}
"Written by the pioneers of the concept, this is the first complete guide to the physical and engineering principles of Massive MIMO. Assuming only a basic background in communications and statistical signal processing, it will guide readers through key topics such as propagation models, channel modeling, and multi-cell performance analyses. The authors' unique capacity-bound approach will enable readers to carry out more effective system performance analysis and develop advanced Massive MIMO techniques and algorithms. Numerous case studies, as well as problem sets and solutions accompanying the book online, will help readers put knowledge into practice and acquire the skillset needed to design and analyze complex wireless communication systems. Whether you are a graduate student, researcher, or industry professional working in the field of wireless communications, this will be an indispensable guide for years to come"
@book{diva2:1088544,
author = {Marzetta, Thomas L. and Larsson, Erik G. and Hong, Yang and Ngo, Hien Quoc},
title = {{Fundamentals of massive MIMO}},
publisher = {Cambridge University Press},
year = {2016},
address = {Cambridge},
}
Book chapters
Every new network generation needs to make a leap in area data throughput, to manage the growing wireless data traffic. The Massive MIMO technologycan bring at least ten-fold improvements in area throughput by increasing the spec-tral efficiency (bit/s/Hz/cell), while using the same bandwidth and density of basestations as in current networks. These extraordinary gains are achieved by equipping the base stations with arrays of a hundred antennas to enable spatial multiplexing of tens of user terminals. This chapter explains the basic motivations and communication theory behind the Massive MIMO technology, and provides implementation-related design guidelines.
@incollection{diva2:1049059,
author = {Van Chien, Trinh and Björnson, Emil},
title = {{Massive MIMO Communications}},
booktitle = {5G Mobile Communications},
year = {2017},
pages = {77--116},
publisher = {Springer},
address = {Switzerland},
}
Conference papers
We consider a robust beamforming problem where large amount of downlink (DL) channel state information (CSI) data available at a multiple antenna access point (AP) is used to improve the link quality to a user equipment (UE) for beyond-5G and 6G applications such as environment-specific initial access (IA) or wireless power transfer (WPT). As the DL CSI available at the current instant may be imperfect or outdated, we propose a novel scheme which utilizes the (unknown) correlation between the antenna domain and physical domain to localize the possible future UE positions from the historical CSI database. Then, we develop a codebook design procedure to maximize the minimum sum beamforming gain to that localized CSI neighborhood. We also incorporate a UE specific parameter to enlarge the neighborhood to robustify the link further. We adopt an indoor channel model to demonstrate the performance of our solution, and benchmark against a usually optimal (but now sub-optimal due to outdated CSI) maximum ratio transmission (MRT) and a subspace based method. We numerically show that our algorithm outperforms the other methods by a large margin. This shows that customized environment-specific solutions are important to solve many future wireless applications, and we have paved the way to develop further data-driven approaches.
@inproceedings{diva2:1852000,
author = {Thoota, Sai Subramanyam and Vieira, Joao and Larsson, Erik G},
title = {{Data-Driven Robust Beamforming for Initial Access}},
booktitle = {IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM},
year = {2023},
series = {IEEE Global Communications Conference},
pages = {5757--5762},
publisher = {IEEE},
}
Distributed tensor decomposition (DTD) is a fundamental data-analytics technique that extracts latent important properties from multi-attribute datasets distributed over edge devices. Its conventional one-shot implementation with over-the-air computation (AirComp) is confronted with the issues of limited storage-and-computation capacities and link interruption, which motivates us to propose a framework of on-thefly communication-and-computing (FlyCom(2)) in this work. The proposed framework enables streaming computation with low complexity by leveraging a random sketching technique and achieves progressive global aggregation through the integration of progressive uploading and multiple-input-multiple-output (MIMO) AirComp. To develop FlyCom(2), an on-the-fly sub-space estimator is designed to take real-time sketches accumulated at the server to generate online estimates for the decomposition. Its performance is evaluated by deriving both deterministic and probabilistic error bounds, which reveal the scaling laws of the decomposition error and inspire a threshold-based scheme to select reliably received sketches. Experimental results validate the performance gain of the proposed selection algorithm and show that compared to its one-shot counterparts, FlyCom(2) achieves comparable (even better with large eigen-gaps) decomposition accuracy besides dramatically reducing devices' complexity costs.
@inproceedings{diva2:1851990,
author = {Chen, Xu and Larsson, Erik G and Huang, Kaibin},
title = {{On-the-Fly Communication-and-Computing for Distributed Tensor Decomposition}},
booktitle = {IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM},
year = {2023},
series = {IEEE Global Communications Conference},
pages = {1084--1089},
publisher = {IEEE},
}
In this paper, we consider a multi-server content-centric networking (CCN) architecture, where the servers have distinct trust credentials toward the user while the requested files convey the user's personal information. The servers can infer personal information when serving the user such that privacy concerns are triggered. Unlike the pre-processing and protocol-based solutions in literature, e.g., encryption, requiring additional processing or lacking quantitative information leakage measure, in this paper, an optimization-based collaborative content delivery strategy is developed to minimize the information leakage to the servers in the content delivery phase. Gaussian mixture model (GMM) is used to construct the user profile and the file contents. We leverage Kullback Leibler (KL) divergence between the exact and estimated user profiles to measure the privacy leakage. The formulated non-convex mixed-integer program is solved with a polyhedral outer approximation (POA) algorithm. We show that our scheme ultimately reduces information leakage over random content delivery while approaching the probabilistic method.
@inproceedings{diva2:1842594,
author = {Liao, Jialing},
title = {{Optimizing Privacy-Preserving Content-Centric Networks}},
booktitle = {ICC 2023 - IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS},
year = {2023},
series = {International Conference on Communications (ICC)},
pages = {4360--4365},
publisher = {IEEE},
}
The paper introduces frequency-domain implementations of variable digital filters using the overlap-save method. Expressions for implementation and design complexities are derived for real-valued impulse responses. Design examples include implementations of a variable bandwidth (VBW) filter alone as well as a cascade of a VBW filter and a variable fractional delay(VFD) filter. Compared to a time-domain implementation and a filter bank approach, the proposed structures can reduce the implementation complexity significantly and achieve savings up to 95% in the multiplication rate and up to 89% in the addition rate.
@inproceedings{diva2:1841417,
author = {Moryakova, Oksana and Johansson, Håkan},
title = {{Frequency-Domain Implementations of Variable Digital FIR Filters Using the Overlap-Save Technique}},
booktitle = {2023 24th International Conference on Digital Signal Processing (DSP)},
year = {2023},
series = {International Conference on Digital Signal Processing (DSP)},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
}
This paper introduces a low-complexity memoryless linearizer for suppression of distortion in analog-to-digital interfaces. It is inspired by neural networks, but has a substantially lower complexity than the neural network schemes that have appeared earlier in the literature in this context. The paper demonstrates that the proposed linearizer can outperform the conventional parallel memoryless Hammerstein linearizer even when the nonlinearities have been generated through a memoryless polynomial model. Further, a design procedure is proposed in which the linearizer parameters are obtained through matrix inversion. Thereby, the costly and time consuming it- erative nonconvex optimization that is traditionally used when training neural networks is eliminated. Moreover, the design and evaluation incorporate a large set of multi-tone signals covering the first Nyquist band. Simulations show signal-to-noise-and-distortion ratio (SNDR) improvements of some 25 dB for multi-tone signals that correspond to the quadrature parts of OFDM signals with QPSK modulation.
@inproceedings{diva2:1840286,
author = {Rodríguez Linares, Deijany and Johansson, Håkan},
title = {{Low-Complexity Memoryless Linearizer for Analog-to-Digital Interfaces}},
booktitle = {2023 24th International Conference on Digital Signal Processing (DSP)},
year = {2023},
series = {International Conference on Digital Signal Processing (DSP)},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
}
In this work, we consider a Federated Edge Learning (FEEL) system where training data are randomly generated over time at a set of distributed edge devices with long-term energy constraints. Due to limited communication resources and latency requirements, only a subset of devices is scheduled for participating in the local training process in every iteration. We formulate a stochastic network optimization problem for designing a dynamic scheduling policy that maximizes the time-average data importance from scheduled user sets subject to energy consumption and latency constraints. Our proposed algorithm based on the Lyapunov optimization framework outperforms alternative methods without considering time-varying data importance, especially when the generation of training data shows strong temporal correlation.
@inproceedings{diva2:1798929,
author = {Hu, Chung-Hsuan and Chen, Zheng and Larsson, Erik G},
title = {{DYNAMIC SCHEDULING FOR FEDERATED EDGE LEARNING WITH STREAMING DATA}},
booktitle = {2023 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW},
year = {2023},
publisher = {IEEE},
}
It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowdsensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio (C/N-0) estimates or automatic gain control (AGC) values. In this work, we exploit C/N-0 measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using C/N-0 measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.
@inproceedings{diva2:1792530,
author = {Olsson, Gladje Karl and Nilsson, Sara and Axell, Erik and Larsson, Erik G and Papadimitratos, Panos},
title = {{Using Mobile Phones for Participatory Detection and Localization of a GNSS Jammer}},
booktitle = {2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS},
year = {2023},
series = {IEEE-ION Position Location and Navigation Symposium},
pages = {536--541},
publisher = {IEEE},
}
Positioning with high precision and reliability can be provided by 5G cellular networks in environments where satellite positioning is not available or reliable. The accuracy that can be achieved by classical methods like triangulation and trilateration however degrades significantly under non line of sight (NLOS) conditions. The problem can be mitigated with increasingly dense deployments of network transmission and reception points (TRPs), but that is both impractical and costly. As an alternative, this study investigates if multipath propagation of radio signals can be exploited to improve positioning accuracy and reduce the necessary deployment density. With 3GPP Rel. 17 new signaling support has been introduced to report the propagation delay, corresponding to the length, of multiple paths between the user equipment (UE) and a network TRP. The length of a multipath can, in combination with a partially known map of the environment, give additional information about the UE position. In this study we develop multipath-assisted tracking algorithms and evaluate their performances in realistic simulations using 3GPP standardized positioning reference signals and measurements in an indoor factory environment. Our evaluations show that multipath-assisted algorithms can achieve an accuracy below 0.9 m in 90% of the cases, which is more than tenfold better than a conventional LOS based algorithm. Moreover, one algorithm variant also shows an ability to track a UE using very few TRPs.
@inproceedings{diva2:1792354,
author = {Andersson, Martin and Lidström, Andreas and Lindmark, Gustav},
title = {{Indoor 5G Positioning using Multipath Measurements}},
booktitle = {2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS},
year = {2023},
series = {IEEE-ION Position Location and Navigation Symposium},
pages = {1092--1098},
publisher = {IEEE},
}
The number of wireless devices is drastically increasing, resulting in many devices contending for radio resources. In this work, we present an algorithm to detect active devices for unsourced random access, i.e., the devices are uncoordinated. The devices use a unique, but non-orthogonal preamble, known to the network, prior to sending the payload data. They do not employ any carrier sensing technique and blindly transmit the preamble and data. To detect the active users, we exploit partial channel state information (CSI), which could have been obtained through a previous channel estimate. For static devices, e.g., Internet of Things nodes, it is shown that CSI is less time-variant than assumed in many theoretical works. The presented iterative algorithm uses a maximum likelihood approach to estimate both the activity and a potential phase offset of each known device. The convergence of the proposed algorithm is evaluated. The performance in terms of probability of miss detection and false alarm is assessed for different qualities of partial CSI and different signal-to-noise ratio.
@inproceedings{diva2:1772947,
author = {Callebaut, Gilles and Rottenberg, Francois and Van der Perre, Liesbet and Larsson, Erik G},
title = {{Grant-Free Random Access of IoT devices in Massive MIMO with Partial CSI}},
booktitle = {2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC},
year = {2023},
series = {IEEE Wireless Communications and Networking Conference},
publisher = {IEEE},
}
This paper introduces realizations of a reconfigurable finite-impulse-response (FIR) filter for simultaneous equalization and lowpass filtering. The proposed structures employ properties of both a variable bandwidth (VBW) filter and a variable equalizer (VE) with an adjustable coefficient using the Farrow structure, therefore they consist of weighted combinations of fixed subfilters. Design procedures using minimax optimization technique are provided. The paper includes a design example and complexity comparisons between the proposed structures of the reconfigurable lowpass equalizer (RLPE) and a common approach of using a regular FIR equalization filter requiring online redesign.
@inproceedings{diva2:1810280,
author = {Moryakova, Oksana and Wang, Yinan and Johansson, Håkan},
title = {{Reconfigurable FIR Lowpass Equalizers}},
booktitle = {2022 IEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS (SIPS)},
year = {2022},
series = {IEEE Workshop on Signal Processing Systems},
pages = {114--119},
publisher = {IEEE},
}
We discuss possible definitions of structural balance conditions in a network with preference orderings as node attributes. The main result is that for the case with three alternatives (A, B, C) we reduce the (3!)(3) = 216 possible configurations of triangles to 10 equivalence classes, and use these as measures of balance of a triangle towards possible extensions of structural balance theory. Moreover, we derive a general formula for the number of equivalent classes for preferences on n alternatives. Finally, we analyze a real-world data set and compare its empirical distribution of triangle equivalence classes to a null hypothesis in which preferences are randomly assigned to the nodes.
@inproceedings{diva2:1766774,
author = {Abrahamsson, Olle and Danev, Danyo and Larsson, Erik G},
title = {{Structural Balance Considerations for Networks with Preference Orders as Node Attributes}},
booktitle = {2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS},
year = {2022},
series = {Conference Record of the Asilomar Conference on Signals Systems and Computers},
pages = {1255--1261},
publisher = {IEEE},
}
Backscatter communication (BSC) is a promising solution for Internet-of-Things (IoT) connections due to its lowcomplexity, low-cost, and energy-efficient solution for sensors. There are several network infrastructure setups that can be used for BSC with IoT nodes/passive devices. One of them is a bistatic setup where there is a need for high dynamic range and high-resolution analog-to-digital converters at the reader side. In this paper, we investigate a bistatic BSC setup with multiple antennas. We propose a novel algorithm to suppress direct link interference between the carrier emitter (CE) and the reader using beamforming into the nullspace of the CEreader direct link to decrease the dynamic range of the system and increase the detection performance of the backscatter device (BSD). Further, we derive a Neyman-Pearson (NP) test and an exact closed-form expression for its performance in the detection of the BSD. Finally, simulation results show that the dynamic range of the system is significantly decreased and the detection performance of the BSD is increased by the proposed algorithm compared to a system not using beamforming in the CE, which could then be used in a host of different practical fields such as agriculture, transportation, factories, hospitals, smart cities, and smart homes.
@inproceedings{diva2:1755694,
author = {Kaplan, Ahmet and Vieira, Joao and Larsson, Erik G},
title = {{Dynamic Range Improvement in Bistatic Backscatter Communication Using Distributed MIMO}},
booktitle = {2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022)},
year = {2022},
series = {IEEE Global Communications Conference},
pages = {2486--2492},
publisher = {IEEE},
}
Deep learning (DL) is a powerful technique for many real-time applications, but it is vulnerable to adversarial attacks. Herein, we consider DL-based modulation classification, with the objective to create DL models that are robust against attacks. Specifically, we introduce three defense techniques: i) randomized smoothing, ii) hybrid projected gradient descent adversarial training, and iii) fast adversarial training, and evaluate them under both white-box (WB) and black-box (BB) attacks. We show that the proposed fast adversarial training is more robust and computationally efficient than the other techniques, and can create models that are extremely robust to practical (BB) attacks.
@inproceedings{diva2:1750184,
author = {Manoj, B. R. and Santos, Pablo Millan and Sadeghi, Meysam and Larsson, Erik G.},
title = {{Toward Robust Networks against Adversarial Attacks for Radio Signal Modulation Classification}},
booktitle = {2022 IEEE 23RD INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATION (SPAWC)},
year = {2022},
series = {IEEE International Workshop on Signal Processing Advances in Wireless Communications},
publisher = {IEEE},
}
In this paper, we consider privacy aspects of wireless federated learning (FL) with Over-the-Air (OtA) transmission of gradient updates from multiple users/agents to an edge server. OtA FL enables the users to transmit their updates simultaneously with linear processing techniques, which improves resource efficiency. However, this setting is vulnerable to privacy leakage since an adversary node can hear directly the uncoded message. Traditional perturbation-based methods provide privacy protection while sacrificing the training accuracy due to the reduced signal-to-noise ratio. In this work, we aim at minimizing privacy leakage to the adversary and the degradation of model accuracy at the edge server at the same time. More explicitly, spatially correlated perturbations are added to the gradient vectors at the users before transmission. Using the zero-sum property of the correlated perturbations, the side effect of the added perturbation on the aggregated gradients at the edge server can be minimized In the meanwhile, the added perturbation will not be canceled out at the adversary, which prevents privacy leakage. Theoretical analysis of the perturbation covariance matrix, differential privacy, and model convergence is provided, based on which an optimization problem is formulated to jointly design the covariance matrix and the power scaling factor to balance between privacy protection and convergence performance. Simulation results validate the correlated perturbation approach can provide strong defense ability while guaranteeing high learning accuracy.
@inproceedings{diva2:1728393,
author = {Liao, Jialing and Chen, Zheng and Larsson, Erik G},
title = {{Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbations}},
booktitle = {2022 58TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON)},
year = {2022},
series = {Annual Allerton Conference on Communication Control and Computing},
publisher = {IEEE},
}
Massive multiple input multiple output (MIMO)emerged as the leading technology for supporting fifth generation(5G) and beyond 5G cellular communication systems. Due to thetremendous increase in data traffic in urban areas and to meetsuch a significant demand, most studies consider macro/micro celldeployments in urban environments. Internet service providers(ISPs) are less interested in providing communication services inrural areas considering the relatively low profits compared to thedeployment and maintenance costs. In this paper, we investigatethe massive MIMO performance in rural scenarios. In particular,we investigate different aspects to consider while designing along-range communication system. We propose to use elevatedbase station (BS) with sectorized antennas with unusually largeaperture and implement a user scheduling algorithm at theBS to provide full digital coverage. We analyze the coveragerange of a massive MIMO system to provide high-rate services.Furthermore, we also analyze the link budget requirements andthe rates users can achieve in such a SuperCell massive MIMOnetwork.
@inproceedings{diva2:1728209,
author = {Kunnath Ganesan, Unnikrishnan and Björnson, Emil and Larsson, Erik G.},
title = {{Bridging the Digital Divide Using SuperCell Massive MIMO}},
booktitle = {2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)},
year = {2022},
series = {IEEE Conference on Vehicular Technology (VTC)},
publisher = {IEEE},
address = {London, United Kingdom},
}
Base stations in 5G and beyond use advanced antenna systems (AASs), where multiple passive antenna elements and radio units are integrated into a single box. A critical bottleneck of such a system is the digital fronthaul between the AAS and baseband unit (BBU), which has limited capacity. In this paper, we study an AAS used for precoded downlink transmission over a multi-user multiple-input multiple-output (MU-MIMO) channel. First, we present the baseline quantization-unaware precoding scheme created when a precoder is computed at the BBU and then quantized to be sent over the fronthaul. We propose a new precoding design that is aware of the fronthaul quantization. We formulate an optimization problem to minimize the mean squared error at the receiver side. We rewrite the problem to utilize mixed-integer programming to solve it. The numerical results manifest that our proposed precoding greatly outperforms quantization-unaware precoding in terms of sum rate.
@inproceedings{diva2:1725173,
author = {Khorsandmanesh, Yasaman and Björnson, Emil and Jalden, Joakim},
title = {{QUANTIZATION-AWARE PRECODING FOR MU-MIMO WITH LIMITED-CAPACITY FRONTHAUL}},
booktitle = {2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)},
year = {2022},
series = {International Conference on Acoustics Speech and Signal Processing ICASSP},
pages = {5378--5382},
publisher = {IEEE},
}
Wireless power transfer (WPT) is an alternative technology to conventional batteries for powering Internet of things (IoT) devices. WPT is especially beneficial in situations when battery replacement is infeasible or expensive. It can also reduce battery-related e-waste. In this paper, we analyze the limits of adopting WPT technology for remote powering of IoT devices. We assume that an IoT device periodically harvests energy from a base station (BS) and transmits a data packet related to the sensor measurement under shadow fading channel conditions. Our goal is to characterize the epsilon-coverage range, where epsilon is the probability of the coverage. Our analysis shows a tradeoff between the coverage range and the rate of sensor measurements, where the maximal epsilon-coverage range is achieved as the sensor measurement rate approaches zero. We demonstrate that the weighted sum of the sleep power consumption and the harvesting sensitivity power of an IoT device limits the maximal e-coverage range. Beyond that range, the IoT device cannot harvest enough energy to operate. The desired rate of the sensor measurements also significantly impacts the epsilon-coverage range. Our results suggest that for an IoT device designed using current technology, the maximal 0.95-coverage range is in the order of 120 m. When high measurement rates are required, the coverage range drops to 50-100 m. Compared to battery-powered IoT devices, WPT is well-suited for medium-range applications plus when battery replacement is costly.
@inproceedings{diva2:1718709,
author = {Tavana, Morteza and Björnson, Emil and Zander, Jens},
title = {{Range Limits of Energy Harvesting from a Base Station for Battery-Less Internet-of-Things Devices}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {153--158},
publisher = {IEEE},
}
An Intelligent Reflecting Surface (IRS) is an emerging technology for improving the data rate over wireless channels by controlling the underlying channel. In this paper, we describe a novel solution for IRS configuration to maximize the data rate over wideband channels. The optimization is obtained by online training of a deep generative neural network. Inspired by related works in image processing, this network is randomly initialized and acts as a regularization term for the optimization process since the structure of the generator is sufficient to capture a great deal of IRS statistics prior to any learning. In contrast to recent deep learning techniques for IRS configuration, the proposed technique does not require an offline training stage and can adapt quickly to any environment. Compared to the previous state-of-the-art algorithm, the proposed method is significantly faster and obtains IRS configurations that achieve higher data transmission rates.
@inproceedings{diva2:1718675,
author = {Fireaizen, Tomer and Metzer, Gal and Ben-David, Dan and Moshe, Yair and Cohen, Israel and Björnson, Emil},
title = {{Intelligent Reflecting Surface OFDM Communication with Deep Neural Prior}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {2645--2650},
publisher = {IEEE},
}
In this paper, we examine the energy consumption of a user equipment (UE) when it transmits a finite-sized data packet. The receiving base station (BS) controls a reconfigurable intelligent surface (RIS) that can be utilized to improve the channel conditions, if additional pilot signals are transmitted to configure the RIS. We derive a formula for the energy consumption taking both the pilot and data transmission powers into account. By dividing the RIS into subarrays consisting of multiple RIS elements using the same reflection coefficient, the pilot overhead can be tuned to minimize the energy consumption while maintaining parts of the aperture gain. Our analytical results show that there exists an energy-minimizing subarray size. For small data blocks and when the channel conditions between the BS and UE are favorable compared to the path to the RIS, the energy consumption is minimized using large subarrays. When the channel conditions to the RIS are better and the data blocks are large, it is preferable to use fewer elements per subarray and potentially configure the elements individually.
@inproceedings{diva2:1718670,
author = {Enqvist, Anders and Demir, Ozlem Tugfe and Cavdar, Cicek and Björnson, Emil},
title = {{Optimizing Reconfigurable Intelligent Surfaces for Small Data Packets: A Subarray Approach}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {2664--2669},
publisher = {IEEE},
}
Previous works on cell-free massive MIMO mostly consider physical-layer and fronthaul transport aspects. How to deploy cell-free massive MIMO functionality in a practical wireless system is an open problem. This paper proposes a new cell-free architecture that can be implemented on top of a virtualized cloud radio access network (V-CRAN). We aim to minimize the end-to-end power consumption by jointly considering the radio, optical fronthaul, virtualized cloud processing resources, and spectral efficiency requirements of the user equipments. The considered optimization problem is cast in a mixed binary second-order cone programming form and, thus, the global optimum can be found using a branch-and-bound algorithm. The optimal power-efficient solution of our proposed cell-free system is compared with conventional small-cell implemented using V-CRAN, to determine the benefits of cell-free networking. The numerical results demonstrate that cell-free massive MIMO increases the maximum rate substantially, which can be provided with almost the same energy per bit. We show that it is more power-efficient to activate cell-free massive MIMO already at low spectral efficiencies (above 1 bit/s/Hz).
@inproceedings{diva2:1718640,
author = {Demir, Ozlem Tugfe and Masoudi, Meysam and Björnson, Emil and Cavdar, Cicek},
title = {{Cell-Free Massive MIMO in Virtualized CRAN: How to Minimize the Total Network Power?}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {159--164},
publisher = {IEEE},
}
How to manage the interference introduced by the enormous wireless devices is a crucial issue to address in the prospective sixth-generation (6G) communications. The treating interference as noise (TIN) optimality conditions are commonly used for interference management and thus attract significant interest in existing wireless systems. Cell-free massive multiple-input multiple-output (CF mMIMO) is a promising technology in 6G that exhibits high system throughput and excellent interference management by exploiting a large number of access points (APs) to serve the users collaboratively. In this paper, we take the first step on studying TIN in CF mMIMO systems from a stochastic geometry perspective by investigating the probability that the TIN conditions hold with spatially distributed network nodes. We propose a novel analytical framework for TIN in a CF mMIMO system with both Binomial Point Process (BPP) and Poisson Point Process (PPP) approximations. We derive the probability that the TIN conditions hold in close form using the PPP approximation. Numerical results validate our derived expressions and illustrate the impact of various system parameters on the probability that the TIN conditions hold.
@inproceedings{diva2:1718636,
author = {Chen, Shuaifei and Zhang, Jiayi and Chen, Zheng and Ai, Bo},
title = {{Treating Interference as Noise in Cell-Free Massive MIMO Networks}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022)},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {1385--1390},
publisher = {IEEE},
}
RadioWeaves, in which distributed antennas with integrated radio and compute resources serve a large number of users, is envisioned to provide high data rates in next-generation wireless systems. In this paper, we develop a physical layer abstraction model to evaluate the performance of different RadioWeaves deployment scenarios. This model helps speed up system-level simulators of the RadioWeaves and is made up of two blocks. The first block generates a vector of signalto-interference-plus-noise ratios (SINRs) corresponding to each coherence block, and the second block predicts the packet error rate corresponding to the SINRs generated. The vector of SINRs generated depends on different parameters such as the number of users, user locations, antenna configurations, and precoders. We have also considered different antenna gain patterns, such as omni-directional and directional microstrip patch antennas. Our model exploits the benefits of exponential effective SINR mapping (EESM). We study the robustness and accuracy of the EESM for RadioWeaves.
@inproceedings{diva2:1709422,
author = {Rimalapudi, Sarvendranath and Kunnath Ganesan, Unnikrishnan and Shaik, Zakir Hussain and Larsson, Erik G},
title = {{Physical Layer Abstraction Model for RadioWeaves}},
booktitle = {2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-SPRING)},
year = {2022},
series = {IEEE Vehicular Technology Conference VTC},
publisher = {IEEE},
}
Radio frequency (RF) wireless power transfer (WPT) is a promising technology for 6G use cases. It enables a massive yet sustainable deployment of batteryless energy neutral (EN) devices at an unprecedented scale. Recent research on 6G is exploring high operating frequencies up to the THz spectrum, where antenna arrays with large apertures are capable of forming narrow, "laser-like" beams. At sub-10 GHz frequencies, physically large antenna arrays are considered that are operating in the array near field. Transmitting spherical wavefronts, power can be focused to a focal point rather than a beam, which allows for efficient and radiation-safe WPT. We formulate a multipath channel model comprising specular components and diffuse scattering to find the WPT power budget in a realistic indoor scenario. Specular components can be predicted by means of a geometric model. This is used to transmit power via multiple beams simultaneously, increasing the available power budget and expanding the initial access distance. We show that exploiting this "beam diversity" reduces the required fading margin for the initial access to EN devices.
@inproceedings{diva2:1699244,
author = {Deutschmann, Benjamin J. B. and Wilding, Thomas and Larsson, Erik G and Witrisal, Klaus},
title = {{Location-based Initial Access for Wireless Power Transfer with Physically Large Arrays}},
booktitle = {2022 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS)},
year = {2022},
series = {IEEE International Conference on Communications Workshops},
pages = {127--132},
publisher = {IEEE},
}
GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported worldwide in the last decade. It is important to detect attacks fast and localize attackers, which can be hard if not impossible without dedicated sensing infrastructure. The notion of participatory sensing, or crowdsensing, is that a large ensemble of voluntary contributors provides the measurements, rather than relying on dedicated sensing infrastructure. This work considers embedded GNSS receivers to provide measurements for participatory jamming detection and localization. Specifically, this work proposes a novel jamming localization algorithm, based on participatory sensing, that exploits AGC and C/N-0 estimates from commercial GNSS receivers. The proposed algorithm does not require knowledge of the jamming power nor of the channels, but automatically estimates all parameters. The algorithm is shown to outperform similar state-of-the-art localization algorithms in relevant scenarios.
@inproceedings{diva2:1697379,
author = {Olsson, Gladje Karl and Axell, Erik and Larsson, Erik G and Papadimitratos, Panos},
title = {{Participatory Sensing for Localization of a GNSS Jammer}},
booktitle = {2022 INTERNATIONAL CONFERENCE ON LOCALIZATION AND GNSS (ICL-GNSS)},
year = {2022},
series = {International Conference on Localization and GNSS},
publisher = {IEEE},
}
We provide the optimal receive combining strategy for federated learning in multiple-input multiple-output (MIMO) systems. Our proposed algorithm allows the clients to perform individual gradient sparsification which greatly improves performance in scenarios with heterogeneous (non i.i.d.) training data. The proposed method beats the benchmark by a wide margin.
@inproceedings{diva2:1695473,
author = {Becirovic, Ema and Chen, Zheng and Larsson, Erik G.},
title = {{Optimal MIMO Combining for Blind Federated Edge Learning with Gradient Sparsification}},
booktitle = {IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
year = {2022},
series = {IEEE International Workshop on Signal Processing Advances in Wireless Communications},
pages = {1--5},
publisher = {IEEE},
}
In this paper, we work on channel estimationtechniques for massive multiple-input multiple-output (MIMO) with Cauchy noise. In the standard massive MIMO setup, the users transmit orthonormal pilots during the training phase and the received signal in the base station is projected onto each orthonormal pilot signal. This process is optimum when the noise is Gaussian. In other words, the obtained signal after this processis the sufficient statistic and we do not lose any information. We show that this process is not optimum when the noise is Cauchy. Hence, we propose a channel estimation technique forthe unprocessed received signal. The proposed channel estimation technique is compared with the channel estimates that are obtained from the projected signal.
@inproceedings{diva2:1694260,
author = {Gülgün, Ziya and Larsson, Erik G.},
title = {{Channel Estimation for Massive MIMO in the Presence of Cauchy Noise}},
booktitle = {ICC 2022 - IEEE International Conference on Communications},
year = {2022},
series = {IEEE International Conference on Communications proceedings},
pages = {1769--1774},
publisher = {IEEE},
}
RadioWeaves network operates a large number ofdistributed antennas using cell-free architecture to provide highdata rates and support a large number of users. Operating thisnetwork in an energy-efficient manner in the limited availablespectrum is crucial. Therefore, we consider energy efficiency(EE) maximization of a RadioWeaves network that shares spectrumwith a collocated primary network in underlay mode.To simplify the problem, we lower bound the non-convex EEobjective function to form a convex problem. We then propose adownlink power allocation policy that maximizes the EE of thesecondary RadioWeaves network subject to power constraint ateach access point and interference constraint at each primaryuser. Our numerical results investigate the secondary system’sperformance in interference, power, and EE constrained regimeswith correlated fading channels. Furthermore, they show that theproposed power allocation scheme performs significantly betterthan the simpler equal power allocation scheme.
@inproceedings{diva2:1687581,
author = {Shaik, Zakir Hussain and Sarvendranath, Rimalapudi and Larsson, Erik G.},
title = {{Energy-Efficient Power Allocation for an Underlay Spectrum Sharing RadioWeaves Network}},
booktitle = {\emph{ICC 2022 - IEEE International Conference on Communications, Korea, Seoul, 16-20 May 2022}},
year = {2022},
series = {IEEE International Conference on Communications},
pages = {799--804},
publisher = {IEEE},
}
Anomaly detection plays a critical role in ensuring the robustness and reliability of federated learning (FL) systems involving distributed implementation of stochastic gradient descent (SGD). Existing methods in the literature usually apply norm-based gradient filters in each iteration and eliminate possible outliers, which can be ineffective in a setting with heterogeneous and unbalanced training data. We propose a heuristic yet novel scheme for adjusting the weights in the gradient aggregation step that accounts for two anomaly metrics, namely the relative distance and the convergence measure. Simulation results show that our proposed scheme brings notable performance gain compared to norm-based policies when the agents have distinct data distributions.
@inproceedings{diva2:1694198,
author = {Chen, Zheng and Hu, Chung-Hsuan and Larsson, Erik G.},
title = {{Anomaly-Aware Federated Learning with Heterogeneous Data}},
booktitle = {2021 IEEE International Conference on Autonomous Systems (ICAS)},
year = {2021},
pages = {1--5},
publisher = {IEEE},
}
We study downlink (DL) channel estimation in a multi-cell Massive multiple-input multiple-output (MIMO) system operating in a time-division duplex. The users must know their effective channel gains to decode their received DL data signals. A common approach is to use the mean value as the estimate, motivated by channel hardening, but this is associated with a substantial performance loss in non-isotropic scattering environments. We propose two novel estimation methods. The first method is model-aided and utilizes asymptotic arguments to identify a connection between the effective channel gain and the average received power during a coherence block. The second one is a deep-learning-based approach that uses a neural network to identify a mapping between the available information and the effective channel gain. We compare the proposed methods against other benchmarks in terms of normalized mean-squared error and spectral efficiency (SE). The proposed methods provide substantial improvements, with the learning-based solution being the best of the considered estimators.
@inproceedings{diva2:1694172,
author = {Ghazanfari, Amin and Van Chien, Trinh and Björnson, Emil and Larsson, Erik G.},
title = {{Learning to Perform Downlink Channel Estimation in Massive MIMO Systems}},
booktitle = {2021 17th International Symposium on Wireless Communication Systems (ISWCS)},
year = {2021},
series = {International Symposium on Wireless Communication Systems (ISWCS)},
pages = {1--6},
}
Grant-free multiple access (GFMA) mitigates the uplink handshake overhead to support low-latency communication by transmitting payload data together with the pilot (preamble). However, the channel capacity with random access is limited by the number of available orthogonal pilots and the incoordination among devices. We consider a delay-constrained GFMA system, where each device with randomly generated data traffic needs to deliver its data packets before some pre-determined deadline. The pilot selection problem is formulated to minimize the average packet drop rate of the worst user. A priority-sorting based centralized policy is derived by introducing a fairness promoting function. For decentralization, we propose a multi-agent policy optimization algorithm with improved sample efficiency by exploring the model structure. Simulation results show that our proposed scheme facilitates near-optimal coordination between devices by using only partial state information.
@inproceedings{diva2:1694140,
author = {Bai, Jianan and Chen, Zheng and Larsson, Erik G.},
title = {{Multi-agent Policy Optimization for Pilot Selection in Delay-constrained Grant-free Multiple Access}},
booktitle = {2021 55th Asilomar Conference on Signals, Systems, and Computers},
year = {2021},
series = {Asilomar Conference on Signals, Systems, and Computers},
pages = {1477--1481},
publisher = {IEEE},
}
With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a learning framework that suits beyond SG and towards 6G systems. This work looks into a future scenario in which there are multiple groups with different learning purposes and participating in different FL processes. We give energy-efficient solutions to demonstrate that this scenario can be realistic. First, to ensure a stable operation of multiple FL processes over wireless channels, we propose to use a massive multiple-input multiple-output network to support the local and global FL training updates, and let the iterations of these FL processes be executed within the same large-scale coherence time. Then, we develop asynchronous and synchronous transmission protocols where these iterations are asynchronously and synchronously executed, respectively, using the downlink unicasting and conventional uplink transmission schemes. Zero-forcing processing is utilized for both uplink and downlink transmissions. Finally, we propose an algorithm that optimally allocates power and computation resources to save energy at both base station and user sides, while guaranteeing a given maximum execution time threshold of each FL iteration. Compared to the baseline schemes, the proposed algorithm significantly reduces the energy consumption, especially when the number of base station antennas is large.
@inproceedings{diva2:1662213,
author = {Vu, Tung T. and Ngo, Hien Quoc and Ngo, Duy T. and Dao, Minh N. and Larsson, Erik G},
title = {{Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups}},
booktitle = {2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
year = {2021},
series = {IEEE Global Communications Conference},
publisher = {IEEE},
}
In this paper, we consider a cellular-based Internet of things (IoT) network consisting of IoT devices that can communicate directly with each other in a device-to-device (D2D) fashion as well as send real-time status updates about some underlying physical processes observed by them. We assume that such real-time applications are supported by cellular networks where cellular base stations (BSs) collect status updates over time from a subset of the IoT devices in their vicinity. We characterize two performance metrics: i) the network throughput which quantifies the performance of D2D communications, and ii) the Age of Information which quantifies the performance of the real-time IoT-enabled applications. Concrete analytical results are derived using stochastic geometry by modeling the locations of IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another Independent PPP. Our results provide useful design guidelines on the efficient deployment of future IoT networks that will jointly support D2D communications and several cellular network-enabled real-time applications.
@inproceedings{diva2:1662126,
author = {Mankar, Praful D. and Chen, Zheng and Abd-Elmagid, Mohamed A. and Pappas, Nikolaos and Dhillon, Harpreet S.},
title = {{A Spatio-temporal Analysis of Cellular-based IoT Networks under Heterogeneous Traffic}},
booktitle = {2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
year = {2021},
series = {IEEE Global Communications Conference},
publisher = {IEEE},
}
The knowledge of channel covariance matrices is of paramount importance to the estimation of instantaneous channels and the design of beamforming vectors in multi-antenna systems. In practice, an abrupt change in channel covariance matrices may occur due to the change in the environment and the user location. Although several works have proposed efficient algorithms to estimate the channel covariance matrices after any change occurs, how to detect such a change accurately and quickly is still an open problem in the literature. In this paper, we focus on channel covariance change detection between a multiantenna base station (BS) and a single-antenna user equipment (UE). To provide theoretical performance limit, we first propose a genie-aided change detector based on the log-likelihood ratio (LLR) test assuming the channel covariance matrix after change is known, and characterize the corresponding missed detection and false alarm probabilities. Then, this paper considers the practical case where the channel covariance matrix after change is unknown. The maximum likelihood (ML) estimation technique is used to predict the covariance matrix based on the received pilot signals over a certain number of coherence blocks, building upon which the LLR-based change detector is employed. Numerical results show that our proposed scheme can detect the change with low error probability even when the number of channel samples is small such that the estimation of the covariance matrix is not that accurate. This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.
@inproceedings{diva2:1662125,
author = {Liu, Runnan and Liu, Liang and He, Dazhi and Zhang, Wenjun and Larsson, Erik G},
title = {{Detection of Abrupt Change in Channel Covariance Matrix for Multi-Antenna Communication}},
booktitle = {2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
year = {2021},
series = {IEEE Global Communications Conference},
publisher = {IEEE},
}
Reconfigurable intelligent surfaces (RISs) have recently received widespread attention in the field of wireless communication. An RIS can be controlled to reflect incident waves from the transmitter towards the receiver; a feature that is believed to fundamentally contribute to beyond SG wireless technology. The typical RIS consists of entirely passive elements, which requires the high-dimensional channel estimation to be done elsewhere. Therefore, in this paper, we present a semi-passive large-scale RIS architecture equipped with only a small fraction of simplified receiver units with only 1-bit quantization. Based on this architecture, we first propose an alternating direction method of multipliers (ADMM)-based approach to recover the training signals at the passive RIS elements, We then obtain the global channel by combining a channel sparsification step with the generalized approximate message passing (GAMP) algorithm. Our proposed scheme exploits both the sparsity and low-rankness properties of the channel in the joint spatial-frequency domain of a wideband mmWave multiple-input-multiple-output (MIMO) communication system. Simulation results show that the proposed algorithm can significantly reduce the pilot signaling needed for accurate channel estimation and outperform previous methods, even with fewer receiver units.
@inproceedings{diva2:1662117,
author = {Hu, Jiangfeng and Yin, Haifan and Björnson, Emil},
title = {{MmWave MIMO Communication with Semi-Passive RIS: A Low-Complexity Channel Estimation Scheme}},
booktitle = {2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
year = {2021},
series = {IEEE Global Communications Conference},
publisher = {IEEE},
}
Reconfigurable intelligent surfaces (RISs) have attracted great attention as a potential beyond SG technology. These surfaces consist of many passive elements of metamaterials whose impedance can be controllable to change the phase, amplitude, or other characteristics of wireless signals impinging on them. Channel estimation is a critical task when it comes to the control of a large RIS when having a channel with a large number of multipath components. In this paper, we propose a novel channel estimation scheme that exploits spatial correlation characteristics at both the massive multiple-input multiple-output (MIMO) base station and the planar RISs, and other statistical characteristics of multi-specular fading in a mobile environment. Moreover, a novel heuristic for phase-shift selection at the RISs is developed, inspired by signal processing methods that are effective in conventional massive MIMO. Simulation results demonstrate that the proposed uplink RIS-aided framework improves the spectral efficiency of the cell-edge mobile users substantially in comparison to a conventional single-cell massive MIMO system.
@inproceedings{diva2:1662115,
author = {Demir, Ozlem Tugfe and Björnson, Emil},
title = {{RIS-Assisted Massive MIMO with Multi-Specular Spatially Correlated Fading}},
booktitle = {2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)},
year = {2021},
series = {IEEE Global Communications Conference},
publisher = {IEEE},
}
This paper presents a novel strategy to decentralize the soft detection procedure in an uplink cell-free massive multiple-input-multiple-output network. We propose efficient approaches to compute the a posteriori probability-per-bit, exactly or approximately, when having a sequential fronthaul. More precisely, each access point (AP) in the network computes partial sufficient statistics locally, fuses it with received partial statistics from another AP, and then forward the result to the next AP. Once the sufficient statistics reach the central processing unit, it performs the soft demodulation by computing the log-likelihood ratio (LLR) per bit, and then a channel decoding algorithm (e.g., a Turbo decoder) is utilized to decode the bits. We derive the distributed computation of LLR analytically.
@inproceedings{diva2:1636172,
author = {Shaik, Zakir Hussain and Björnson, Emil and Larsson, Erik G.},
title = {{Distributed Computation of A Posteriori Bit Likelihood Ratios in Cell-Free Massive MIMO}},
booktitle = {2021 29th European Signal Processing Conference (EUSIPCO)},
year = {2021},
pages = {935--939},
publisher = {IEEE},
}
In a distributed multi-antenna system, multiple geographically separated transmit nodes communicate simultaneously to a receive node. Synchronization of these nodes is essential to achieve a good performance at the receiver. RadioWeaves is a new paradigm of cell-free massive MIMO array deployment using distributed multi-antenna panels in indoor environments. In this paper, we study the carrier frequency synchronization problem in distributed RadioWeave panels. We propose a novel, over-the-air synchronization protocol, which we call as BeamSync, to synchronize all the different multi-antenna transmit panels. We also show that beamforming the synchronization signal in the dominant direction of the channel between the panels is optimal and the synchronization performance is significantly better than traditional beamforming techniques.
@inproceedings{diva2:1633532,
author = {Kunnath Ganesan, Unnikrishnan and Sarvendranath, Rimalapudi and Larsson, Erik G.},
title = {{BeamSync:
Over-The-Air Carrier Synchronization in Distributed RadioWeaves}},
booktitle = {25th International ITG Workshop on Smart Antennas (WSA 2021)},
year = {2021},
publisher = {IEEE},
}
Deep learning (DL) is becoming popular as a new tool for many applications in wireless communication systems. However, for many classification tasks (e.g., modulation classification) it has been shown that DL-based wireless systems are susceptible to adversarial examples; adversarial examples are well-crafted malicious inputs to the neural network (NN) with the objective to cause erroneous outputs. In this paper, we extend this to regression problems and show that adversarial attacks can break DL-based power allocation in the downlink of a massive multiple-input-multiple-output (maMIMO) network. Specifically, we extend the fast gradient sign method (FGSM), momentum iterative FGSM, and projected gradient descent adversarial attacks in the context of power allocation in a maMIMO system. We benchmark the performance of these attacks and show that with a small perturbation in the input of the NN, the white-box attacks can result in infeasible solutions up to 86%. Furthermore, we investigate the performance of black-box attacks. All the evaluations conducted in this work are based on an open dataset and NN models, which are publicly available.
@inproceedings{diva2:1620244,
author = {Banugondi Rajashekara, Manoj and Sadeghi, Meysam and Larsson, Erik G},
title = {{Adversarial Attacks on Deep Learning Based Power Allocation in a Massive MIMO Network}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021)},
year = {2021},
series = {IEEE International Conference on Communications},
publisher = {IEEE},
}
Caching popular contents at a large number of access points and edge-clouds is a promising solution to alleviate the increasing backhaul congestion in beyond fifth-generation (B5G) networks. By integrating with cell-free massive multiple-input multiple-output (CF mMIMO), wireless caching can harness their combined virtues, i.e., almost uniform service quality, strong macro-diversity, and reduction of the data traffic from the core network. In this paper, we consider an offline cache-aided scenario with two caching strategies to minimize the total energy consumption (TEC), which are evaluated from the cache hit probability (CHP). The TEC minimization is showed to be NP-complete and, hence, dealt with a proposed greedy algorithm. An adaptive power control policy is proposed to reduce the TEC. We compare CF mMIMO with small cells in terms of the successful content delivery probability (SCDP) and TEC, respectively. The numerical results show that CF mMIMO can offer a much more uniform service, significantly higher SCDP, and lower average TEC when compared to than SC.
@inproceedings{diva2:1620169,
author = {Chen, Shuaifei and Zhang, Jiayi and Björnson, Emil and Wang, Shuai and Xing, Chengwen and Ai, Bo},
title = {{Wireless Caching: Cell-Free versus Small Cells}},
booktitle = {IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021)},
year = {2021},
series = {IEEE International Conference on Communications},
publisher = {IEEE},
}
Novel network architectures for 6G distributed massive MIMO systems rely on coherent signaling by distributed antenna panels which are coordinated by a central controller. This type of network architecture is based on reciprocity operation where antenna panels rely on uplink channel estimates for coherent downlink precoding. This paper proposes a calibration method for distributed massive MIMO systems, which overcomes hardware non-reciprocities in order to enable reciprocity-based operation. Measurements for system calibration are collected via a beam-sweep between all pairs of antenna panels. We lay out the system model for this new setup, and propose a maximum likelihood-based procedure to compute calibration coefficients based on the collected measurement set. The procedure is computationally efficient and stable, since 1) each iteration has a closed-form, and 2) the procedure is guaranteed to converge to at least a local optimum (or saddle point). Simulations indicate significant calibration improvements compared to re-using state of the art calibration schemes for the problem at hand.
@inproceedings{diva2:1619691,
author = {Vieira, Joao and Larsson, Erik G.},
title = {{Reciprocity calibration of Distributed Massive MIMO Access Points for Coherent Operation}},
booktitle = {2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)},
year = {2021},
series = {IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)},
pages = {783--787},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
}
Classification between different activities in an indoor environment using wireless signals is an emerging technology for various applications, including intrusion detection, patient care, and smart home. Researchers have shown different methods to classify activities and their potential benefits by utilizing WiFi signals. In this paper, we analyze classification of moving objects by employing machine learning on real data from a massive multi-input-multi-output (MIMO) system in an indoor environment. We conduct measurements for different activities in both line-of-sight and non line-of-sight scenarios with a massive MIMO testbed operating at 3.7 GHz. We propose algorithms to exploit amplitude and phase-based features classification task. For the considered setup, we benchmark the classification performance and show that we can achieve up to 98% accuracy using real massive MIMO data, even with a small number of experiments. Furthermore, we demonstrate the gain in performance results with a massive MIMO system as compared with that of a limited number of antennas such as in WiFi devices.
@inproceedings{diva2:1616368,
author = {Manoj, B. R. and Tian, Guoda and Gunnarsson, Sara and Tufvesson, Fredrik and Larsson, Erik G},
title = {{MOVING OBJECT CLASSIFICATION WITH A SUB-6 GHZ MASSIVE MIMO ARRAY USING REAL DATA}},
booktitle = {2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)},
year = {2021},
pages = {8133--8137},
publisher = {IEEE},
}
Massive MIMO (Multiple Input Multiple Output) has demonstrated as a potential candidate for 5G-and-beyond wireless networks. Instead of using Gaussian signals as most of the previous works, this paper makes a novel contribution by investigating the transmission quality of image data by utilizing the Massive MIMO technology. We first construct a framework to decode the image signal from the noisy received data in the uplink Massive MIMO transmission by utilizing the alternating direction method of multipliers (ADMM) approach. Then, a low-pass filter is exploited to enhance the efficiency of the remaining noise and artifacts reduction in the recovered image. Numerical results demonstrate the necessity of a post-filtering process in enhancing the quality of image recovery.
@inproceedings{diva2:1602560,
author = {Phan Thi, Kim Chinh and van Chien, Trinh and Tran, Manh Hoang and Nguyen, Tien Hoa and Nguyen, Van Duc},
title = {{On the Performance of Image Recovery in Massive MIMO Communications}},
booktitle = {IEEE ICCE 2020: 2020 IEEE EIGHTH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE)},
year = {2021},
pages = {487--491},
publisher = {IEEE},
}
The performance of both primary and secondary networks in underlay cognitive radio networks (CRNs) with the help of incremental amplify and forward (IAF) relaying under imperfect channel state information (CSI) are investigated. Particularly, the interference probability at primary networks denoted by IP as well as the outage probability at secondary networks denoted by OP, are computed in the closed-form expressions. Our findings show that the impact of the imperfect CSI on the performance of IP is non-negligible. To tackle the high value of IP, reducing the transmit power at the secondary transmitters is a proper solution, it, however, will also increase the OP at the secondary networks. Thus, a simple power control coefficient is proposed to compromise the performance between two networks. Finally, Monte-Carlo simulations are provided to verify the accuracy of the proposed mathematical frameworks.
@inproceedings{diva2:1602404,
author = {Lam, Thanh Tu and Phan, Lam Tung and van Chien, Trinh and Tran, Trung Duy and Nguyen, Tien Hoa},
title = {{Performance Evaluation of Incremental Relaying in Underlay Cognitive Radio Networks with Imperfect CSI}},
booktitle = {IEEE ICCE 2020: 2020 IEEE EIGHTH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE)},
year = {2021},
pages = {472--477},
publisher = {IEEE},
}
Federated Learning (FL) is a newly emerged decentralized machine learning (ML) framework that combines on-device local training with server-based model synchronization to train a centralized ML model over distributed nodes. In this paper, we propose an asynchronous FL framework with periodic aggregation to eliminate the straggler issue in FL systems. For the proposed model, we investigate several device scheduling and update aggregation policies and compare their performances when the devices have heterogeneous computation capabilities and training data distributions. From the simulation results, we conclude that the scheduling and aggregation design for asynchronous FL can be rather different from the synchronous case. For example, a norm-based significance-aware scheduling policy might not be efficient in an asynchronous FL setting, and an appropriate "age-aware" weighting design for the model aggregation can greatly improve the learning performance of such systems.
@inproceedings{diva2:1694184,
author = {Hu, Chung-Hsuan and Chen, Zheng and Larsson, Erik G.},
title = {{Device Scheduling and Update Aggregation Policies for Asynchronous Federated Learning}},
booktitle = {2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
year = {2020},
series = {IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
pages = {281--285},
}
In this work, we consider a system where external requests arrive for status updates of a remote source, which is monitored by an energy harvesting (EH) sensor. The requests are placed in an aggregator that has direct communication with the sensor and is also equipped with storage space to cache a previously generated status update. A probabilistic model is considered to determine whether a new request will be served with a fresh update from the EH sensor or with a cached update from the aggregator. In the first case, the fresh update will replace the cached one in the aggregator. Assuming that the energy arrivals at the sensor can be modeled by a Bernoulli process, we characterize the average Age of Information (AoI) of the source seen at the aggregator as a function of the external request probability, the battery charging probability, and the probability that a fresh update will be generated by the EH sensor. Our numerical results reveal some insights about the role of caching in EH-based status updating systems.
@inproceedings{diva2:1616371,
author = {Pappas, Nikolaos and Chen, Zheng and Hatami, Mohammad},
title = {{Average AoI of Cached Status Updates for a Process Monitored by an Energy Harvesting Sensor}},
booktitle = {2020 54TH ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS)},
year = {2020},
pages = {272--276},
publisher = {IEEE},
}
n/a
@inproceedings{diva2:1604228,
author = {Liu, Xiangyu and Xu, Hui and Wang, Yinan and Li, Nan and Johansson, Håkan},
title = {{Correlation-Based Calibration for Nonlinearity Mismatches in Dual-Channel TIADCs}},
booktitle = {2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)},
year = {2020},
series = {IEEE International Symposium on Circuits and Systems},
publisher = {IEEE},
}
In this paper, two first-order compensation strategies for timing mismatch in two-channel time-interleaved analog-to-digital converters (TIADCs) are analyzed, and expressions for the spurious-free dynamic range (SFDR) after compensation are derived. The derived expressions reveal that the strategy where both channels are compensated to match each other, using half the value of the mismatch with different signs, achieves a substantially greater SFDR than the strategy where only one channel is compensated to match the other (reference) channel. This is because, after compensation, the remaining aliasing distortion is shown to be of third order in the former strategy whereas it is of second order in the latter. Simulations included demonstrate the validity of the derived expressions.
@inproceedings{diva2:1600162,
author = {Wang, Yinan and Liu, Xiangyu and Johansson, Håkan and Zhao, Chengxuan and Chen, Kairang and Zhu, Xi},
title = {{On first-order compensation of timing mismatch in two-channel TIADCs}},
booktitle = {2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)},
year = {2020},
series = {IEEE International Symposium on Circuits and Systems},
publisher = {IEEE},
}
In this paper, we investigate the impact of channel aging on the performance of cell-free (CF) massive multiple-input multiple-output (MIMO) systems with pilot contamination. To take into account the channel aging effect due to user mobility, we first compute a channel estimate. We use it to derive novel closed-form expressions for the uplink spectral efficiency (SE) of CF massive MIMO systems with large-scale fading decoding and matched-filter receiver cooperation. The performance of a small-cell system is derived for comparison. It is found that CF massive MIMO systems achieve higher 95%-likely uplink SE in both low-and high-mobility conditions, and CF massive MIMO is more robust to channel aging. Fractional power control (FPC) is considered to compensate to limit the inter-user interference. The results show that, compared with full power transmission, the benefits of FPC are gradually weakened as the channel aging grows stronger.
@inproceedings{diva2:1599452,
author = {Zheng, Jiakang and Zhang, J. and Björnson, Emil and Ai, Bo},
title = {{Cell-Free Massive MIMO with Channel Aging and Pilot Contamination}},
booktitle = {2020 IEEE Global Communications Conference Proceedings},
year = {2020},
series = {IEEE Global Communications Conference (GLOBECOM)},
publisher = {IEEE},
}
Conventionally, a substantial number of reflecting elements (REs) is deployed at the intelligent reflecting surface (IRS) to mitigate the effect of the double-fading attenuation in the IRS-aided link, leading to a large surface size and considerable power consumption. In this paper, a new type of IRS, called active IRS, is proposed to solve this challenge by allowing each RE to amplify the incident signal with the assistance of the active loads (negative resistances). Thus, given a power budget at the IRS, the IRS-aided link can be enhanced by increasing the number of active REs as well as amplifying the incident signal. Specifically, we consider the use of an active IRS-aided single input multiple output (SIMO) system, in which the received signal-to-noise ratio (SNR) is maximized, by optimizing not only the reflecting coefficient matrix at the IRS but also the receive beamforming at the receiver. To solve this non-convex problem, we propose an alternating optimization algorithm, that iteratively optimizes the two design variables. In particular, the receive beamforming is founded to be in the form of a linear minimum mean square error (MMSE) detector, and the reflecting coefficient matrix is obtained via the Charnes-Cooper transformation and the semi-definite programming (SDP). Simulation results show that under a practical power consumption model, the proposed active IRS-aided system achieves better performance over the conventional passive IRS-aided system with the same power budget.
@inproceedings{diva2:1596588,
author = {Long, Ruizhe and Liang, Ying-Chang and Pei, Yiyang and Larsson, Erik G},
title = {{Active Intelligent Reflecting Surface for SIMO Communications}},
booktitle = {GLOBECOM 2020},
year = {2020},
series = {GLOBECOM, IEEE Global Communications Conference},
publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS},
}
This paper studies the uplink spectral efficiency (SE) achieved by two single-antenna user equipments (UEs) communicating with a Large Intelligent Surface (LIS), defined as a planar array consisting of N antennas that each has area A. The analysis is carried out with a deterministic line-of-sight propagation channel model that captures key fundamental aspects of the so-called geometric near-field of the array. Maximum ratio (MR) and minimum mean squared error (MMSE) combining schemes are considered. With both schemes, the signal and interference terms are numerically analyzed as a function of the position of the transmitting devices when the width/height L = root NA of the square-shaped array grows large. The results show that an exact near-field channel model is needed to evaluate the SE whenever the distance of transmitting UEs is comparable with the LIS dimensions. It is shown that, if L grows, the UEs are eventually in the geometric near-field and the interference does not vanish. MMSE outperforms MR for an LIS of practically large size.
@inproceedings{diva2:1591825,
author = {Torres, Andrea de Jesus and Sanguinetti, Luca and Björnson, Emil},
title = {{Near- and Far-Field Communications with Large Intelligent Surfaces}},
booktitle = {2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS},
year = {2020},
series = {Conference Record of the Asilomar Conference on Signals Systems and Computers},
pages = {564--568},
publisher = {IEEE},
}
Intelligent reflecting surfaces (IRSs), consisting of reconfigurable metamaterials, have recently attracted attention as a promising cost-effective technology that can bring new features to wireless communications. These surfaces can be used to partially control the propagation environment and can potentially provide a power gain that is proportional to the square of the number of IRS elements when configured in a proper way. However, the configuration of the local phase matrix at the IRSs can be quite a challenging task since they are purposely designed to not have any active components, therefore, they are not able to process any pilot signal. In addition, a large number of elements at the IRS may create a huge training overhead. In this paper, we present a deep learning (DL) approach for phase reconfiguration at an IRS in order to learn and make use of the local propagation environment. The proposed method uses the received pilot signals reflected through the IRS to train the deep feedforward network. The performance of the proposed approach is evaluated and the numerical results are presented.
@inproceedings{diva2:1591819,
author = {Özdogan, Özgecan and Björnson, Emil},
title = {{Deep Learning-based Phase Reconfiguration for Intelligent Reflecting Surfaces}},
booktitle = {2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS},
year = {2020},
series = {Conference Record of the Asilomar Conference on Signals Systems and Computers},
pages = {707--711},
publisher = {IEEE},
}
In this work, we consider the uplink of a scalable cell-free massive MIMO system where the users are served only by a subset of access points (APs) in the network. The APs are physically grouped into predetermined "cell-centric clusters", which are connected to different cooperative central processing units (CPUs). Given the cooperative nature of the considered communications network, we assume that each user is associated with a "virtual cluster", that, in general, involves some APs belonging to different cell-centric clusters. Assuming the maximum-ratio-combining at the APs, we propose a user-association procedure aimed at the maximization of the sum-rate of the users in the system. The proposed procedure is based on the Hungarian Algorithm and exploits only the knowledge of the position of the APs in the network. Numerical results reveal that the performance of the proposed approach is not always better than the alternatives but it offers a considerably lower backhaul load with a negligible performance loss compared to full-cell free approaches.
@inproceedings{diva2:1591812,
author = {DAndrea, Carmen and Larsson, Erik G},
title = {{User Association in Scalable Cell-Free Massive MIMO Systems}},
booktitle = {2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS},
year = {2020},
series = {Conference Record of the Asilomar Conference on Signals Systems and Computers},
pages = {826--830},
publisher = {IEEE},
}
A potential showstopper for reciprocity-based beamforming is that the uplink SNR often is much smaller than the downlink SNR, making it hard to estimate channels on the uplink. We analyze this problem by considering a "grid-of-beams world" with a finite number of possible channel realizations. We assume that the terminal can accurately detect the channel and we propose a method of improving the channel detection from uplink pilots by designing a mapping between the channel and the pilots. We find a simple metric that is to be minimized to maximize performance. Further, we propose an algorithm that draws pilot sequences from a distribution aimed to minimize the metric. We see that we can come close to optimal performance, which requires long sequences, with significantly shorter sequences.
@inproceedings{diva2:1591810,
author = {Becirovic, Ema and Björnson, Emil and Larsson, Erik G},
title = {{Reciprocity Aided CSI Feedback for Massive MIMO}},
booktitle = {2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS},
year = {2020},
series = {Conference Record of the Asilomar Conference on Signals Systems and Computers},
pages = {1022--1027},
publisher = {IEEE},
}
With the advances in virtual and augmented reality, gaming applications, and entertainment, certain indoor scenarios will require vastly higher capacity than what can be delivered by 5G. In this paper, we focus on massive MIMO for indoor environments. We provide a case study of the distributed deployment of the antenna elements over the walls of a room and not restricting the antenna separation to be half the wavelength. This is a new paradigm of massive MIMO antenna deployment, introduced in [1] under the name RadioWeaves. We investigate different antenna deployment scenarios in line of sight communication. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses caused by grating lobes and thus saves a lot on transmit power. Through simulations, we show that the RadioWeaves technology can provide high rates to multiple users by spending very little power at the transmitter compared to a co-located deployment.
@inproceedings{diva2:1584155,
author = {Kunnath Ganesan, Unnikrishnan and Björnson, Emil and Larsson, Erik G.},
title = {{RadioWeaves for Extreme Spatial Multiplexing in Indoor Environments}},
booktitle = {2020 54th Asilomar Conference on Signals, Systems, and Computers},
year = {2020},
series = {IEEE},
pages = {¨1007--1011},
address = {Pacific Grove, CA, USA},
}
An implementation of activity detection for grant-free massive machine type communication is presented. The implemented algorithm is based on coordinate descent which shows a rapid convergence time. A number of modifications to the original algorithm is proposed to allow efficient implementation in hardware. In addition, the implementation is based on fixed-point representation, and, hence, exhaustive word length simulations have been performed for the different processing steps.
@inproceedings{diva2:1562575,
author = {Henriksson, Mikael and Gustafsson, Oscar and Kunnath Ganesan, Unnikrishnan and Larsson, Erik G.},
title = {{An Architecture for Grant-Free Random Access Massive Machine Type Communication Using Coordinate Descent}},
booktitle = {Proceedings of Fifty-Fourth Asilomar Conference on Signals, Systems and Computers},
year = {2020},
series = {Asilomar Conference on Signals, Systems and Computers},
volume = {54},
pages = {1112--1116},
publisher = {IEEE},
address = {Pacific Grove, CA, USA},
}
Despite the deleterious effect of hardware impairments (HWIs) on wireless systems, most prior works in cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems have not accounted for their impact. In particular, the effect of phase noise (PN) has not been investigated at all in CF systems. Moreover, there is no work investigating HWIs in scalable CF (SCF) mMIMO systems, encountering the prohibitively demanding fronthaul requirements of large networks with many users. Hence, we derive the uplink spectral efficiency (SE) under HWIs with minimum mean-squared error (MMSE) combining in closed-form by means of the deterministic equivalent (DE) analysis. Notably, previous works, accounted for MMSE decoding, studied the corresponding SE only by means of simulations. Numerical results illustrate the performance loss due to HWIs and result in insightful conclusions.
@inproceedings{diva2:1546222,
author = {Papazafeiropoulos, A. K. and Björnson, Emil and Kourtessis, P. and Chatzinotas, S. and Senior, John M.},
title = {{Scalable Cell-Free Massive MIMO Systems With Hardware Impairments}},
booktitle = {2020 IEEE 31ST ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (IEEE PIMRC)},
year = {2020},
series = {IEEE International Symposium on Personal Indoor and Mobile Radio Communications Workshops-PIMRC Workshops},
publisher = {IEEE},
}