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Investigation on Key Technologies in Large-Scale MIMO

Journal of Computer Science & Technology 2013年第3期28卷 412-419页

作者：粟欣曾捷容丽萍邝育军 Tsinghua National Laboratory for Information Science and Technology Tsinghua University College of Communication and Information Engineering University of Electronic Science and Technology of China

Large-scale MIMO （multiple-input multiple-output） systems with numerous low-power antennas can provide better performance in terms of spectrum efficiency, power saving and link reliability than conventional MIMO. For large-scale MIMO, there are several technical issues that need to be practically addressed （e.g., pilot pattern design and low-power transmission design） and theoretically addressed （e.g., capacity bound, channel estimation, and power allocation strategies）. In this paper, we analyze the sum rate upper bound of large-scale MIMO, investigate its key technologies including channel estimation, downlink precoding, and uplink detection. We also present some perspectives concerning new channel modeling approaches, advanced user scheduling algorithms, etc.

关键词： large-scale multiple-input multiple-output channel estimation downlink precoding uplink detection

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On Countermeasures of Pilot Spoofing Attack in Massive MIMO Systems: A Double Channel Training Based Approach

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第7期68卷 6697-6708页

作者： Wang, Wei Cheng, Nan Teh, Kah Chan Lin, Xiaodong Zhuang, Weihua Shen, Xuemin Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Univ Guelph Sch Comp Sci Guelph ON N1G 2W1 Canada

In this paper, we investigate secure communication in a massive multiple-input multiple-output (MIMO) system with multiple users and multiple eavesdroppers (Eve) under both pilot spoofing attack (PSA) and uplink jamming. Specifically, Eve impairs the normal channel estimation by sending identical pilot sequences with the legitimate users. Based on the impaired channel estimation, the base station adopts linear processing schemes for uplink data reception, which is jammed by Eve, and downlink confidential information transmission. We first evaluate the impact of the PSA on the achievable rate with linear processing, and then propose a double channel training based scheme to combat PSA. By using the channel estimation difference in two training phases, the presence of the PSA can be detected and accurate legitimate channel estimation can be obtained by removing the effect of Eve's channel. Furthermore, we analyze the channel estimation errors and derive a closed-form expression of the minimum mean square error precoding scheme to maximize the minimum achievable secrecy rate, which outperforms the conventional linear precoding counterparts.

关键词： Massive MIMO pilot spoofing attack double channel training downlink precoding secrecy rate

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Construction of 1-Bit Transmit Signal Vectors for downlink MU-MISO Systems: QAM Constellations

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2021年第10期70卷 10065-10076页

作者： Park, Sungyeal Cho, Yunseong Hong, Songnam Ajou Univ Artificial Intelligence Convergence Network Suwon 16499 South Korea Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA Hanyang Univ Dept Elect Engn Seoul 04763 South Korea

In this paper, we investigate the construction of a transmit signal for downlink multiuser multiple-input single-output (MU-MISO) systems under the cost-effective 1-bit digital-to-analog converters (DACs). Due to the coarse nonliner property, conventional precoding methods, developed under infinite-resolution DACs, could not yield an attractive performance having a severe error-floor. Finding an optimal transmit signal, moreover, is computationally implausible due to its combinatorial nature. This challenging problem has been partially solved in our earlier work focusing on phase-shift-keying constellations. Our major contribution is to extend it into more practical quadrature-amplitude-modulation constellations in a non-trivial way. We first derive the so-called feasibility condition to guarantee that every user's noiseless received signal belongs to a desired decision region, and then transform it as linear constraints. Taking the robustness to an additive noise into account, the proposed construction method is formulated as a mixed integer linear programming problem. We construct an efficient algorithm to solve it (equivalently, to generate an 1-bit transmit signal). Via simulation results, we demonstrate the superiority of the proposed method with respect to a computational complexity and detection performance.

关键词： precoding Quadrature amplitude modulation downlink Phase shift keying MISO communication Computational complexity Power demand 1-bit DAC downlink precoding linear programming massive MISO

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Widely Linear precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2017年第5期16卷 3298-3312页

作者： Zhang, Wence de lamare, Rodrigo C. Pan, Cunhua Chen, Ming Dai, Jianxin Wu, Bingyang Bao, Xu Jiangsu Univ Zhenjiang 212013 Peoples R China Pontificia Univ Catolica Rio de Janeiro CETUC BR-22451900 Rio de Janeiro Brazil Univ York York YO10 5DD N Yorkshire England Queen Mary Univ London Sch Elect Engn & Comp Sci London England Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Sch Sci Nanjing 210003 Peoples R China

In this paper, we study widely linear precoding techniques to mitigate in-phase/quadrature-phase (IQ) imbalance (IQI) in the downlink of large-scale multiple-input multiple-output (MIMO) systems. We adopt a real-valued signal model, which considers the IQI at the transmitter, and then develop widely linear zero-forcing (WL-ZF), widely linear matched filter, widely linear minimum mean-squared error, and widely linear block-diagonalization (WL-BD) type precoding algorithms for both single-and multiple-antenna users. We also present a performance analysis of WL-ZF and WL-BD. It is proved that without IQI, WL-ZF has exactly the same multiplexing gain and power offset as ZF, while when IQI exists, WL-ZF achieves the same multiplexing gain as ZF with ideal IQ branches, but with a minor power loss, which is related to the system scale and the IQ parameters. We also compare the performance of WL-BD with BD. The analysis shows that with ideal IQ branches, WL-BD has the same data rate as BD, while when IQI exists, WL-BD achieves the same multiplexing gain as BD without IQ imbalance. Numerical results verify the analysis and show that the proposed widely linear type precoding methods significantly outperform their conventional counterparts with IQI and approach those with ideal IQ branches.

关键词： IQ imbalance large-scale MIMO widely-linear signal processing downlink precoding

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Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2023年 71卷 433-446页

作者： Zhao, Xiaotong Lu, Siyuan Shi, Qingjiang Luo, Zhi-Quan Tongji Univ Sch Software Engn Shanghai 201804 Peoples R China Huawei Technol Shanghai 201206 Peoples R China Shenzhen Res Inst Big Data Shenzhen 518172 Peoples R China Chinese Univ Hong Kong Shenzhen 518172 Peoples R China

precoding design for maximizing weighted sum-rate (WSR) is a fundamental problem for downlink of massive multi-user multiple-input multiple-output (MU-MIMO) systems. It is well-known that this problem is generally NP-hard due to the presence of multi-user interference. The weighted minimum mean-square error (WMMSE) algorithm is a popular approach for WSR maximization. However, its computational complexity is cubic in the number of base station (BS) antennas, which is unaffordable when the BS is equipped with a large antenna array. In this paper, we consider the WSR maximization problem with either a sum-power constraint (SPC) or per-antenna power constraints (PAPCs). For the former, we prove that any nontrivial stationary point must have a low-dimensional subspace structure, and then propose a reduced-WMMSE (R-WMMSE) with linear complexity by exploiting the solution structure. For the latter, we propose a linear-complexity WMMSE approach, named PAPC-WMMSE, by using a novel recursive design of the algorithm. Both R-WMMSE and PAPC-WMMSE have simple closed-form updates and guaranteed convergence to stationary points. Simulation results verify the efficacy of the proposed designs, especially the much lower complexity as compared to the state-of-the-art approaches for massive MU-MIMO systems.

关键词： Antennas Signal processing algorithms precoding Optimization Convergence Computational complexity Antenna arrays Massive MU-MIMO downlink precoding weighted MMSE linear complexity sum power constraint per-antenna power constraints

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Deep Learning for Distributed Channel Feedback and Multiuser precoding in FDD Massive MIMO

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2021年第7期20卷 4044-4057页

作者： Sohrabi, Foad Attiah, Kareem M. Yu, Wei Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequency-division duplex massive multiple-input multiple-output system in which a base station (BS) serves multiple mobile users, but with rate-limited feedback from the users to the BS. A key observation is that the multiuser channel estimation and feedback problem can be thought of as a distributed source coding problem. In contrast to the traditional approach where the channel state information (CSI) is estimated and quantized at each user independently, this paper shows that a joint design of pilots and a new DNN architecture, which maps the received pilots directly into feedback bits at the user side then maps the feedback bits from all the users directly into the precoding matrix at the BS, can significantly improve the overall performance. This paper further proposes robust design strategies with respect to channel parameters and also a generalizable DNN architecture for varying number of users and number of feedback bits. Numerical results show that the DNN-based approach with short pilot sequences and very limited feedback overhead can already approach the performance of conventional linear precoding schemes with full CSI.

关键词： precoding Channel estimation downlink Training Quantization (signal) Estimation Deep learning Channel estimation deep neural network (DNN) distributed source coding (DSC) downlink precoding feedback frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) quantization

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Pilot Decontamination Processing in Cell-Free Massive MIMO

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IEEE COMMUNICATIONS LETTERS 2021年第12期25卷 3990-3994页

作者： Alvarez Polegre, Alberto Sanguinetti, Luca Garcia Armada, Ana Univ Carlos III Madrid Dept Signal Theory & Commun Madrid 28911 Leganes Spain Univ Pisa Dipartimento Ingn Informaz I-65122 Pisa Italy

This letter focuses on the pilot contamination problem in the uplink and downlink of cell-free massive multiple-input multiple-output networks with different degrees of cooperation between access points. The optimum minimum mean square error processing can take advantage of large-scale fading coefficients for canceling the interference of pilot-sharing user-equipments and thus achieves asymptotically unbounded capacity. However, it is computationally demanding and can only be implemented in a fully centralized network. Here, sub-optimal schemes are derived that provide unbounded capacity with linear-growing complexity and using only local channel estimates but global channel statistics. This makes them suited for both centralized and distributed networks. In this latter case, the best performance is achieved with a generalized maximum ratio combiner that maximizes a capacity bound based on channel statistics only.

关键词： Channel estimation Interference Contamination Signal to noise ratio Covariance matrices Uplink Complexity theory Cell-free massive MIMO pilot contamination uplink combining downlink precoding reduced-complexity minimum mean square error generalized maximum ratio

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A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing

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IEEE WIRELESS COMMUNICATIONS LETTERS 2024年第5期13卷 1225-1229页

作者： Winter, Samuel Zhang, Yangyishi Zheng, Gan Hanzo, Lajos BT Grp Res & Network Strategies Ipswich IP5 3RE England Univ Warwick Sch Engn Coventry CV4 7AL England Univ Southampton ECS Dept Southampton SO17 1BJ England

Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.

关键词： Lattices Hardware Annealing Symbols Qubit Perturbation methods Quantum annealing downlink precoding vector perturbation MIMO

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Linear CE and 1-bit Quantized precoding With Optimized Dithering

IEEE OPEN JOURNAL OF SIGNAL PROCESSING

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IEEE OPEN JOURNAL OF SIGNAL PROCESSING 2020年 1卷 310-325页

作者： Saxena, Amodh Kant Mezghani, Amine Heath, Robert W. Univ Texas Austin Wireless Networking & Commun Grp Austin TX 78712 USA Univ Manitoba Dept ECE Winnipeg MB R3T 5V6 Canada N Carolina State Univ Dept ECE Raleigh NC 27606 USA Univ Texas Austin Austin TX 78712 USA

High power amplifiers (HPA), used at transmission, add nonlinear impairments to the output signals. Through Constant envelope (CE) transmission, distortion in the signal can be avoided without wasting power on PA linearization. A more restricted form of CE transmission, 1-bit quantized transmission, further simplifies the RF chain and reduces the DAC power consumption. In this paper, for CE transmission and 1-bit quantized transmission at the BS antennas, we analyze downlink transmission for low complexity linear precoding. We observe that for small numbers of users in the downlink, correlation among the quantization error components across BS antennas is high, deteriorating the performance rapidly as number of users become smaller. To improve performance for smaller numbers of downlink users, we propose the addition of correlated Gaussian dither to the precoded signal before quantization and subsequent transmission. We observe that the receive SQINR peaks for finite non-trivial dither power. For given value of transmit power, number of BS antennas and number of users, SQINR is maximized analytically by the transmitter, to find the optimum dither power, using the Bussgang decomposition. We observe that with the implementation of optimized dithering, the error floor in the coded BER at high transmit power, for CE and 1-bit quantized transmissions, is pushed down significantly. We also observe that optimum dither power increases monotonically with transmit power, with rate of increase decreasing with increasing transmit power. Further, the optimum dither power strictly increases with number of BS antennas.

关键词： 1-bit quantized transmission massive MIMO downlink precoding constant envelope transmission 1-bit DACs Bussgang decomposition

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Low Complexity Precoder with Exploration for 1-bit MU-MISO: QAM constellations 25

Low Complexity Precoder with Exploration for 1-bit MU-MISO: ...

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25th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Hong, Sungweon Park, Sungyeal Cho, Yunseong Hong, Songnam Hanyang Univ Elect Engn Seoul South Korea Hyundai Motors Co Hwaseong South Korea Samsung Res Amer Plano TX 75024 USA

ISBN: (纸本)9798350393194;9798350393187

We study the construction of a transmit signal for downlink multi-user multiple-input single-output (MU-MISO) systems with cost-effective 1-bit digital-to-analog converters (DACs). In our earlier work, this challenging problem was formulated as a mixed integer linear programming (MILP) and solved through conventional LP relaxation. In this paper, we present a two-step iterative algorithm with an elegant performance-complexity tradeoff. The proposed algorithm can approach the performance of the LP-based method while reducing the computational complexity by 1/ log(N-t), where N-t is the number of transmit antennas. Via simulations, we demonstrate the effectiveness of the proposed algorithm.

关键词： 1-bit DAC downlink precoding mixed integer linear programming massive MISO

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