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A Novel rzf precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems

IEICE TRANSACTIONS ON COMMUNICATIONS 2016年第2期E99B卷 439-446页

作者： Deng, Qian Guo, Li Lin, Jiaru Liu, Zhihui Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Commun Beijing 100876 Peoples R China Jiangxi Univ Sci & Technol Coll Appl Sci Ganzhou 341000 Peoples R China

In this paper, we propose an efficient regularized zeroforcing (rzf) precoding method that has lower hardware resource requirements and produces a shorter delay to the first transmitted symbol compared with truncated polynomial expansion (TPE) that is based on Neumann series in massive multiple-input multiple-output (MIMO) systems. The proposed precoding scheme, named matrix decomposition-polynomial expansion (MDPE), essentially applies a matrix decomposition algorithm based on polynomial expansion to significantly reduce full matrix multiplication computational complexity. Accordingly, it is suitable for real-time hardware implementations and high-mobility scenarios. Furthermore, the proposed method provides a simple expression that links the optimization coefficients to the ratio of BS/UTs antennas (beta). This approach can speedup the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that theMDPE scheme can rapidly approximate the performance of the full precision rzf and optimal TPE algorithm, while adaptively selecting matrix polynomial terms in accordance with the different a and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.

关键词： massive MIMO matrix decomposition rzf precoding computational complexity power allocation

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Frequency Domain Detection and precoding for Massive MIMO With Single Carrier Modulation

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第5期21卷 3232-3248页

作者： Kenney, Brent A. Majid, Arslan J. Moradi, Hussein Farhang-Boroujeny, Behrouz Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Idaho Natl Lab Idaho Falls ID 83415 USA

Single carrier modulation (SCM) schemes are attractive for uplink (UL) transmissions due to improved power efficiency at the user equipment (UE) transmitter compared with multi-carrier modulation schemes. In a massive MIMO scenario with SCM, the UL detection must mitigate the effects of inter-symbol interference and multi-user interference. This processing is effectively performed in the frequency domain (FD) using a minimum mean squared error (MMSE) detector when the transmission is framed with a cyclic prefix. This paper analyzes an MMSE-based detector compatible with distributed processing in a time-division duplex (TDD) system. The matrix inverses computed for the UL detection are then reused to perform multi-user precoding for the downlink (DL). We find that this scheme yields tremendous savings in computational complexity compared to commonly used zero-forcing (ZF) precoding without sacrificing any performance. Since MMSE processing introduces a bias to the estimates, we derive the scalar coefficients necessary to cancel the MMSE bias. The impact of channel estimation errors is analyzed for both the UL and DL cases in conjunction with a power-efficient approach to SCM channel estimation. Moreover, extensive simulations are performed to confirm our theoretical findings.

关键词： precoding Massive MIMO Detectors Channel estimation OFDM Antennas Signal to noise ratio Single carrier modulation massive MIMO frequency domain processing MMSE detection rzf precoding

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A Low-Complexity Massive MIMO precoding Algorithm Based on Chebyshev Iteration

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IEEE ACCESS 2017年 5卷 22545-22551页

作者： Zhang, Chi Li, Zhengquan Shen, Lianfeng Yan, Feng Wu, Ming Wang, Xiumin Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Jiliang Univ Coll Informat Engn Hangzhou 310018 Zhejiang Peoples R China

precoding algorithm is used to transmit signals effectively and to reduce the interferences from other user terminals in the massive multiple-input multiple-output (MIMO) systems. In order to decrease the computational complexity of the precoding matrix, this paper proposes a new precoding algorithm. We use Chebyshev iteration to estimate the matrix inversion in the regularized zero-forcing precoding (rzf) algorithm. It does not need to compute the matrix inversion directly but uses iterations to estimate the matrix inversion. Therefore, the computational complexity can be decreased in this way. Furthermore, Chebyshev iteration has lower convergence rate, and it can gain precoding matrix quickly. This paper analyzes the performance of the Chebyshev-rzf precoding algorithm using average achievable rate and computes the complexity of the algorithm. Then, this paper optimizes initial values of the Chebyshev iteration algorithm on the basis of the feature of massive MIMO systems and makes initial values easier to be obtained. Simulation results show that after two iterations, the Chebyshev-rzf precoding algorithm can get similar average achievable rate as the rzf precoding algorithm does. An optimized Chebyshev-rzf precoding algorithm gets similar performance to the Chebyshev-rzf precoding algorithm after one iteration.

关键词： rzf precoding Chebyshev iteration Newton iteration massive MIMO

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On the Downlink Average Energy Efficiency of Non-Stationary XL-MIMO

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IEEE TRANSACTIONS ON COMMUNICATIONS 2024年第11期72卷 7294-7307页

作者： Zhang, Jun Lu, Jiacheng Zhang, Jingjing Han, Yu Wang, Jue Jin, Shi Nanjing Univ Posts & Telecommun Jiangsu Key Lab Wireless Commun Nanjing 210003 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210003 Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong 226019 Peoples R China

Extra large-scale multiple-input multiple-output (XL-MIMO) is a key technology for future wireless communication systems. This paper considers the effects of visibility region (VR) at the base station (BS) in a non-stationary multi-user XL-MIMO scenario, where only partial antennas can receive users' signal. In time division duplexing (TDD) mode, we first estimate the VR at the BS by detecting the energy of the received signal during uplink training phase. The probabilities of two detection errors are derived and the uplink channel on the detected VR is estimated. In downlink data transmission, to avoid cumbersome Monte-Carlo trials, we derive a deterministic approximate expression for ergodic average energy efficiency (EE) with the regularized zero-forcing (rzf) precoding. In frequency division duplexing (FDD) mode, the VR is estimated in uplink training and then the channel information of detected VR is acquired from the feedback channel. In downlink data transmission, the approximation of ergodic average EE is also derived with the rzf precoding. Invoking approximate results, we propose an alternate optimization algorithm to design the detection threshold and the pilot length in both TDD and FDD modes. The numerical results reveal the impacts of VR estimation error on ergodic average EE and demonstrate the effectiveness of our proposed algorithm.

关键词： Uplink Channel estimation precoding Antenna arrays Downlink Training MIMO communication Extra large-scale MIMO visibility region rzf precoding average energy efficiency

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Secrecy Rate Analysis for RIS-Aided Multi-User MISO System over Rician Fading Channel

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Journal of Communications and Information Networks 2023年第1期8卷 48-56页

作者： Jiaping Wang Jun Zhang Jiacheng Lu Jue Wang Qi Zhang Dongqian Wang School of Communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210000China School of Information Science and Technology Nantong UniversityNantong 226019China.

The reconfigurable intelligent surface(RIS),which is composed of multiple passive reflective components,is now considered as an effective mean to improve security performance in wireless communications,as it can enhance the signal of legitimate users and suppress the power leakage at eavesdroppers by adjusting signal *** this paper,we maximize the downlink ergodic secrecy sum rate of a RIS-aided multi-user system over Rician fading channels,where we assume that only imperfect channel state information(CSI)is available at the base station(BS).Firstly,we obtain the deterministic approximate expression for the ergodic secrecy sum rate by resorting to the large-system approximation *** the problem is formulated to maximize the downlink ergodic secrecy sum rate by optimizing the regularization coefficient of regularized zero-forcing(rzf)precoding and the phase-shifting matrix of the *** using the particle swarm optimization(PSO)method,we propose an alternate optimization(AO)algorithm to solve this non-convex ***,the numerical simulations illustrate the accuracy of our large-system approximate expression as well as the effectiveness of the proposed algorithm.

关键词： RIS large-system approximation rzf precoding imperfect CSI ergodic secrecy sum rate

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Joint Detection Method for Non-orthogonal Multiple Access System Based on Linear precoding and Serial Interference Cancellation

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JOURNAL OF INFORMATION PROCESSING SYSTEMS 2021年第5期17卷 933-946页

作者： Li, Jianpo Wang, Qiwei Northeast Elect Power Univ Sch Comp Sci Jilin Jilin Peoples R China

In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (rzf) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses rzf precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-tointerference and noise ratio (SINR).

关键词： Joint Detection Algorithm NOMA rzf precoding Serial Interference Cancellation

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Low-Complexity Linear precoding for Pilot Contamination Mitigation in Multi-Cell Massive MIMO Systems 25

Low-Complexity Linear Precoding for Pilot Contamination Miti...

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International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Feng, Manman Xu, Yaohua Minist Educ Key Lab Intelligent Comp & Signal Proc Beijing Peoples R China Anhui Univ Sch Elect & Informat Engn Hefei Anhui Peoples R China

ISBN: (纸本)9781538621592

The pilot contamination is caused by non-orthogonal pilot sequences reuse in uplink, which affects the performance of Massive MEMO systems seriously, so it is necessary to mitigate pilot contamination. In this paper, we propose a pilot contamination precoding scheme to mitigate multi-cell pilot contamination. In the uplink, we propose a cell-defined training scheme, where the same pilot sequence is used in the same cell, and different cells use orthogonal pilot sequences, which eliminates inter-cell interference and introduces intra-cell interference artificially. In the downlink, we adopt Truncated Polynomial Expansion (TPE) precoding to reduce intra-cell interference, since the truncated polynomial of TPE precoding can replace the matrix inversion of Regularized Zero-Forcing (rzf) precoding, which reduces the complexity of rzf precoding and approximates the performance of rzf precoding by suitable truncation orders. Simulation results show the effectiveness of the proposed scheme.

关键词： Massive MIMO Pilot contamination precoding scheme rzf precoding TPE precoding

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Linear precoding for Downlink Massive MIMO with Delayed CSIT and Channel Prediction

Linear Precoding for Downlink Massive MIMO with Delayed CSIT...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Papazafeiropoulos, Anastasios Ratnarajah, Tharmalingam Univ Edinburgh Inst Digital Commun IDCoM Edinburgh EH9 3JL Midlothian Scotland

ISBN: (纸本)9781479930838

We consider a multi-cell multi-user downlink channel of a time-division duplex (TDD) MIMO system, where the base stations (BSs) employ the concept of massive MIMO, i.e., they are equipped with a large number of antennas. In addition, the number of users increases with the same speed. Focusing on the practical impairments of the channel such as pilot contamination and, in particular, delayed channel state information at the transmitter (CSIT), we derive an approximation of the sum rate with regularized zero-forcing (rzf) precoding, which provides a quantification of the capacity loss. As a result, it is deemed necessary to obtain the deterministic equivalent sum rate by incorporating in our analysis channel prediction circumventing the degradation due to delayed CSIT. The proposed results are accurate for realistic system dimensions, as simulations testify. Finally, we show the benefits of applying rzf in the sum rate against using eigenbeamforming (BF) for the same Doppler shift with no extra computational complexity.

关键词： Doppler shift MIMO communication antennas array signal processing losses precoding prediction theory telecommunication channels time division multiplexing BF BS CSIT rzf precoding TDD MIMO system base stations capacity loss quantification computational complexity delayed CSIT delayed channel state information at the transmitter deterministic equivalent sum rate approximation downlink massive MIMO eigenbeamforming linear precoding multicell multiuser downlink channel prediction pilot contamination practical impairments realistic system dimensions regularized zero-forcing precoding time-division duplex MIMO system Antennas Channel estimation Contamination Correlation Downlink Interference Signal to noise ratio

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