大规模MIMO系统中基于权重高斯赛德低复杂度ZF预编码方案

doi:10.11959/j.issn.1000-0801.2019048

Abstract

Abstract:

In massive MIMO systems,due to inversion of Hermitian matrix,the complexity of the traditional ZF precoding method increases exponentially with increase of the number of users.To solve this problem,a low complexity digital ZF precoding scheme based on weighted Gauss-Seidel (WGS) was proposed.That was weighted addtion the iteration results of previous step and Gausee-Seidel iteration results to accelerate the iterative convergence.The weighting factor was determined by the least mean square sum,and the weighting factor was proved to make the algorithm converge.The simulation results show that the WGS algorithm can approximate the performance of ZF precoding scheme with very few iterations,and reduce the complexity of ZF precoding from O(K ³) to O(K²),where K is the number of users.

Key words: massive MIMO, ZF precoding, weighted Gauss-Seidel, low complexity

CLC Number:

TN929.53

Dong ZHOU,Haiyan CAO,Fangmin XU,Xin FANG,Xiumin WANG. A low complexity ZF precoding scheme based on weighted Gauss-Seidel in massive MIMO systems[J]. Telecommunications Science, 2019, 35(3): 69-75.

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References 18

[1]	NGO H Q , LARSSON E G , MARZETTA T L ,et al. Energy and spectral efficiency of very large multiuser MIMO systems[J]. IEEE Transactions on Communications, 2013,61(4): 1436-1449.
[2]	LIU Z , DU W , SUN D ,et al. Energy and spectral efficiency tradeoff for massive MIMO systems with transmit antenna selection[J]. IEEE Transactions on Vehicular Technology, 2017,66(5): 4453-4457.
[3]	曹海燕, 冯瑞瑞, 方昕 ,等. 大规模 MIMO 系统中基于能效最大化的资源联合优化算法[J]. 电信科学, 2017,33(12): 84-90.
	CAO H Y , FENG R R , FANG X ,et al. A joint optimization algorithm based on energy efficiency maximization for massive MIMO systems[J]. Telecommunications Science, 2017,33(12): 84-90.
[4]	PRASAD K N R S V , HOSSAIN E , and BHARGAVA V K ,et al. Energy efficiency in massive MIMO-based 5G networks:opportunities and challenges[J]. IEEE Wireless Communications, 2017,24(3): 86-94.
[5]	BOGALE T E , LE L B . Massive MIMO and mmWave for 5G wireless HetNet:potential benefits and challenges[J]. IEEE Vehicular Technology Magazine, 2016,11(1): 64-75.
[6]	COSTA M H M . Writing on dirty paper (Corresp)[J]. IEEE Transactions on Information Theory, 1983,29(3): 439-441.
[7]	LU Z , NING J , ZHANG Y ,et al. Richardson method based linear precoding with low complexity for massive MIMO systems[C]// IEEE Vehicular Technology Conference,September 6-9,2015,Boston,USA. Piscataway:IEEE Press, 2015: 1-4.
[8]	SONG W , CHEN X , WANG L ,et al. Joint conjugate gradient and Jacobi iteration based low complexity precoding for massive MIMO systems[C]// IEEE/CIC International Conference on Communications,July 27-29,2016,Chengdu,China. Piscataway:IEEE Press, 2016: 1-5.
[9]	XIE T , LU Z , HAN Q ,et al. Low-complexity LSQR-based linear precoding for massive MIMO systems[C]// IEEE Vehicular Technology Conference,September 6-9,2015,Boston,USA. Piscataway:IEEE Press, 2015: 1-5.
[10]	XIE T , DAI L , GAO X ,et al. Low-complexity SSOR-based precoding for massive MIMO systems[J]. IEEE Communications Letters, 2016,20(4): 744-747.
[11]	KAMMOUN A , MULLER A , BJORNAON E ,et al. Linear precoding based on polynomial expansion:large-scale multi-cell MIMO systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2014,8(5): 861-875.
[12]	PRABHU H , RODRIGUES J , EDFORS O ,et al. Approximative matrix inverse computations for very-large MIMO and applications to linear precoding systems[C]// Wireless Communications and Networking Conference,April 7-10,2013,Shanghai,China. Piscataway:IEEE Press, 2013: 2710-2715.
[13]	GAO X , DAI L , ZHANG J ,et al. Capacity-approaching linear precoding with low-complexity for large-scale MIMO systems[C]// IEEE International Conference on Communications,June 8-15,2015,London,UK. Piscataway:IEEE Press, 2015: 1577-1582.
[14]	MINANGO J , ALMEIDA C D . Low-complexity MMSE detector based on the first-order Neumann series expansion for massive MIMO systems[C]// IEEE 9th Latin-American Conference on Communications,November 8-10,2017,Guatemala City,Guatemala. Piscataway:IEEE Press, 2017: 1-5.
[15]	FLORDELIS J , RUSEK F , TUFVESSON F ,et al. Massive MIMO performance-TDD versus FDD:what do measurements say?[J]. IEEE Transactions on Wireless Communications, 2017(99):1.
[16]	MI D , DIANATI M , ZHANG L ,et al. Massive MIMO performance with imperfect channel reciprocity and channel estimation error[J]. IEEE Transactions on Communications, 2017(99): 1-1.
[17]	TULINO A M , VERDU S . Random matrix theory and wireless communications[J]. Communications ＆ Information Theory, 2004,1(1): 1-182.
[18]	BJ?RCK ? . Numerical methods in matrix computations[M]. Heidelburg: SpringerPress, 2015.

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迭代次数	RM	GS	WGS
i= 2	2(4K ²+8K)	8K ²+4K	2(4K ²+8K)+4K
i=3	3(4K ²+8K)	12K ²+4K	3(4K ²+8K)+4K
i=4	4(4K ²+8K)	16K ²+4K	4(4K ²+8K)+4K
i=5	5(4K ²+8K)	20K ²+4K	5(4K ²+8K)+4K

A low complexity ZF precoding scheme based on weighted Gauss-Seidel in massive MIMO systems

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