大规模MIMO系统中基于牛顿迭代和超松弛迭代的WWSE预编码算法

doi:10.11959/j.issn.1000-0801.2019278

Abstract

Abstract:

In massive MIMO system,Newton iteration algorithm was applied to the traditional minimum mean-square error (WWSE) precoding algorithm to calculate the inverse operation,but the initial value of iteration was complicated.Aiming at this problem,WWSESOR-NT algorithm was proposed.The intermediate algorithm based on the SOR iterative algorithm was proposed.Then combined with Newton iteration algorithm,the intermediate algorithm was used to directly estimate the inverse of higher-order matrix,and the result was taken as the initial value of Newton iteration algorithm to accelerate the convergence speed.The simulation results show that WWSESOR-NT algorithm can approximate the performance of WWSE algorithm with fewer iterations and approximately the same complexity.

Key words: massive MIMO, MMSE precoding, SOR iteration, Newton iteration

CLC Number:

TN929.53

Wensheng SUN,Junjie XU. Newton iteration and SOR iteration based WWSE precoding algorithm in massive MIMO systems[J]. Telecommunications Science, 2019, 35(11): 51-57.

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References 16

[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. doi: 10.1109/TCOMM.2013.020413.110848
[2]	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.
[3]	COSTA M H M . Writing on dirty paper[J]. IEEE Transactions on Information Theory, 1983,29(3): 439-441. doi: 10.1109/TIT.1983.1056659
[4]	NARSINMHAN T L ， CHOCKALINGA-M A . Channel hardening-exploiting message passing(CHEMP) receiver in large-scale MIMO systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2014,8(5): 847-860. doi: 10.1109/JSTSP.2014.2314213
[5]	LU Z , NING J , ZHANG Y ,et al. Richards-on method based linear precoding with low complexity for massive MIMO system[C]// IEEE Vehicular Technology Conference,May 11-14,2015,Glasgow,UK. Piscataway:IEEE Press, 2015: 1-4.
[6]	SONG W , CHEN X , WANG L ,et al. Joint conjugate gradient and Jacobi based low complexity precoding for massive MIMO systems[C]// IEEE/CIC International Conference on Communications in China,July 27-29,2016,Chengdu,China. Piscataway:IEEE Press, 2016: 1-5.
[7]	GAO X Y , DAI L L , HU Y T ,et al. Matrix inversion-less signal detection using SOR method for uplink large-scale MIMO systems[C]// IEEE Global Communications Conference,December 8-12,2015,Austin,TX,USA. Piscataway:IEEE Press, 2015: 3291-3295.
[8]	GAO X , DAI L , ZHANG J ,et al. Capacity-approaching linear precoding with low-complexity for large-scale MIMO systems[C]// 2015 IEEE International Conference on Communications,June 8-12,2015,London,UK. Piscataway:IEEE Press, 2015: 1577-1582.
[9]	LI T , PATOLE S , TORLAK M . A multistage linear receiver approach for MMSE detection in massive MIMO[C]// Asilomar Conference on Signals,Systems and Computers,November 2-5,2014,Pacific Grove,CA,USA. Piscataway:IEEE Press, 2014: 2067-2072.
[10]	ZHU Q H , SONG Z P , WU J Q . A low-complexity RZF-SOR precoding algorithm for massive MIMO systems[J]. Telecommunication Engineering, 2017,57(12): 1427-1432.
[11]	ZHOU D , CAO H Y , XU F M ,et al. A low complexity ZF precoding scheme based on weighted Gauss-Seidel in massive MIMO systems[J]. Telecommunication Science, 2019,35(3): 69-75.
[12]	ROSARIO F , MONTEIRO F A , RODRIGUES A . Fast matrix inversion updates for massive MIMO detection and precoding[J]. IEES Signal Processing Letters, 2016,23(1): 75-79.
[13]	BJORCK A . Numerical methods in matrix computations[M]. Berlin: Springer International PublishingPress, 2015.
[14]	ZHANG Y N , MA W M , CAI B H . From Zhang neural network to Newton iteration for matrix inversion[J]. IEEE Transactions on Circuits and Systems I:Regular Papers, 2009,56(7): 1405-1415. doi: 10.1109/TNNLS.2014.2342260 pmid: 25122845
[15]	AJOSE S O , IMOIZE A L , BAKARE R A ,et al. BER comparison of different modulation schemes over AWGN and Rayleigh fading channels for MIMO-OFDM system[J]. International Journal of Communication Networks ＆ Distributed Systems, 2017,18(2):129.
[16]	TANG C , LIU C , YUAN L C ,et al. High precision low complexity matrix inversion based on Newton iteration for data detection in the massive MIMO[J]. IEEE Communications Letters, 2016,20(3): 490-493. doi: 10.1109/LCOMM.2015.2514281

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