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

电信科学 ›› 2019, Vol. 35 ›› Issue (3): 69-75.doi: 10.11959/j.issn.1000-0801.2019048

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

周冬¹,曹海燕¹,许方敏¹,方昕¹,王秀敏²

¹ 杭州电子科技大学，浙江杭州 310018
² 中国计量大学，浙江杭州 310018

修回日期:2019-03-01 出版日期:2019-03-01 发布日期:2019-03-23
作者简介:周冬（1994- ），男，杭州电子科技大学通信工程学院硕士生，主要研究方向为无线通信系统、大规模MIMO系统中的预编码技术。|曹海燕（1975- ），女，博士，杭州电子科技大学通信工程学院副教授，主要研究方向为无线通信系统的信道编码、信号检测和LTE物理层标准等。|许方敏（1980- ），女，杭州电子科技大学通信工程学院讲师，主要研究方向为先进移动通信系统及其关键技术，包括干扰抑制策略和无线资源管理策略。|方昕（1975- ），女，杭州电子科技大学通信工程学院副教授，主要研究方向为4G、5G物理层算法。|王秀敏（1963- ），女，中国计量大学信息工程学院教授，主要研究方向为电路与系统、信号处理。
基金资助:
国家自然科学基金资助项目(61501158);国家自然科学基金资助项目(61379027);浙江省自然科学基金资助项目(LY14F010019);浙江省自然科学基金资助项目(LQ15F01004)

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

Dong ZHOU¹,Haiyan CAO¹,Fangmin XU¹,Xin FANG¹,Xiumin WANG²

¹ Hangzhou Dianzi University,Hangzhou 310018,China
² China Jiliang University,Hangzhou 310018,China

Revised:2019-03-01 Online:2019-03-01 Published:2019-03-23
Supported by:
The National Natural Science Foundation of China(61501158);The National Natural Science Foundation of China(61379027);The Natural Science Foundation of Zhejiang Province of China(LY14F010019);The Natural Science Foundation of Zhejiang Province of China(LQ15F01004)

摘要/Abstract

摘要：

大规模MIMO系统中的传统ZF（zero forcing，迫零）预编码方法中由于存在厄米特矩阵求逆，其复杂度随着用户数的增多呈指数增加。针对这一问题，提出了一种基于权重高斯赛德（weighted Gauss-Seidel， WGS）的低复杂度全数字ZF预编码方案，即在高斯赛德（GS）的基础上，将传统GS算法迭代结果与上一步的迭代结果进行权重相加以加速迭代收敛，其权重因子通过最小均方和来确定，并且证明权重因子可使算法收敛。仿真结果表明，WGS算法通过极少的迭代次数即可逼近ZF 预编码方案的性能，且将ZF预编码的复杂度从O（K³）降低到O（K²），其中，K 为用户数。

关键词: 大规模MIMO, ZF预编码, 权重高斯赛德, 低复杂度

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

中图分类号:

TN929.53

周冬,曹海燕,许方敏,方昕,王秀敏. 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[J]. 电信科学, 2019, 35(3): 69-75.

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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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

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

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

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