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

孙文胜; 许俊杰

doi:10.11959/j.issn.1000-0801.2019278

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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

研究与开发 | 更新时间：2024-06-05

- 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
- Newton iteration and SOR iteration based WWSE precoding algorithm in massive MIMO systems
- 电信科学 2019年35卷第11期页码：51-57
- 作者机构：
- 作者简介：
  
  [ "孙文胜（1966- ），男，杭州电子科技大学通信工程学院副教授，主要研究方向为网络通信、无线通信等" ]
  [ "许俊杰（1995- ），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、大规模MIMO系统中的预编码算法" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2019278
  中图分类号： TN929.53
- 网络出版日期：2019-11，
  
  纸质出版日期：2019-11-20
- 稿件说明：
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孙文胜, 许俊杰. 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[J]. 电信科学, 2019,35(11):51-57.

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.
孙文胜, 许俊杰. 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[J]. 电信科学, 2019,35(11):51-57. DOI： 10.11959/j.issn.1000-0801.2019278.

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. DOI： 10.11959/j.issn.1000-0801.2019278.

摘要

在大规模 MIMO 系统中，将牛顿迭代法用于传统的 WWSE 预编码算法求逆运算，但是其迭代初始值计算复杂。针对这一问题，提出WWSESOR-NT算法。在SOR算法的基础上提出中间算法，然后与牛顿迭代算法相结合，利用中间算法直接对高阶矩阵的逆进行估算，将得到的结果作为牛顿迭代法的迭代初始值以加快收敛速度。仿真结果显示，与传统牛顿迭代法比较，WWSESOR-NT 算法能够以更少的迭代次数和近似相同的复杂度逼近WWSE算法的性能。

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.

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references

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