大规模MIMO系统混合线性迭代信号检测算法

张晓华; 彭小; 黄龙

doi:10.13756/j.gtxyj.2022.02.012

您当前的位置：

首页 >

文章列表页 >

大规模MIMO系统混合线性迭代信号检测算法

无线通信技术 | 更新时间：2022-06-15

- 大规模MIMO系统混合线性迭代信号检测算法
- Hybrid Linear Iterative Signal Detection Algorithm for Massive MIMO Systems
- 光通信研究 2022年第2期页码：56-60
- 作者机构：
  
  重庆市信息通信咨询设计院有限公司，重庆　400041
- 作者简介：
  
  张晓华(1980-)，男，重庆人。高级工程师，硕士，主要研究方向为移动通信。
  彭小，高级工程师。E-mail：18908371112@189.cn
- 基金信息：
  
  2019年重庆市技术创新与应用发展专项资助项目(cstc2019jscx-zdztzxX0002)
- DOI：10.13756/j.gtxyj.2022.02.012
  中图分类号： TN929.5
- 纸质出版日期：2022-04-10，
  
  收稿日期：2021-07-01，
扫描看全文
张晓华, 彭小, 黄龙. 大规模MIMO系统混合线性迭代信号检测算法[J]. 光通信研究, 2022,(2):56-60.

ZHANG Xiao-hua, PENG Xiao, HUANG Long. Hybrid Linear Iterative Signal Detection Algorithm for Massive MIMO Systems[J]. Study on Optical Communications, 2022,(2):56-60.
张晓华, 彭小, 黄龙. 大规模MIMO系统混合线性迭代信号检测算法[J]. 光通信研究, 2022,(2):56-60. DOI： 10.13756/j.gtxyj.2022.02.012.

ZHANG Xiao-hua, PENG Xiao, HUANG Long. Hybrid Linear Iterative Signal Detection Algorithm for Massive MIMO Systems[J]. Study on Optical Communications, 2022,(2):56-60. DOI： 10.13756/j.gtxyj.2022.02.012.

摘要

针对大规模多输入多输出(MIMO)系统中线性最小均方误差(MMSE)信号检测算法复杂的高维矩阵求逆难以用于实际工程的问题，文章基于矩阵分块思想并结合Neumann级数展开算法，提出了一种低复杂度的混合迭代算法。利用MMSE算法中加权矩阵逆矩阵的Neumann级数二阶展开作为其分块矩阵求逆的迭代初始值，可以有效提高算法收敛速度。仿真结果表明，该方法能以较少迭代次数逼近传统MMSE算法较优检测性能，并降低计算复杂度。

Abstract

The linear Minimum Mean Square Error (MMSE) signal detection algorithm in the massive Multiple-Input Multiple-Output (MIMO) system is difficult to use in practical engineering due to the complex inversion of the high-dimensional matrix of the signal detection algorithm. In order to solve this problem

the article proposes a low-complexity hybrid iterative algorithm based on the idea of matrix block and combined with Neumann series expansion algorithm. Using the Neumann series second-order expansion of the inverse matrix of the weighted matrix in the MMSE algorithm as the initial value of the iterative inversion of the block matrix can effectively improve the convergence speed of the algorithm. The simulation results show that this method can have similar performance as the traditional MMSE algorithm with fewer iterations and lower complexity.

关键词

信号检测大规模多输入多输出混合迭代矩阵分块Neumann级数展开

Keywords

signal detectionmassive MIMOhybrid iterationmatrix blockNeumann series expansion

references

Larsson E G, Edfors O, Tufvesson F, et al. Massive MIMO for Next Generation Wireless Systems[J]. IEEE Communications Magazine, 2014, 52(2): 186-195.

Qian M, Wang Y, Zhou Y, et al. A Super Base Station based Centralized Network Architecture for 5G Mobile Communication Systems[J]. Digital Communications & Networks, 2015, 1(2): 152-159.

Jin F, Cui F, Liu Q, et al. A Unified Model for Signal Detection in Massive MIMO System and Its Application[C]//2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC). Las Vegas, NV, USA: IEEE, 2019: 8651841.

Cao H, Yang J, Fang X, et al. Low Complexity Detection Algorithm based on Two-diagonal Matrix Decomposition in Massive MIMO Systems[J]. Journal of Electronics & Information Technology, 2018, 40(2): 416-420.

Jin F, Liu Q, Liu H, et al. A Low Complexity Signal Detection Scheme based on Improved Newton Iteration for Massive MIMO Systems[J]. IEEE Communications Letters, 2019, 23(4): 748-751.

Marzetta T L. Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas[J]. IEEE Transactions on Wireless Communications, 2010, 9(11): 3590-3600.

Jiang Y, Varanasi M K, Li J. Performance Analysis of ZF and MMSE Equalizers for MIMO Systems: An In-depth Study of the High SNR Regime[J]. IEEE Transactions on Information Theory, 2011, 57(4): 2008-2026.

Wu M, Yin B, Wang G, et al. Large-scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations[J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(5): 916-929.

Tang C, Liu C, Yuan L, 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.

Gao X, Dai L, Yuen C, et al. Low-complexity MMSE Signal Detection based on Richardson Method for Large-scale MIMO Systems[C]//2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall). Vancouver, BC, Canada: IEEE, 2014: 6966041.

Hu Y, Wang Z, Gao L X, et al. Low-complexity Signal Detection using CG Method for Uplink Large-scale MIMO Systems[C]//IEEE International Conference on Communication Systems. Macau, China: IEEE, 2015: 7024849.

申滨, 赵书锋, 黄龙杨. 基于Kaczmarz迭代的大规模MIMO系统低复杂度软输出信号检测[J]. 电子学报, 2018, 46(11): 2746-2752.

更多指标>

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

MIMO中基于预处理的广义加权Gauss-Seide算法

一种基于优化的毫米波信道估计算法研究

基于透镜天线阵的毫米波系统波束选择研究

均匀平面天线阵列的大规模MIMO系统评估

低复杂度的似然搜索树检测算法