A Low-complexity Signal Detection Algorithm for Uplink Massive MIMO Systems

DING Chun-hui; HE Guang-hui

Chinese

您当前的位置：

首页 >

文章列表页 >

A Low-complexity Signal Detection Algorithm for Uplink Massive MIMO Systems

更新时间：2026-09-04

- A Low-complexity Signal Detection Algorithm for Uplink Massive MIMO Systems
- Vol. 34, Issue 2, Pages: 6-9(2017)
- 作者机构：
  
  上海交通大学微电子学院,上海,200240
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
丁春辉, 贺光辉. 一种上行链路大规模MIMO系统的低复杂度检测算法[J]. 微电子学与计算机, 2017, 34(2): 6-9.

DING Chun-hui, HE Guang-hui. A Low-complexity Signal Detection Algorithm for Uplink Massive MIMO Systems[J]. 2017, 34(2): 6-9.
丁春辉, 贺光辉. 一种上行链路大规模MIMO系统的低复杂度检测算法[J]. 微电子学与计算机, 2017, 34(2): 6-9. DOI：

DING Chun-hui, HE Guang-hui. A Low-complexity Signal Detection Algorithm for Uplink Massive MIMO Systems[J]. 2017, 34(2): 6-9. DOI：

摘要

提出了一种适用于上行链路大规模MIMO系统的基于Kaczmarz算法的低复杂度检测算法.通过将MMSE检测算法转化成等效的增广矩阵的形式

提出的算法同时避免了直接矩阵求逆和Gram矩阵求解.此外

一种算法初始值的估计方法和近似的软判决信息计算方法也被提出用于进一步降低算法复杂度.仿真结果表明该算法在性能和计算复杂度方面优于近期文献中的算法.同时

FPGA的验证结果也表明提出的算法能以更低的硬件资源消耗完成大规模MIMO系统的检测.

Abstract

A low-complexity signal detection approach based on Kaczmarz algorithm is proposed to iteratively realize MMSE detection for uplink massive MIMO systems. By applying an equivalent augmented matrix in MMSE detection

the proposed algorithm avoid the exact matrix inversion and Gram matrix computation. Moreover

promising initial estimation and an approximate method to compute soft-output information is utilized to further reduce the complexity. Simulation results demonstrate that the proposed approach outperforms recently proposed algorithms in complexity and performance. Meanwhile

the FPGA implementation results verify that our proposed method can efficiently compute the approximate inverse with low complexity.

关键词

Keywords

references

Yin B, Wu M, Studer C, et al. Implementation trade-offs for linear detection in massive MIMO systems[C]//Proc. IEEE ICASSP 2013. Vancouver, Canada, 2013: 2679-2683.

Rusek F, Persson D, Lau B L, et al. Scaling up MIMO: opportunities and challenges with very large arrays[J]. IEEE Signal Process. Mag., 2013, 30(1): 40-60. DOI: 40

Wu M, Yin B, Vosoughi A, et al. Approximate matrix inversion for high-throughput data detection in the massive MIMO uplink[C]//Proc. IEEE ISCAS 2013. China, Beijing, 2013: 2155-2158.

Strohmer T, Vershynin R. A randomized Kaczmarz algorithm for linear systems with exponential convergence[J]. Fourier Analysis and Applications, 2008, 15(2): 262-278. DOI: 262

Yin B, Wu M, Cavallaro J R, et al. Conjugate gradient-based soft-output detection and precoding in massive MIMO systems[C]//Proc. IEEE GLOBECOM 2014. Austin, TX, 2014: 3696-3701.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Aerial small object detection algorithm based on improved RT-DETR

Lightweight countermeasures against Spectre attacks on the branch prediction unit

Simulation on the DC characteristics of double heterojunction p-GaN HEMT with AlN/GaN hybrid buffer layer

A high-efficiency charge pump for ultra-low voltage boost systems

High gain stability high temperature operational amplifier based on reverse body bias

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰