A low-complexity and near-optimal massive MIMO detection algorithm

CHEN Xi; WU Tian-bao; GONG Yi-yu; LV Dong-xu; HE Guang-hui

Chinese

您当前的位置：

首页 >

文章列表页 >

A low-complexity and near-optimal massive MIMO detection algorithm

更新时间：2026-09-04

- A low-complexity and near-optimal massive MIMO detection algorithm
- Vol. 37, Issue 10, Pages: 48-53(2020)
- 作者机构：
  
  1. 上海交通大学电子信息与电气工程学院,上海,200240
  2. 国网四川省电力公司电力科学研究院,四川,成都,610041
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2020
- 稿件说明：
移动端阅览
陈曦, 吴天宝, 龚奕宇, 吕东旭, 贺光辉. 一种低复杂度近最优大规模MIMO检测算法[J]. 微电子学与计算机, 2020, 37(10): 48-53.

CHEN Xi, WU Tian-bao, GONG Yi-yu, et al. A low-complexity and near-optimal massive MIMO detection algorithm[J]. 2020, 37(10): 48-53.
陈曦, 吴天宝, 龚奕宇, 吕东旭, 贺光辉. 一种低复杂度近最优大规模MIMO检测算法[J]. 微电子学与计算机, 2020, 37(10): 48-53. DOI：

CHEN Xi, WU Tian-bao, GONG Yi-yu, et al. A low-complexity and near-optimal massive MIMO detection algorithm[J]. 2020, 37(10): 48-53. DOI：

摘要

为了提升大规模MIMO(Massive Multiple-input Multiple-output)检测算法的性能并降低其复杂度，本文提出了一种基于连续替换Richardson迭代的低复杂度近最优检测算法.该算法采用连续替换策略，提升了传统Richardson迭代的收敛速度；除此之外，提出了基于特征值估计的初始化策略，在较低的复杂度下进一步提升了算法性能.仿真结果表明该算法对比传统Richardson迭代性能提升显著，且在128×16规模MIMO系统中，当迭代次数为2，误比特率为10时相对于MMSE仅有0.06 dB的性能损失，而相对于Jacobi算法有2 dB的性能提升，算法复杂度降低了10.8%.文章还给出了该算法在Xilinx Virtex-7 FPGA平台的硬件实现结果，较其他算法有更高的吞吐率，达到了10.3 Mbps.

Abstract

In order to improve the performance and reduce the complexity of Massive Multiple-input Multiple-output (MIMO) detection algorithm

a low-complexity near-optimal detection algorithm based on continuous replacement Richardson iteration is proposed. The algorithm adopts a continuous replacement strategy to improve the convergence speed of traditional Richardson iterations. In addition

an initialization strategy based on eigenvalue estimation is proposed

which further improves the performance of the algorithm at a low complexity. Simulation results show that the algorithm has a significant improvement over traditional Richardson iteration performance. In a 128×16 scale MIMO system

when the number of iterations is 2 and the bit error rate is 10

there is only 0.06 dB performance losscompared to MMSEs

and 2 dB performance improvement compared to Jacobis

while the algorithm complexity is reduced by 10.8%. The article also gives the hardware implementation results of the algorithm on the Xilinx Virtex-7 FPGA platform

which has a higher throughput rate than other algorithms

reaching 10.3 Mbps.

关键词

Keywords

references

GAO X, DAI L, HU Y, et al. Matrix inversionless signal detection using SOR method for uplink large-scale MIMO systems[C]// IEEE Global Telecommun Conference. Austin, TX, USA, IEEE, 2014: 3291-3295

QIN X, YAN Z, HE G. A near-optimal detection scheme based on joint steepest descent and jacobi method for uplink massive MIMO systems[J]. IEEE Communications Letters, 2016, 20(2):276-279. DOI: 276

PRABHU H, RODRIGUES J, EDFORS O, et al. Approximate matrix inverse computations for very-large MIMO and applications to Linear Pre-coding systems[C]// IEEE Wireless CommunicationAnd Networking Conference.Shanghai, China, IEEE, 2013: 2710-2715

YIN B, WU M, CAVALLARO J R, et al. Conjugate gradient based soft-output detection and precoding in massive MIMO systems[C]// IEEE Global Telecommun Conference. Austin, TX, USA, IEEE, 2014: 3696-3701

JING X, LI A, LIU H, A low-complexity lanczos-algorithm-based detector with soft-output for multiuser massive MIMO systems[J].Digital Signal Process, 2017, 69:41-49 DOI: 41

GAO X, DAI L, MA Y, et al. Low-complexity near-optimal signal detection for uplink large-scale MIMO systems[J]. IEEE Electron Letter, 2014, 50(18):1326-1328 DOI: 1326

ANDREWS J G, BUZZI S, CHOI W, et al. What will 5G be[J]. IEEE Journal on selected areas in communications, 2014, 32(6): 1065-1082. DOI: 1065

YIN B, WU M, STUDER C, et al. Large-scale MIMO detection for 3GPP LTE: algorithms and FPGA implementations[J]. IEEE J. Sel. Topics Signal Process, 2014, 8(5):916-929 DOI: 916

GAO X, DAI L, YUAN 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: 1-5.

MINANGO J, ALMEIDA C DE. Optimum and quasi-optimum relaxation parameters for low-complexity massive MIMO detector based on richardson method[J]. Electronics Letters, 2017, 53(16):1114-1115. DOI: 1114

LV W B, HE G H.A low complexity S-GMI-THP precoding algorithm and hardware implementation for multi-user MIMO systems[J]. Microelectronics % Computer, 2019, 36(7):6-11. DOI: 6

ALBREEM M A, JUNTTI M, SHAHABUDDIN S. Massive MIMO detection techniques: A survey[J]. IEEE Communications Surveys % Tutorials, 2019:1. DOI: 1

DING C H, HE G H.A low-complexity signal detection algorithmfor uplink massive MIMO systems[J]. Microelectronics % Computer, 2017, 34(2):6-9. DOI: 6

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on assembly action recognition based on MSS-YOLO-MPHands fusion architecture

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

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

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Design of ultra-low power real-time clock circuits

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