Low complexity IAOR signal detection for uplink GSM - massive MIMO systems

被引:0
|
作者
Hanchate, Seema M. [1 ]
Nema, Shikha [1 ]
机构
[1] SNDT Womens Univ, Usha Mittal Inst Technol, Mumbai, Maharashtra, India
关键词
massive MIMO; MMSE signal detection; accelerated over-relaxation; channel correlation; computational complexity; uplink transmission; MODULATION; NETWORK;
D O I
10.1504/IJCNDS.2024.141674
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Massive multiple input multiple output (Mamimo) is a high-speed wireless communication that uses more antennas at the receiver base station. When more antennas are utilised, the channel matrix gets larger. As a result of the inversion channel matrix, the complexity of linear signal detection grows. Mamimo consumes more power due to radio-frequency (RF) chains. The channel magnitude and correlation are used to implement the antenna selection process. The antenna selection method reduces the number of RF chains and improves BER performance. To avoid expensive matrix inversion, the improved accelerated over relaxation (IAOR) signal detection algorithm is presented. For various antenna designs, the bit error rate is calculated. According to the result of MATLAB simulation, the performance of the standard minimum mean square error (MMSE) detection and the proposed method are approximately equal. The proposed IAOR signal detection method improves the overall performance and energy efficiency and also reduces computational complexity.
引用
收藏
页码:699 / 710
页数:13
相关论文
共 50 条
  • [31] SD-Based Low-Complexity Signal Detection Algorithm in Massive MIMO Systems
    Jiang, Xiaolin
    Zhang, Lihuan
    MOBILE NETWORKS & APPLICATIONS, 2023, 29 (4): : 1203 - 1211
  • [32] Low-Complexity Signal Detection Based on Relaxation Iteration Method in Massive MIMO Systems
    GUO Ruohan
    LI Xiaohui
    FU Weihong
    HEI Yongqiang
    China Communications, 2015, (S1) : 1 - 8
  • [33] A Low-Complexity Signal Detection Utilizing AOR Iterative Method for Massive MIMO Systems
    Zhang, Zhenyu
    Dai, Xiaoming
    Dong, Yuanyuan
    Wang, Xiyuan
    Liu, Tong
    CHINA COMMUNICATIONS, 2017, 14 (11) : 269 - 278
  • [34] Low-Complexity Signal Detection Based on Relaxation Iteration Method in Massive MIMO Systems
    GUO Ruohan
    LI Xiaohui
    FU Weihong
    HEI Yongqiang
    中国通信, 2015, 12(S1) (S1) : 1 - 8
  • [35] Extrapolation Principle-Based Low-Complexity Signal Detection in Massive MIMO Systems
    Khoso, Imran A.
    Kang, Chung G.
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2024, 13 (05) : 1419 - 1423
  • [36] Low-Complexity Signal Detection for Massive MIMO Systems via Trace Iterative Method
    Imran, A. Khoso
    Zhang, Xiaofei
    Abdul, Hayee Shaikh
    Ihsan, A. Khoso
    Zaheer, Ahmed Dayo
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2024, 35 (03) : 549 - 557
  • [37] A Low Complexity Signal Detection Scheme Based on Improved Newton Iteration for Massive MIMO Systems
    Jin, Fangli
    Liu, Qiufeng
    Liu, Hao
    Wu, Peng
    IEEE COMMUNICATIONS LETTERS, 2019, 23 (04) : 748 - 751
  • [38] Low-Complexity Symbol Detection for Massive MIMO Uplink Based on Jacobi Method
    Kong, Byeong Yong
    Park, In-Cheol
    2016 IEEE 27TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2016, : 406 - 410
  • [39] Low-Complexity Signal Detection Based on Relaxation Iteration Method in Massive MIMO Systems
    Guo Ruohan
    Li Xiaohui
    Fu Weihong
    Hei Yongqiang
    CHINA COMMUNICATIONS, 2015, 12 (01) : 1 - 8
  • [40] Low-complexity MMSE-IRC algorithm for uplink massive MIMO systems
    Ren, Bin
    Wang, Yingmin
    Sun, Shaohui
    Zhang, Yawen
    Dai, Xiaoming
    Niu, Kai
    ELECTRONICS LETTERS, 2017, 53 (14) : 972 - 973