Low-Complexity Decision Feedback Equalization for Single-Carrier Massive MIMO Systems

被引:1
|
作者
Zhang, Xiaohui [1 ]
Xing, Ling [1 ]
Wu, Honghai [1 ]
Ji, Baofeng [1 ]
Zhang, Gaoyuan [1 ]
机构
[1] Henan Univ Sci & Technol, Sch Informat Engn, Luoyang 471023, Peoples R China
基金
中国国家自然科学基金;
关键词
Decision feedback equalizers; Massive MIMO; Computational complexity; Frequency-domain analysis; Filters; Signal detection; Loading; Single-carrier; massive MIMO; decision feedback equalization; low-complexity signal detection; frequency domain equalization; FREQUENCY-DOMAIN EQUALIZATION; TURBO-EQUALIZATION; TRANSMISSION; MODULATION; RECEIVERS; ALGORITHM; SCHEMES; DESIGN; TIME; OFDM;
D O I
10.1109/TVT.2024.3431672
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Decision feedback equalization (DFE) has demonstrated its potential to achieve near-optimal performance in signal detection within single-carrier massive MIMO systems. However, matrix-inversion-based DFE schemes are not suitable for massive MIMO systems due to their prohibitively high computational complexity. In this paper, we investigate frequency domain DFE for signal detection in single-carrier massive MIMO systems with the goal of reducing computational complexity for practical applications. We propose a low-complexity implicit DFE scheme for single-carrier massive MIMO systems, which mitigates inter-stream and inter-symbol interference by leveraging the Neumann series (NS) expansion for matrix inversion approximation (MIA). The proposed scheme performs DFE implicitly by recursively computing forward/feedback signals using the NS expansion, thereby avoiding computationally intensive matrix inversions and forward/feedback filters calculation. Simulation and analysis results indicate that, compared to matrix-inversion-based DFE schemes, the proposed implicit DFE scheme can significantly reduce computational complexity while achieving similar performance in single-carrier massive MIMO systems. Moreover, it outperforms existing low-complexity detection methods under stringent channel conditions while maintaining similar or even lower complexity.
引用
收藏
页码:17316 / 17330
页数:15
相关论文
共 50 条
  • [41] Enhanced Low-Complexity Matrix Inversion Method for Massive MIMO Systems
    Ahmed, Yasser Naguib
    2019 16TH INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATION SYSTEMS (ISWCS), 2019, : 495 - 499
  • [42] A Low-Complexity Multiuser Adaptive Modulation Scheme for Massive MIMO Systems
    Zhou, Yuehao
    Zhong, Caijun
    Jin, Shi
    Huang, Yongming
    Zhang, Zhaoyang
    IEEE SIGNAL PROCESSING LETTERS, 2016, 23 (10) : 1464 - 1468
  • [43] Power Control and Low-Complexity Receiver for Uplink Massive MIMO Systems
    Fan, Lixing
    Huang, Yongming
    Zhang, Fan
    He, Shiwen
    Yang, Luxi
    2014 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2014, : 266 - 270
  • [44] A Low-Complexity Detection Method Based on Iteration for Massive MIMO Systems
    Li, Huan
    Zhao, Xuying
    Guo, Chen
    Wang, Xiaoqin
    2017 IEEE 9TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN), 2017, : 487 - 491
  • [45] A Low-Complexity Signal Detection Approach in Uplink Massive MIMO Systems
    Liang, Zhuojun
    Ding, Chunhui
    He, Guanghui
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2018, E101A (07): : 1115 - 1119
  • [46] Low-Complexity MMSE Receiver Design for Massive MIMO OTFS Systems
    Sheikh, Mudasir Ahmad
    Singh, Prem
    Budhiraja, Rohit
    IEEE COMMUNICATIONS LETTERS, 2022, 26 (11) : 2759 - 2763
  • [47] Low-Complexity SSOR-Based Precoding for Massive MIMO Systems
    Xie, Tian
    Dai, Linglong
    Gao, Xinyu
    Dai, Xiaoming
    Zhao, Youping
    IEEE COMMUNICATIONS LETTERS, 2016, 20 (04) : 744 - 747
  • [48] A Low-Complexity Equalizer for Massive MIMO Systems Based on Array Separability
    Ribeiro, Lucas N.
    Schwarz, Stefan
    Rupp, Markus
    de Almeida, Andre L. F.
    Mota, Joao C. M.
    2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2017, : 2453 - 2457
  • [49] A New Low-Complexity WMMSE Algorithm for Downlink Massive MIMO Systems
    Zhou, Ningxin
    Wang, Zheng
    He, Lanxin
    Huang, Yang
    2022 14TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING, WCSP, 2022, : 1096 - 1101
  • [50] Securing Massive MIMO Systems: Secrecy for Free With Low-Complexity Architectures
    Bereyhi, Ali
    Asaad, Saba
    Mueller, Ralf R.
    Schaefer, Rafael F.
    Fischer, Georg
    Poor, H. Vincent
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (09) : 5831 - 5845