Uplink channel estimation for massive MIMO systems exploring joint channel sparsity

被引：39
|
作者：
Qi, Chenhao [1 ]
Wu, Lenan [1 ]
机构：
[1] Southeast Univ, Sch Informat Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China
来源：
ELECTRONICS LETTERS | 2014年 / 50卷 / 23期
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1049/el.2014.2769
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：
The joint sparsity of uplink channels in massive multi-input-multi-output (MIMO) systems is explored and a block sparse model is proposed for joint channel estimation. The block coherence of this model is analysed. It is indicated that as the number of antennas at the base station grows to be infinity, the block coherence will be zero. Then a block optimised orthogonal matching pursuit (BOOMP) algorithm is proposed. Simulation results verify the analysis and show that the joint estimation using the BOOMP algorithm can significantly improve the channel estimation performance.
引用
收藏
页码：1770 / 1771
页数：2
相关论文
共 50 条
  • [21] Massive MIMO Uplink Channel Estimation using Compressive Sensing
    Lahbib, Noura Derria
    Cherif, Maha
    Hizem, Moez
    Bouallegue, Ridha
    [J]. 2019 27TH INTERNATIONAL CONFERENCE ON SOFTWARE, TELECOMMUNICATIONS AND COMPUTER NETWORKS (SOFTCOM), 2019, : 193 - 198
  • [22] Deep learning for joint channel estimation and feedback in massive MIMO systems
    Guo, Jiajia
    Chen, Tong
    Jin, Shi
    Li, Geoffrey Ye
    Wang, Xin
    Hou, Xiaolin
    [J]. DIGITAL COMMUNICATIONS AND NETWORKS, 2024, 10 (01) : 83 - 93
  • [23] Deep learning for joint channel estimation and feedback in massive MIMO systems
    Jiajia Guo
    Tong Chen
    Shi Jin
    Geoffrey Ye Li
    Xin Wang
    Xiaolin Hou
    [J]. Digital Communications and Networks, 2024, 10 (01) - 93
  • [24] Low Complexity Joint Channel Estimation and Compression for Massive MIMO Systems
    Aafreen, Rubeena
    Khan, Mohammed Zafar Ali
    [J]. 2023 IEEE FUTURE NETWORKS WORLD FORUM, FNWF, 2024,
  • [25] Exploiting Markov Random Field Sparsity for Wideband Channel Estimation in Massive MIMO Systems
    Liu, Xiaofeng
    Wang, Wenjin
    Gong, Xinrui
    Fu, Xiao
    Gao, Xiqi
    Xia, Xiang-Gen
    [J]. 2022 14TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING, WCSP, 2022, : 1040 - 1045
  • [26] Optimal Uplink Channel Estimation Algorithm for OFDM Based MmWave Massive MIMO Systems
    Hajjaj, Moufida
    Mejri, Ameni
    Bouallegue, Ridha
    Hasnaoui, Salem
    [J]. 2018 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2018, : 801 - 805
  • [27] On Channel Estimation of Uplink TDD Massive MIMO Systems Through Different Pilot Structures
    Amadid, Jamal
    Boulouird, Mohamed
    Riadi, Abdelhamid
    Hassani, Moha M'Rabet
    [J]. NETWORKING, INTELLIGENT SYSTEMS AND SECURITY, 2022, 237 : 161 - 176
  • [28] Hierarchical Sparse Estimation of Non-Stationary Channel for Uplink Massive MIMO Systems
    Tan, Chongyang
    Cai, Donghong
    Fang, Fang
    Shan, Jiahao
    Xu, Yanqing
    Ding, Zhiguo
    Fan, Pingzhi
    [J]. IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 6640 - 6645
  • [29] Variational Bayes' Joint Channel Estimation and Soft Symbol Decoding for Uplink Massive MIMO Systems With Low Resolution ADCs
    Thoota, Sai Subramanyam
    Murthy, Chandra R.
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2021, 69 (05) : 3467 - 3481
  • [30] QUANTIZED VARIATIONAL BAYESIAN JOINT CHANNEL ESTIMATION AND DATA DETECTION FOR UPLINK MASSIVE MIMO SYSTEMS WITH LOW RESOLUTION ADCS
    Thoota, Sai Subramanyam
    Murthy, Chandra R.
    Annavajjala, Ramesh
    [J]. 2019 IEEE 29TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2019,
12345