Highly accurate millimeter wave channel estimation in massive MIMO system

被引:0
|
作者
Zhang, Beibei [1 ]
Xu, Peng [1 ]
Qiao, Bo [2 ]
Wei, Ziping [2 ]
Li, Bin [2 ]
Zhao, Chenglin [2 ]
机构
[1] Jiangsu Automat Res Inst, Lianyungang, Jiangsu, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
channel estimation; millimetre waves; CELLULAR WIRELESS; NETWORKS; FEEDBACK;
D O I
10.1049/cmu2.12569
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
Accurate channel state information (CSI) is extremely crucial to realize high-accurate hybrid precoding, in millimeter wave communication systems. In order to improve the CSI estimation performance, several traditional channel estimators have been developed by exploiting the sparse or low-rank property, whilst they bring huge channel training overhead and computational complexity. In this work, based on jointly sparse and low-rank property of massive multiple input multiple output (MIMO) channel, one non-convex mmWave channel estimation problem is formulated and a novel scheme to acquire one accurate CSI estimation result with greatly reduced training overhead is proposed. Specifically, the non-convex problem is reformulated as two simple sub-problems, by exploiting the alternating direction method of multipliers (ADMM) technique. Based on the low-rank characteristic, one fast gradient descent matrix completion algorithm is developed to accurately solve the first sub-problem. On this basis, the compressed sensing (CS) technique to acquire the accurate CSI estimation matrix is further utilized. Numerical simulation validates that the method could achieve the much higher channel estimation accuracy, yet only incurs the lower overhead compared with the traditional scheme.
引用
下载
收藏
页码:670 / 680
页数:11
相关论文
共 50 条
  • [1] Model based Beamspace Channel Estimation for Millimeter Wave Massive MIMO System
    Xia, Zhikang
    Qi, Chenhao
    Zhang, Tengxiang
    2018 10TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2018,
  • [2] Channel estimation by reduced dimension decomposition for millimeter wave massive MIMO system
    Dai, Rong
    Liu, Yang
    Wang, Qin
    Yu, Yu
    Guo, Xin
    PHYSICAL COMMUNICATION, 2021, 44
  • [3] Accurate Channel Estimation for Millimeter-Wave MIMO Systems
    Cheng, Xiantao
    Tang, Chao
    Zhang, Zhongpei
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (05) : 5159 - 5163
  • [4] Beamspace Channel Estimation for Millimeter Wave Massive MIMO System With Hybrid Precoding and Combining
    Ma, Wenyan
    Qi, Chenhao
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2018, 66 (18) : 4839 - 4853
  • [5] Channel Estimation for 3-D Lens Millimeter Wave Massive MIMO System
    Ma, Wenyan
    Qi, Chenhao
    IEEE COMMUNICATIONS LETTERS, 2017, 21 (09) : 2045 - 2048
  • [6] Hybrid Beamforming Based Millimeter Wave Massive MIMO Channel Estimation
    Huang Jingze
    Liang Xuwen
    Xie Zhuochen
    LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (05)
  • [7] Millimeter-Wave Massive MIMO Channel Estimation in Relay Environment
    Liu, Zhenghong
    He, Jing
    Chen, Yuanzhi
    Du, Jianhe
    Li, Jiaqi
    2020 IEEE 3RD INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SIGNAL PROCESSING (ICICSP 2020), 2020, : 370 - 374
  • [8] Regularized Multipath Matching Pursuit for Sparse Channel Estimation in Millimeter Wave Massive MIMO System
    Tao, Jun
    Qi, Chenhao
    Huang, Yongming
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2019, 8 (01) : 169 - 172
  • [9] Sub-Array-Based Millimeter Wave Massive MIMO Channel Estimation
    Zhu, Xuan
    Liu, Yang
    Wang, Cheng-Xiang
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2023, 12 (09) : 1608 - 1612
  • [10] Device Activity Detection and Channel Estimation for Millimeter-Wave Massive MIMO
    Li, Yinchuan
    Zhan, Yuancheng
    Zheng, Le
    Wang, Xiaodong
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2024, 72 (02) : 1062 - 1074