Wideband mmWave Massive MIMO Channel Estimation and Localization

被引:8
作者
Weng, Shudi [1 ]
Jiang, Fan [1 ,2 ]
Wymeersch, Henk [1 ]
机构
[1] Chalmers Univ Technol, Dept Elect Engn, S-41296 Gothenburg, Sweden
[2] Halmstad Univ, Sch Informat Technol, S-30118 Halmstad, Sweden
关键词
Channel estimation; Wideband; Narrowband; Millimeter wave communication; Location awareness; Tensors; Perturbation methods; Wideband effect; ESPRIT; wideband localization; mmWave MIMO; MULTIDIMENSIONAL HARMONIC RETRIEVAL; DECOMPOSITION; OFDM;
D O I
10.1109/LWC.2023.3270160
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Spatial wideband effects are known to affect channel estimation and localization performance in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Based on perturbation analysis, we show that the spatial wideband effect is in fact more pronounced than previously thought and could significantly degrade performance if not properly considered in the algorithm design, even at moderate bandwidths. We propose a novel channel estimation method based on multidimensional ESPRIT algorithms per subcarrier, combined with unsupervised learning for pairing across subcarriers, which shows significant performance gain over existing schemes under wideband conditions.
引用
收藏
页码:1314 / 1318
页数:5
相关论文
共 50 条
  • [41] Tensor-Based Joint Channel Estimation and Symbol Detection for Time-Varying mmWave Massive MIMO Systems
    Du, Jianhe
    Han, Meng
    Chen, Yuanzhi
    Jin, Libiao
    Gao, Feifei
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2021, 69 : 6251 - 6266
  • [42] Adaptive Random Spatial based Channel Estimation (ARSCE) for Wideband mmWave MIMO System
    Vadgave, Rajkumar M.
    Manjula, S.
    Vishwanath, T. S.
    2021 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER TECHNOLOGIES AND OPTIMIZATION TECHNIQUES (ICEECCOT), 2021, : 575 - 579
  • [43] Channel Estimation for IRS-Assisted mmWave Massive MIMO Systems in Mixed-ADC Architecture
    Zhang, Rui
    Tan, Weiqiang
    Li, Shidang
    Tang, Maobin
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (06): : 9969 - 9978
  • [44] Simplified Learned Approximate Message Passing Network for Beamspace Channel Estimation in mmWave Massive MIMO Systems
    Ruan, Chengyao
    Zhang, Zaichen
    Jiang, Hao
    Zhang, Hongming
    Dang, Jian
    Wu, Liang
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (05) : 5142 - 5156
  • [45] Design and Optimization on Training Sequence for mmWave Communications: A New Approach for Sparse Channel Estimation in Massive MIMO
    Ma, Xu
    Yang, Fang
    Liu, Sicong
    Song, Jian
    Han, Zhu
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2017, 35 (07) : 1486 - 1497
  • [46] Two-Stage Channel Estimation for mmWave Massive MIMO Systems Based on ResNet-UNet
    Zhao, Junhui
    Wu, Yao
    Zhang, Qingmiao
    Liao, Jieyu
    IEEE SYSTEMS JOURNAL, 2023, 17 (03): : 4291 - 4300
  • [47] Improved Hierarchical Codebook-Based Channel Estimation for mmWave Massive MIMO Systems
    Yoon, Sung-Geun
    Lee, Seung Joon
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2022, 11 (10) : 2095 - 2099
  • [48] Switch-Based Hybrid Analog/Digital Channel Estimation for mmWave Massive MIMO
    Poulin, Alec
    Morsali, Alireza
    Champagne, Benoit
    2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL), 2020,
  • [49] CNN-based Channel Estimation using NOMA for mmWave Massive MIMO System
    Anu, T. S.
    Raveendran, Tara
    2023 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP, SSP, 2023, : 349 - 353
  • [50] Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems
    He, Hengtao
    Wen, Chao-Kai
    Jin, Shi
    Li, Geoffrey Ye
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2018, 7 (05) : 852 - 855