Mixed LoS/NLoS Near-Field Channel Estimation for Extremely Large-Scale MIMO Systems

被引:0
|
作者
Lu, Yu [1 ]
Dai, Linglong [1 ]
机构
[1] Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol BNRis, Dept Elect Engn, Beijing 100084, Peoples R China
来源
ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS | 2023年
基金
中国国家自然科学基金; 欧盟地平线“2020”;
关键词
6G; extremely large-scale MIMO; channel estimation; near-field;
D O I
10.1109/ICC45041.2023.10278686
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Accurate channel estimation is essential to empower extremely large-scale MIMO (XL-MIMO) with ultra-high spectral efficiency in 6G networks. With the sharp increase in the antenna array aperture of the XL-MIMO system, the electromagnetic propagation field will change from far-field to near-field. Unfortunately, due to the near-field effect, the existing near-field XL-MIMO channel model mismatches the practical mixed line-of-sight (LoS) and non-line-of-sight (NLoS) channel feature. In this paper, a mixed LoS/NLoS near-field XL-MIMO channel model is proposed to accurately describe the LoS and NLoS path components simultaneously, where the LoS path component is modeled by the geometric free space propagation assumption while NLoS path components are modeled by the near-field array response vectors. Then, to define the range of near-field for XL-MIMO, the MIMO Rayleigh distance (MIMO-RD) is derived. Next, a two stage channel estimation algorithm is proposed, where the LoS path component and NLoS path components are estimated separately. Numerical simulation results demonstrate that, the proposed two stage scheme is able to outperform the existing methods.
引用
收藏
页码:1506 / 1511
页数:6
相关论文
共 50 条
  • [21] Near-Field Analysis of Extremely Large-Scale MIMO: Power, Correlation, and User Selection
    Cui, Xiangyu
    Park, Ki-Hong
    Alouini, Mohamed Slim
    IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2025, 6 : 252 - 270
  • [22] Near-Field Beam Training for Extremely Large-Scale MIMO Based on Deep Learning
    Nie, Jiali
    Cui, Yuanhao
    Yang, Zhaohui
    Yuan, Weijie
    Jing, Xiaojun
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2025, 24 (01) : 352 - 362
  • [23] High-Efficient Near-Field Channel Characteristics Analysis for Large-Scale MIMO Communication Systems
    Jiang, Hao
    Shi, Wangqi
    Chen, Xiao
    Zhu, Qiuming
    Chen, Zhen
    IEEE INTERNET OF THINGS JOURNAL, 2025, 12 (06): : 7446 - 7458
  • [24] Hybrid-Field Channel Estimation for Extremely Large-Scale Massive MIMO System
    Hu, Zhentao
    Chen, Chaoyu
    Jin, Yong
    Zhou, Lin
    Wei, Qian
    IEEE COMMUNICATIONS LETTERS, 2023, 27 (01) : 303 - 307
  • [25] Dynamic Hybrid-field Channel Estimation for Extremely Large-scale Massive MIMO
    Yan, Xingyun
    Yuan, Jide
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [26] Hierarchical Beam Training for Extremely Large-Scale MIMO: From Far-Field to Near-Field
    Lu, Yu
    Zhang, Zijian
    Dai, Linglong
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2024, 72 (04) : 2247 - 2259
  • [27] Near-Field 2D Hierarchical Beam Training for Extremely Large-Scale MIMO
    Lu, Yu
    Zhang, Zijian
    Dai, Linglong
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 7176 - 7181
  • [28] Machine Learning Enhanced Near-Field Secret Key Generation for Extremely Large-Scale MIMO
    Chen, Chen
    Zhang, Junqing
    2024 IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING FOR COMMUNICATION AND NETWORKING, ICMLCN 2024, 2024, : 183 - 188
  • [29] Near-Field Channel Estimation for Extremely Large-Scale Reconfigurable Intelligent Surface (XL-RIS)-Aided Wideband mmWave Systems
    Yang, Songjie
    Xie, Chenfei
    Lyu, Wanting
    Ning, Boyu
    Zhang, Zhongpei
    Yuen, Chau
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2024, 42 (06) : 1567 - 1582
  • [30] Near-Field Beam Training for Extremely Large-Scale IRS
    Wang, Tao
    Lv, Jie
    Tong, Haonan
    You, Changsheng
    Yin, Changchuan
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,