inis 24(3):

Research Article

Distributed Spatially Non-Stationary Channel Estimation for Extremely-Large Antenna Systems

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  • @ARTICLE{10.4108/eetinis.v11i3.5992,
        author={Yanqing Xu and Shuai Wang and Ruihong Jiang and Zhou Wang},
        title={Distributed Spatially Non-Stationary Channel Estimation for Extremely-Large Antenna Systems},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={11},
        number={3},
        publisher={EAI},
        journal_a={INIS},
        year={2024},
        month={5},
        keywords={Channel estimation, spatially non-stationary channel, extremely large aperture array},
        doi={10.4108/eetinis.v11i3.5992}
    }
    
  • Yanqing Xu
    Shuai Wang
    Ruihong Jiang
    Zhou Wang
    Year: 2024
    Distributed Spatially Non-Stationary Channel Estimation for Extremely-Large Antenna Systems
    INIS
    EAI
    DOI: 10.4108/eetinis.v11i3.5992
Yanqing Xu1,*, Shuai Wang2,*, Ruihong Jiang3,*, Zhou Wang4,*
  • 1: Chinese University of Hong Kong
  • 2: Singapore University of Technology and Design
  • 3: Beijing University of Posts and Telecommunications
  • 4: Tsinghua University
*Contact email: shuai_wang@sutd.edu.sg, shuai_wang@sutd.edu.sg, shuai_wang@sutd.edu.sg, huai_wang@sutd.edu.sg

Abstract

This paper aims to develop a distributed channel estimation (CE) algorithm for spatially non-stationary (SNS) channels in extremely large aperture array systems, addressing the issues of high communication cost and computational complexity associated with traditional centralized algorithms. However, SNS channels differ from conventional spatially stationary channels, presenting new challenges such as varying sparsity patterns for different antennas. To overcome these challenges, we propose a novel distributed CE algorithm accompanied by a simple yet effective hard thresholding scheme. The proposed algorithm is not only suitable for uniform antenna arrays but also for irregularly deployed antennas. Simulation results demonstrate the advantages of the proposed algorithm in terms of estimation accuracy, communication cost, and computational complexity.