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  • Deep Learning-Based CSI Feedback for Terahertz Ultra-Massive MIMO Systems Open Access

    Yuling LI  Aihuang GUO  

     
    LETTER-Communication Theory and Signals

      Pubricized:
    2023/12/01
      Vol:
    E107-A No:8
      Page(s):
    1413-1416

    Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) is envisioned as a key enabling technology of 6G wireless communication. In UM-MIMO systems, downlink channel state information (CSI) has to be fed to the base station for beamforming. However, the feedback overhead becomes unacceptable because of the large antenna array. In this letter, the characteristic of CSI is explored from the perspective of data distribution. Based on this characteristic, a novel network named Attention-GRU Net (AGNet) is proposed for CSI feedback. Simulation results show that the proposed AGNet outperforms other advanced methods in the quality of CSI feedback in UM-MIMO systems.