Deep Reinforcement Learning for Interference Suppression in RIS-Aided High-Speed Railway Networks

Jianpeng Xu, Bo Ai, Tony Q.S. Quek, Yupei Liuc

研究成果: Conference contribution

摘要

This paper investigates the reconfigurable intelligent surface (RIS)-aided high-speed railway (HSR) network, where one RIS is deployed nearby the onboard mobile relay (MR) to suppress the external interference in HSR system. In order to enhance the HSR network capacity against the interference, we formulate an optimization problem for designing the phase shifts at the RIS. Since the HSR environment is time-varying and complicated, the optimization problem is challenging to settle. Inspired by the recent advances of artificial intelligence (AI), we propose a deep reinforcement learning (DRL)-based scheme to design the RIS phase shifts. Simulation results show that 1) deploying the RIS nearby the onboard MR is strongly facilitative of suppressing the interference; 2) the proposed DRL scheme can achieve better capacity than the baseline schemes.

原文English
主出版物標題2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面337-342
頁數6
ISBN(電子)9781665426718
DOIs
出版狀態Published - 2022
事件2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022 - Seoul, Korea, Republic of
持續時間: 2022 5月 162022 5月 20

出版系列

名字2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022

Conference

Conference2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
國家/地區Korea, Republic of
城市Seoul
期間22-05-1622-05-20

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 訊號處理
  • 控制和優化

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