Energy Harvesting Design for Cooperative Reconfigurable Intelligent Surface with Multi-Agent Deep Reinforcement Learning

Yihang Tao, Jun Wu*, Qianqian Pan, Xiuzhen Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cooperative reconfigurable intelligent surface (Cooperative- RIS)-assisted communication systems have been proven to provide more smart computing and communication ability than single-RIS or multi-distributed-RIS systems regarding beamforming gain and channel diversity. However, the increased number of deployed RISs brings heavier energy consumption, which makes the cooperative- RIS system less sustainable. The majority of previous works mainly study energy harvesting (EH) for single- RIS systems which cannot be directly applied to the cooperative- RIS systems. In this paper, we study the EH for cooperative- RIS-assisted communication systems. Specifically, we first model the cooperative beamforming and EH optimization as a non-convex problem. Besides, we propose a multi-agent deep deterministic policy gradient (MADDPG)-based EH efficiency maximization scheme for cooperative RISs while satisfying an acceptable sum rate. Finally, experimental results show the effectiveness of our proposed scheme.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 10th International Conference on Intelligent Data and Security, IDS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages42-46
Number of pages5
ISBN (Electronic)9798350389487
DOIs
Publication statusPublished - 2024
Event10th IEEE International Conference on Intelligent Data and Security, IDS 2024 - New York City, United States
Duration: 2024 May 102024 May 12

Publication series

NameProceedings - 2024 IEEE 10th International Conference on Intelligent Data and Security, IDS 2024

Conference

Conference10th IEEE International Conference on Intelligent Data and Security, IDS 2024
Country/TerritoryUnited States
CityNew York City
Period24/5/1024/5/12

Keywords

  • cooperative beamforming
  • energy harvesting
  • multi-agent deep reinforcement learning
  • reconfigurable intelligent surface
  • smart communication

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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