Heterogeneous Multi-Agent Reinforcement Learning for Joint Active and Passive Beamforming in IRS Assisted Communications

Ang Gao, Xinshun Sun, Yongshuai Xu, Wei Liang

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Ahstract-The Intelligent Reflecting Surface (IRS) has the potential to reconstruct the electromagnetic propagation environment, paving the way for a new multi-IRS assisted communications paradigm that beams scattered signals for improved spectrum efficiency (SE). However, accurate channel estimation and sharing becomes a challenge when a large number of IRS elements are involved, leading to extra hardware complexity and communication overhead. Moreover, due to the cross-interference caused by massive reflecting paths when multiple IRSs are introduced, SE optimization becomes challenging to achieve a close-formed solution because of non-convexity. This paper improves a heterogeneous based multi-agent deep deterministic policy gradient (MADDPG) approach for joint active and passive beamforming optimization without channel estimation, where base station (BS) and multiple IRSs cooperatively learn to enhance SE and suppress the interference. Due to the centralized-training and distributed-execution feature of MADDPG, the well-trained BS and IRSs can execute both the active and passive beamforming optimization independently without referring to other agents, which can greatly reduce the communication overhead and simplify the IRS deployment. Numeral simulations demonstrate the effectiveness of the proposed approach on enhancing SE and suppressing interference in the multi-IRS assisted communications system.

源语言英语
主期刊名32nd Wireless and Optical Communications Conference, WOCC 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350337150
DOI
出版状态已出版 - 2023
活动32nd Wireless and Optical Communications Conference, WOCC 2023 - Newark, 美国
期限: 5 5月 20236 5月 2023

出版系列

姓名32nd Wireless and Optical Communications Conference, WOCC 2023

会议

会议32nd Wireless and Optical Communications Conference, WOCC 2023
国家/地区美国
Newark
时期5/05/236/05/23

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