A DRL-based Reflection Enhancement Method for RIS-assisted Multi-receiver Communications

Wei Wang*, Peizheng Li, Angela Doufexi, Mark A Beach

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

In reconfigurable intelligent surface (RIS)-assisted wireless communication systems, the pointing accuracy and intensity of reflections depend crucially on the ’profile,’ representing the amplitude/phase state information of all elements in a RIS array. The superposition of multiple single-reflection profiles enables multi-reflection for distributed users. However, the optimization challenges from periodic element arrangements in single-reflection and multi-reflection profiles are understudied. The combination of periodical single-reflection profiles leads to amplitude/phase counteractions, affecting the performance of each reflection beam. This paper focuses on a dual-reflection optimization scenario and investigates the far-field performance deterioration caused by the misalignment of overlapped profiles. To address this issue, we introduce a novel deep reinforcement learning (DRL)-based optimization method. Comparative experiments against random and exhaustive searches demonstrate that our proposed DRL method outperforms both alternatives, achieving the shortest optimization time. Remarkably, our approach achieves a 1.2 dB gain in the reflection peak gain and a broader beam without any hardware modifications.
Original languageEnglish
Title of host publication2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9798350329285
ISBN (Print)9798350329292
DOIs
Publication statusPublished - 11 Dec 2023
Event2023 IEEE 98th Vehicular Technology Conference - Hong Kong, Hong Kong
Duration: 10 Oct 202313 Oct 2023
https://events.vtsociety.org/vtc2023-fall/

Publication series

NameIEEE Vehicular Technology Conference
PublisherIEEE
ISSN (Print)1090-3038
ISSN (Electronic)2577-2465

Conference

Conference2023 IEEE 98th Vehicular Technology Conference
Abbreviated titleVTC2023-Fall
Country/TerritoryHong Kong
CityHong Kong
Period10/10/2313/10/23
Internet address

Bibliographical note

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