Recent Studies on Deep Reinforcement Learning in RIS-UAV Communication Networks

Tri Hai Nguyen, Heejae Park, Laihyuk Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) technologies have recently been identified as enablers for future wireless networks. Deep reinforcement learning (DRL) is also a potential technique for optimizing performance in dynamic and complex networking environments. In this paper, we examine the state-of-the-art studies on DRL utilization in RIS-UAV communication systems concerning their objectives, optimization parameters, deployment scenarios, and DRL methods. In addition, we emphasize research challenges and directions that can be addressed to improve RIS-UAV networks.

Original languageEnglish
Title of host publication5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages378-381
Number of pages4
ISBN (Electronic)9781665456456
DOIs
StatePublished - 2023
Event5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023 - Virtual, Online, Indonesia
Duration: 20 Feb 202323 Feb 2023

Publication series

Name5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023

Conference

Conference5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023
Country/TerritoryIndonesia
CityVirtual, Online
Period20/02/2323/02/23

Keywords

  • 5G/6G network
  • aerial access network
  • deep reinforcement learning
  • RIS
  • UAV
  • wireless communication

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