LAPSE:2023.11774
Published Article
LAPSE:2023.11774
A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications
February 28, 2023
Abstract
Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that need to be addressed to realize IRS-assisted UAV communications systems.
Keywords
Energy Efficiency, intelligent reflecting surface (IRS), Optimization, spectral efficiency, unmanned aerial vehicle (UAV)
Suggested Citation
Park KW, Kim HM, Shin OS. A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications. (2023). LAPSE:2023.11774
Author Affiliations
Park KW: School of Electronic Engineering, Soongsil University, Seoul 06978, Korea [ORCID]
Kim HM: Department of Information Communication Convergence Technology, Soongsil University, Seoul 06978, Korea [ORCID]
Shin OS: School of Electronic Engineering, Soongsil University, Seoul 06978, Korea; Department of Information Communication Convergence Technology, Soongsil University, Seoul 06978, Korea [ORCID]
Journal Name
Energies
Volume
15
Issue
14
First Page
5143
Year
2022
Publication Date
2022-07-15
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15145143, Publication Type: Review
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LAPSE:2023.11774
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https://doi.org/10.3390/en15145143
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Feb 28, 2023
 
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