Reference : Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift O...

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/53392

Title :	Controlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization
Language :	English
Author, co-author :	Van Chien, Trinh []
	Tu, Lam Thanh []
	Tran Dinh, Hieu [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Nguyen, Hieu Van []
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Di Renzo, Marco []
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2022
Main document title :	ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher :	IEEE
Peer reviewed :	Yes
Audience :	International
Event name :	ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Event date :	23-05-2022 to 27-05-2022
Event place (city) :	Singapore
Event country :	Singapore
Abstract :	[en] Reconfigurable intelligent surfaces (RISs) have recently gained significant interest as an emerging technology for future wireless networks. This paper studies an RIS-assisted propagation environment, where a single-antenna source transmits data to a single-antenna destination in the presence of a weak direct link. We analyze and compare RIS designs based on long-term and short-term channel statistics in terms of coverage probability and ergodic rate. For the considered optimization designs, closed-form expressions for the coverage probability and ergodic rate are derived. We use numerical simulations to validate the obtained analytical framework. Also, we show that the considered optimal phase shift designs outperform several heuristic benchmarks.
Permalink :	http://hdl.handle.net/10993/53392
DOI :	10.1109/ICASSP43922.2022.9746584

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