Accurate approximation to channel distributions of cascaded RIS-aided systems with phase errors over Nakagami-m channels

Zhakipov, Zhandos, Rabie, Khaled M ORCID: https://orcid.org/0000-0002-9784-3703, Li, Xingwang and Nauryzbayev, Galymzhan (2023) Accurate approximation to channel distributions of cascaded RIS-aided systems with phase errors over Nakagami-m channels. IEEE Wireless Communications Letters, 12 (5). pp. 922-926. ISSN 2162-2337

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Official URL: https://doi.org/10.1109/LWC.2023.3251647

Abstract

Reconfigurable intelligent surfaces (RISs) are a promising technology foreseen to drive the development of beyond-fifth-generation (B5G) wireless networks. This letter proposes a novel accurate approximation to the channel distribution of cascaded RIS-aided wireless networks, with a reasonable assumption of phase errors, over Nakagami- m fading channels. Using the approximation, the probability density function (PDF) and outage probability (OP) expressions are derived for the end-to-end cascaded RIS-aided communication. Obtained PDF and OP formulas are valid for any number of cascaded RISs, n , and reflecting elements per individual RIS, N. The approximation accuracy is validated using the Kolmogorov-Smirnov goodness-of-fit test. Analytical results are verified by Monte Carlo simulations under different system parameters. Finally, derived expressions have been used to illustrate the impact of various important system parameters on the outage performance of the proposed system.

Item Type:	Article (Article)
Peer-reviewed:	Yes
Date Deposited:	03 Nov 2023 10:28
Publisher:	Institute of Electrical and Electronics Engineers
Additional Information:	© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Faculties > Science and Engineering
Subject terms:	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
URI:	https://mmu-uat.leaf.cosector.com/id/eprint/632944
DOI:	https://doi.org/10.1109/LWC.2023.3251647
ISSN	2162-2337
e-ISSN	2162-2345

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