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  • Placement Optimization and Power Management in a Multiuser Wireless Communication System With Reconfigurable Intelligent Surfaces
Title: Placement Optimization and Power Management in a Multiuser Wireless Communication System With Reconfigurable Intelligent Surfaces
Employing Reconfigurable Intelligent Surface (RIS) is an advanced strategy to enhance the efficiency of wireless communication systems. However, the number and positions of the RISs elements are still challenging and require a smart optimization framework. This paper aims to optimize the number of RISs subject to the technical limitations of the average achievable data rate with consideration of the practical overlapping between the associated multi-RISs in wireless communication systems. In this regard, the Differential evolution optimizer (DEO) algorithm is created to minimize the number of RIS devices to be installed. Accordingly, the number, positions, and phase shift matrix coefficients of RISs are then jointly optimized using the intended DEO. Also, it is contrasted to several recent algorithms, including Particle swarm optimization (PSO), Gradient-based optimizer (GBO), Growth optimizer (GO), and Seahorse optimization (SHO). The outcomes from the simulation demonstrate the high efficiency of the proposed DEO and GO in obtaining a 100% feasibility rate for finding the minimum number of RISs under different threshold values of the achievable rates. PSO scores a comparable result of 99.09%, while SHO and GBO attain poor rates of 66.36% and 53.94%, respectively. Nevertheless, the excellence of the created DEO becomes evident through having the lowest average number of RISs when compared to the other algorithms. Numerically, the DEO drives improvements by 5.13%, 15.68%, 30.58%, and 51.01% compared to GO, PSO, SHO and GBO, respectively.  more » « less
Award ID(s):
2210252
PAR ID:
10596634
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
IEEE Open Journal of the Communications Society
Volume:
5
ISSN:
2644-125X
Page Range / eLocation ID:
4186-4206
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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