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Improved Artificial Rabbits Algorithm for Positioning Optimization and Energy Control in RIS Multiuser Wireless Communication Systems

delete2024-06-01
delete10
PRE
AI
A
Ahmed S. Alwakeel
M
M. Ismail
M
Mostafa M. Fouda *
A
Abdullah M. Shaheen
A
Adel Khaled
DOI:10.1109/JIOT.2024.3373563delete
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Abstract

Abstract

En 中文
An innovative method to raise wireless communication systems' efficiency is to use Reconfigurable Intelligent Surface (RIS). Unfortunately, determining the quantity and locations of the RIS elements continues to be difficult, requiring a clever optimization framework. Concerning the practical overlap between the related multi-RISs in wireless communication systems, this article attempts to minimize the number of RISs while considering the average possible data rate and technological constraints. In this regard, a novel enhanced artificial rabbits algorithm (EARA) is developed to minimize the number of RISs to be installed. The novel EARA is inspired by the natural survival strategies of rabbits, including detour eating and random concealment. A more effective method of exploring the search space around the best solution so far is produced by the suggested EARA by combining an upgraded collaborative searching operator (CSO) arrangement. Also, an adaptive time function is included to increase the effect of this exploitation tactic by the increasing number of iterations. The simulation results show that the suggested EARA is highly efficient in reaching the maximum success rate of producing the smallest number of RISs under various feasible rate threshold settings. When EARA is compared to standard artificial rabbits optimizer (ARO), growth optimizer (GO), artificial ecosystem optimizer (AEO), and particle swarm optimization (PSO), the average number of RISs is improved by 5.32%, 6.7%, 16.73%, and 20.06%, respectively. Furthermore, according to simulation data, the EARA outperforms AEO, GO, ARO, and PSO in terms of success rate at delta = 1.4 by 6.66%, 6.66%, 45.43%, and 99%, respectively.
Keywords:
Reconfigurable intelligent surfaces
Optimization
Rabbits
Internet of Things
Array signal processing
Signal to noise ratio
Reflection coefficient
Achievable rate limitation
artificial rabbits algorithm
reconfigurable intelligent surfaces
wireless communication

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

S
Suez University
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970
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E
egyptian knowledge bank (ekb)
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Citations: 84
I
Idaho State University
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