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A Grey Wolf Optimiser (GWO)-Based RIS Phase Shift Design for a RIS-Assisted Multi-Antenna System
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AI
DOI：10.1109/LCOMM.2024.3423013.png)
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Abstract
En 中文
Reconfigurable Intelligent Surfaces (RIS) offer numerous interesting advantages, including the ability to dynamically rearrange wireless channels to enhance communication system performance. The design of RIS phase shift has received more attention, and the majority of present methods for optimising spectral efficiency (SE) involve complex matrix inversions that increase the overall complexity. In this study, we present a novel RIS phase shift design approach that uses a grey wolf optimizer (GWO) to maximise the user's spectral efficiency. The proposed GWO approach creates several grey wolf search agents. Based on SE performance, each search agent's position is modified in iteration to determine the optimal choice. The outcomes of the simulation demonstrate that the proposed GWO-based algorithm can quickly converge, consume significantly less time, and produce noticeable improvements in spectral efficiency.
Keywords:
Vectors
Spectral efficiency
Optimization
Array signal processing
Signal to noise ratio
Linear programming
Statistics
RIS
grey wolf optimizer
spectral efficiency
energy efficiency
discrete phase shift
Journal
IF:
4.4
Papers:
1.3W
Citations:
2.2W
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