Multi-Scale Single-Bit RP-EMS Synthesis for Advanced Propagation Manipulation through System-by-Design

Oliveri, G.; Rocca, P.; Salucci, M.; Erricolo, D.; Massa, A.

doi:10.48550/arxiv.2203.04399

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…The availability of RIS was discussed in [6,7]. The work in [8] represents a sort of RIS design to enhance the beam-shaping capability. The difference between RIS and relaying was introduced in [9].…”

Section: Introductionmentioning

confidence: 99%

Position Design for Reconfigurable Intelligent-Surface-Aided Indoor Visible Light Communication Systems

Zhang

Guo

2022

Electronics

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As an emerging technology, reconfigurable intelligent surfaces (RISs) have been investigated to apply to visible light communication (VLC) systems to enhance the transmission capability of the systems, recently. However, the optimization of RIS location in VLC has not been studied. In this study, we first investigated RIS positioning design in VLC. Specifically, we set two indoor VLC scenarios with a VLC RIS composed of a mirror array. We set the achievable rates in different scenarios as the utility functions to optimize the position of the RIS array according to the placement of the access point (AP) and user. We found that the problems are nondeterministic polynomial (NP)-hard. Aiming at the different optimization problems, the particle swarm optimization (PSO) algorithm was used to confirm the optimal position of the RIS array. Unlike the traditional algorithm, we added an adaptive mutation mechanism to the algorithm to guarantee the randomness of the particle to search for the optimal solution. Finally, our simulation results showed that the proper position design of the RIS array can improve the communication performance to a greater degree, while the computational complexity required to solve the position optimization problems through the PSO algorithm can be significantly reduced compared with that required for the exhaustive search method in the case where both of the algorithms find the optimal solution.

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