Simulated Annealing Genetic Algorithm based RIS Phase Optimization in the High-Speed Communication of the Railways

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

The aim is to solve the problem of unstable and discontinuous signal transmission in the wireless communication of the High-Speed Railway (HSR). In the RIS mobile wireless communication system for highways, the active radiation and the RIS discrete phase at the basis station are jointly optimized in order to maximize the system capacity under the restrictions of the transmitting strength of the basic station and RIS discrete phase shift. Firstly, the closed-form solution of the base station beam allocation is derived using the generalized Rayleigh entropy theorem. Then the Simulated Annealing (SA) algorithm was invented as an improvement on the standard Genetic Algorithm (GA). The enhanced genetic algorithm is used to solve discrete phase of RIS. The results of the simulation show that the overall effectiveness of the system with RIS is significantly higher than the system without RIS. The SA-GA, which significantly outperforms standard genetic algorithm and achieves fast convergence.

Original languageEnglish
Title of host publicationProceedings - 2023 8th International Conference on Communication, Image and Signal Processing, CCISP 2023
EditorsJing Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages564-568
Number of pages5
ISBN (Electronic)9798350305838
DOIs
StatePublished - 2023
Externally publishedYes
Event8th International Conference on Communication, Image and Signal Processing, CCISP 2023 - Hybrid, Chengdu, China
Duration: 17 Nov 202319 Nov 2023

Publication series

NameProceedings - 2023 8th International Conference on Communication, Image and Signal Processing, CCISP 2023

Conference

Conference8th International Conference on Communication, Image and Signal Processing, CCISP 2023
Country/TerritoryChina
CityHybrid, Chengdu
Period17/11/2319/11/23

Keywords

  • discrete
  • genetic algorithm
  • high-speed rail
  • reconfigurable intelligent surface
  • simulated annealing algorithm

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