Abstract
This paper exploits the applications of evolutionary algorithms to solve a challenging category of optimization problems in 6G mobile networks, particularly focusing on communication reliability with modulated signals of reconfigurable intelligent surface (RIS)-assisted multiple input multiple output (MIMO) systems. By deriving the analytical downlink symbol error rate (SER) of each user as a multivariate function of both the phase-shift and beam-forming vectors, we introduce a novel average SER minimization problem subject to the transmitted power budget and phase shift coefficients, which is NP-hard. By incorporating the differential evolution (DE) algorithm as a pivotal tool and an efficient local search to overcome the local optimum for optimizing the intricate active and passive beamforming variables, the non-convexity of the considered SER optimization problem can be effectively handled. Numerical results indicate that the proposed joint active and passive beamforming design is superior to the other benchmarks.
Original language | English |
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Title of host publication | GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion |
Publisher | Association for Computing Machinery |
Pages | 651-654 |
Number of pages | 4 |
ISBN (Electronic) | 9798400704956 |
Publication status | Published - 01 Aug 2024 |
Event | GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion - Melbourne, Australia Duration: 14 Jul 2024 → 18 Jul 2024 |
Publication series
Name | GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion |
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Conference
Conference | GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion |
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Country/Territory | Australia |
City | Melbourne |
Period | 14/07/2024 → 18/07/2024 |
Bibliographical note
Publisher Copyright:© 2024 Copyright held by the owner/author(s).
Keywords
- beamforming design
- communication reliability
- differential evolution
- RIS-assisted MIMO
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Control and Optimization
- Discrete Mathematics and Combinatorics
- Logic