Bio-inspired optimization methods for visible light communication: a comprehensive review

被引：0

作者：

Martin Dratnal ^{[1
]}

Lukas Danys ^{[1
]}

Radek Martinek ^{[1
]}

机构：

[1] Faculty of Electrical Engineering and Computer Science,Department of Cybernetics and Biomedical Engineering

[2] VSB–Technical University of Ostrava,undefined

来源：

Artificial Intelligence Review | / 58卷 / 8期

关键词：

Artificial intelligence; Bio-inspired algorithms; Channel equalization; Genetic algorithm; Swarm intelligence; Visible light communication.;

D O I：

10.1007/s10462-025-11251-5

中图分类号：

学科分类号：

摘要：

Visible light communication (VLC) offers a promising alternative to traditional radio frequency communication due to its greater bandwidth, energy efficiency, and security advantages. This paper presents a comprehensive review of bio-inspired optimization algorithms, including swarm intelligence and genetic algorithms, that enhance the performance and robustness of VLC systems. These techniques have demonstrated significant potential in addressing challenges such as channel optimization and noise reduction. However, despite their advantages, bio-inspired algorithms also face limitations, including computational complexity and limited adaptability to dynamic real-world conditions. Additionally, the integration of bio-inspired methods with artificial intelligence (AI) may further enhance their adaptability and efficiency in VLC systems. This review highlights both the opportunities and challenges associated with bio-inspired optimization in VLC and provides insights into future directions for research and practical implementation, which will focus on developing more efficient and scalable bio-inspired approaches that can operate in highly variable environments while minimizing energy consumption.

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