A survey on machine learning algorithm applications in visible light communication systems

Maha Sliti, Manel Mrabet, Mouna Garai, Lassaad Ben Ammar

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Visible Light Communication (VLC) technology offers a promising alternative for high-speed data transfer due to its ability to simultaneously illuminate and transport data. This research studies the application of Machine Learning (ML) algorithms for the purpose of addressing several issues associated with VLC technology. These challenges include the reduction of non-linearity, channel estimation, detection of modulation format, localization, enhancement of security, optimization of mobility, and management of resources. ML algorithms have the potential to enhance the efficiency and reliability of VLC systems, ensuring that data flow is uninterrupted. Additionally, the study analyzes the challenges that are involved with the application of ML algorithms in VLC technology as well as the potential future research topics that could be pursued.

Original languageEnglish
Article number1351
JournalOptical and Quantum Electronics
Volume56
Issue number8
DOIs
StatePublished - Aug 2024

Keywords

  • Applications
  • Machine learning algorithms
  • Open research directions
  • Visible light communication (VLC)

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