Visible Light Communication (VLC) has emerged as an attractive alternative to radio frequency (RF) communication, due to its abundant, license-free bandwidth and cost effectiveness. The visible light spectrum is much larger than the entire RF spectrum, and it is largely unexplored. VLC has proved its viability in automotive applications to provide short range vehicle-to-vehicle and vehicle-to-infrastructure communications due to increased deployment of LED lights and image sensors in modern vehicles. However, there are a few challenges that need to be addressed before global adaptation. A must-read for researchers, graduate students and industry professionals who work in the VLC field, this book investigates the suitability of VLC for vehicular communications from a fundamental wireless communication standpoint. Mathematically accurate channel models are developed, and advanced signal processing approaches to overcome challenges such as sunlight interference, shadowing and fast changing channels are described. Results are verified through simulation with realistic parameters.

The book explores the innovative application of Visible Light Communication (VLC) in enhancing autonomous vehicles and intelligent transportation systems, emphasizing the integration of AI and Machine Learning to improve communication and safety in vehicular networks. It dissects the architecture, performance analysis, and future challenges of VLC technology while highlighting its potential to complement existing communication standards in real-time vehicular scenarios.

Visible Light Communication (VLC) has emerged as an attractive alternative to radio frequency (RF) communication, due to its abundant, license-free bandwidth and cost effectiveness. The visible light spectrum is much larger than the entire RF spectrum, and it is largely unexplored. VLC has proved its viability in automotive applications to provide short range vehicle-to-vehicle and vehicle-to-infrastructure communications due to increased deployment of LED lights and image sensors in modern vehicles. However, there are a few challenges that need to be addressed before global adaptation. A must-read for researchers, graduate students and industry professionals who work in the VLC field, this book investigates the suitability of VLC for vehicular communications from a fundamental wireless communication standpoint. Mathematically accurate channel models are developed, and advanced signal processing approaches to overcome challenges such as sunlight interference, shadowing and fast changing channels are described. Results are verified through simulation with realistic parameters.

The book explores the innovative application of Visible Light Communication (VLC) in enhancing autonomous vehicles and intelligent transportation systems, emphasizing the integration of AI and Machine Learning to improve communication and safety in vehicular networks. It dissects the architecture, performance analysis, and future challenges of VLC technology while highlighting its potential to complement existing communication standards in real-time vehicular scenarios.