The book focuses on the innovative application of Visible Light Communication (VLC) within the realm of vehicular networks and intelligent transportation systems (ITS). VLC promises significant advantages as a supplementing technology to radio wireless communications, including huge bandwidth, low interference due to low confinement. VLC also enables the usage of existing LED head/taillights in most vehicles as wireless transmitters.
The scope of the document encompasses various aspects of VLC in vehicular contexts, including its architecture, channel modeling, noise considerations, and performance analysis. Advance topics such as MIMO, Optical OFDM, Precoding\Equalization and adaptive noise cancellation are studied in detail in the realms of VLC. Furthermore, it examines the potential of VLC to complement existing communication standards, such as IEEE 802.11p and Cellular V2X, especially in scenarios demanding low latency and high reliability communications, all these with realistic simulation results.
The approach taken in the book involves a comprehensive analysis of VLC systems' architecture, including the roles of VLC emitters and receivers, and the characteristics of the VLC channel. It covers research directions to overcome various hurdles to overcome the challenges in vehicular VLC applications including the incorporation of Machine Learning (ML) and Artificial Intelligence (AI) algorithm. By delving into both theoretical and practical frameworks, the book aims to present a holistic view of how VLC, when integrated with AI and ML technologies, can revolutionize communication in autonomous vehicles and contribute to safer and more efficient transportation systems.
The scope of the document encompasses various aspects of VLC in vehicular contexts, including its architecture, channel modeling, noise considerations, and performance analysis. Advance topics such as MIMO, Optical OFDM, Precoding\Equalization and adaptive noise cancellation are studied in detail in the realms of VLC. Furthermore, it examines the potential of VLC to complement existing communication standards, such as IEEE 802.11p and Cellular V2X, especially in scenarios demanding low latency and high reliability communications, all these with realistic simulation results.
The approach taken in the book involves a comprehensive analysis of VLC systems' architecture, including the roles of VLC emitters and receivers, and the characteristics of the VLC channel. It covers research directions to overcome various hurdles to overcome the challenges in vehicular VLC applications including the incorporation of Machine Learning (ML) and Artificial Intelligence (AI) algorithm. By delving into both theoretical and practical frameworks, the book aims to present a holistic view of how VLC, when integrated with AI and ML technologies, can revolutionize communication in autonomous vehicles and contribute to safer and more efficient transportation systems.
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