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Heterogeneous VLC/RF multi-hop cluster V2V channel allocation algorithm based on equivalent SINR.

RongRong Ying, Jun Sang, Xingyue Shen

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    This study introduces a new algorithm for vehicular ad hoc networks (VANETs) that combines visible light communication (VLC) and radio frequency (RF) to improve data transmission quality and speed between vehicles.

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    Area of Science:

    • Vehicular communication networks
    • Wireless communication systems
    • Network protocols

    Background:

    • Vehicular ad hoc networks (VANETs) face challenges with low communication quality and limited transmission rates.
    • Existing communication models often struggle to provide reliable connectivity in dynamic vehicle environments.

    Purpose of the Study:

    • To develop a heterogeneous visible light communication (VLC) and radio frequency (RF) multi-hop communication model for VANETs.
    • To present a novel channel allocation algorithm (NCAABES) that enhances vehicle-to-vehicle (V2V) communication efficiency.

    Main Methods:

    • A multi-hop communication model based on vehicle node clustering is established.
    • A heterogeneous VLC/RF channel allocation algorithm (NCAABES) is introduced, utilizing equivalent Signal to Interference plus Noise Ratio (SINR).
    • Relay nodes are employed for multi-hop communication when direct links are degraded.

    Main Results:

    • The NCAABES algorithm demonstrated significant improvements in SINR compared to existing schemes (MCSVDD, VLCnet, RFnet).
    • NCAABES achieved the lowest Bit Error Rate (BER) across various vehicle densities and transmission power levels.
    • The algorithm effectively enhances communication quality and transmission rates in VANETs.

    Conclusions:

    • The proposed NCAABES algorithm offers a robust solution for improving communication quality and efficiency in VANETs.
    • Heterogeneous VLC/RF integration with intelligent channel allocation is crucial for next-generation vehicular networks.
    • The findings suggest a more reliable and faster communication infrastructure for connected vehicles.