Impact of Dynamic Traffic on Vehicle-to-Vehicle Visible Light Communication Systems

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    Abstract

    In this article we studies the impact of dynamic vehicular traffic density on the signal-to-noise-ratio and the associated bit-error-rate (BER) performance of vehicle-to-vehicle visible light communication (V2V-VLC) systems. The article uses traffic data from the M42 and M6 motorways in the U.K. to investigate the probability of coexistence of other vehicles in the adjacent lanes, which induce interference and act as potential reflectors. The results show that the probability of coexistence of other vehicles in the adjacent lanes is lane-independent and it increases during the rush hours to 90%, while it decays to less than 10% during the off-peak and early morning hours. The intervehicular distance and the BER performance vary widely between different lanes and different periods of the day. The results also show that the BER performance of V2V-VLC system with non-line-of-sight (NLOS) component and with LOS component are comparable at rush hours. However, high BER values are predicted during the off-peak hours for NLOS components of the channel.
    Original languageEnglish
    Pages (from-to)3512-3521
    Number of pages10
    JournalIEEE Systems Journal
    Volume16
    Issue number3
    Early online date17 Aug 2021
    DOIs
    Publication statusPublished - 1 Sep 2022

    Bibliographical note

    © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Funder

    The authors would like to thank Highways England and Mott MacDonald for providing us with traffic data that were also used in the InnovateUK funded project UKCITE, grant 102581. This work was carried out as a self-funded PhD programme at Coventry University, UK. O Haas was funded by Assured CAV Parking, innovate-UK grant 105095, Cheng-Xiang Wang was funded by the National Natural Science Foundation of China (NSFC) under Grant 61960206006 and the EU H2020 RISE TESTBED2 project under Grant 872172.

    Keywords

    • Dynamic traffic conditions
    • dynamic vehicular traffic density
    • vehicular communication channel model
    • vehicular communications
    • visible light communication (VLC)

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