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

    Student thesis: Doctoral ThesisDoctor of Philosophy


    Due to the directional nature of the visible light signals propagation, the performance of visible light communications (VLC) systems depends on the geometry of the link. In dynamic vehicle to-vehicle VLC (V2V-VLC) systems, the geometry of the VLC link changes continuously due to the unpredictable movement patterns of the transmitter, receiver and surrounding vehicles. This thesis investigates the impact of dynamic traffic conditions during different times of the day to establish a statistical channel model for the V2V-VLC systems. The study considers the geometrical variation due to the variable inter-vehicle spacing and radiation pattern of vehicles’ sources. The results showed that the statistical model of channel path loss is given by a convolution of the distributions of the inter-vehicle spacing and the radiation pattern of vehicles’ sources. Based on the measured traffic, the line of sight (LOS) and non-LOS path loss are developed for the radiation pattern of vehicles’ sources which depends on the manufactures. The study shows that the LOS path loss distribution depends on the radiation pattern, whereas it has a less significant effect on the non-LOS path loss distribution. Furthermore, the existence of multiple reflectors decreases path loss and enhances the communication link’s performance. Different weather conditions add attenuation that increases the mean path loss value without changing the statistical distribution of the path loss. Studying the temporal properties of the V2V-VLC channel shows that the channel can be described as time-variant non-stationary with flat and slow fading behaviour. The bit-error-rate (BER) and signal-to-noise (SNR) ratio performance, when the on-off-keying (OOK) modulation scheme is used, depends on the dynamic traffic and the existence of other vehicles in the adjacent lanes. A difference of at least 2 dB between the required SNR values to achieve comparable BER performance in different lanes is observed.
    Date of Award2021
    Original languageEnglish
    Awarding Institution
    • Coventry University
    SupervisorSujan Rajbhandari (Supervisor), Zahir Ahmad (Supervisor) & Olivier Haas (Supervisor)

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