Abstract
Abstract Ambient light noise is a major cause of performance degradation in visible light communication (VLC) systems. It affects outdoor VLC applications in terms of signal to noise ratio (SNR) and bit error rates (BER). Sunlight plays an important role in increasing the effects of ambient noise on VLC signal. VLC is suggested as a promising communication mode between two vehicles, in vehicle-to-vehicle (V2V) communication systems. In this paper, we discuss and propose an efficient method to overcome the effect of sunlight irradiance in VLC links used for V2V communication. We propose K-Nearest Neighbour (KNN), a machine learning-based adaptive filter to combat the effects of solar irradiance. Our smart filter can adapt itself according to varying noise conditions and help to achieve acceptable BER in support of reliable communications.
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