Design and analysis of allan variance based adaptive noise canceller for vehicular visible light communication

Visible light communication (VLC) can serve as a supplement to the radio frequency to address its inherent constraints. VLC can be easily implemented in vehicles using their existing LED components. Sunlight interference can cause significant variation in the background noise powers, leading to signal-to-noise ratio (SNR) degradation in vehicular VLC (VVLC) communication. Hence, it is necessary to improve the performance besides interference. Allan variance is a temporal analysis approach that can extract the noise from the received data. In this article, an Allan variance-based adaptive noise canceller for a VVLC system is proposed and evaluated. Based on the Allan variance obtained, the step size and the number of taps of the adaptive filter are adjusted for superior performance. This proposed filter effectively mitigates the pronounced autocorrelation induced by the noise interference. It yields about an 85% bit error rate (BER) reduction compared to the conventional filter. This improved convergence underscores the potential for enhanced communication performance and reliability. The balanced distribution of the Manchester encoded signal outperforms NRZ encoding. Thus, this work contributes a novel adaptive noise canceller design for a VVLC system and also provides valuable insights to the significance of Allan variance in the VLC system performance.