Kernel Recursive Maximum Versoria Criterion Based Post-Distorter for VLC Using Kernel-Width Sampling

Visible light communication (VLC) has emerged as a potential candidate for next generation wireless systems. However, nonlinear characteristics of emitting diode (LED), user-mobility, and DC-bias fluctuations are the major factors that limit throughput VLC link, makes overall additive distortion non-Gaussian distributed. To mitigate this noise processes encountered in systems due to LED nonlinearity, recently random Fourier features (RFF) based kernel recursive maximum Versoria criterion (KRMVC) post-distortion algorithm is proposed, which delivers better performance compared classical polynomial series, least squares (KRLS) algorithms incorporation higher order statistics error. RFF-KRMVC sensitive choice kernel-width, results approximation errors imperfect kernel-width. This paper proposes novel using kernel-width sampling (KWS) technique called RFF-KWS-KRMVC, implements under hyperparameter-free finite memory budget. Furthermore, analytical expressions mean square error, error rate quantified proposed RFF-KWS-KRMVC post-distorter, corroborated by Monte-Carlo simulations performed over standard channel models.