Low Complexity Channel Estimation for Fractionally Sampled Underwater Visible Light Communication

In practical underwater visible light communication (UVLC) scenarios, the communication links inevitably suffer from many stochastic channel effects including multi-path dispersion, scattering, turbulence, etc., and/or from the mobility of the transceiver, therefore resulting in a time-varying, location dependent non-stationary propagation environment. Naturally, how to design a cost-efficient channel estimation (CE) for UVLC systems becomes a significant technical challenge, due to the complicated channel characteristics and implementational constraints in underwater environment. In this paper, we propose a class of Bayesian CE algorithms for fractionally-sampled optical orthogonal frequency division multiplexing (FS-OOFDM) assisted UVLC systems. The so-called Sherman-Morrison formula (SMF) based CEs (SMF-CEs) exploit the property of rank-one structure of the channel covariance and autocorrelation matrices in the delay domain, to achieve a superior performance at a modest computational complexity.