Channel estimation for wideband underwater visible light communication: a compressive sensing perspective.

With the rapid development of light emitting diode (LED), visible light communication (VLC) becomes an important technique for information transmission including underwater applications. However, accurate channel estimation for underwater VLC is still challenging due to the complex environment of the underwater VLC channel. In this paper, by utilizing a proper approximation, where the channel attenuation is linear with the frequency, a new compressive sensing (CS) based channel estimation approach is proposed. Utilizing the sparse property of the reflection path length for the underwater VLC channel, the CS framework is modeled to estimate the reflection path length, which can further recover the underwater VLC channel. Moreover, a Bayesian CS recovery algorithm is investigated to overcome the problem of high coherence for the sensing matrix which outperforms the conventional greedy algorithm such as orthogonal matching pursuit (OMP). Simulation results illustrate that our proposed channel estimation for underwater VLC systems has a superior performance which can significantly reduce the pilot overhead, improve the spectral efficiency, and enhance the estimation accuracy.