Underwater VLC channel estimation based on Kalman filtering for direct current optical- and asymmetrically clipping optical- orthogonal frequency division multiplexing techniques

Abstract

In this paper, we suppose an underwater optical wireless communication (UOWC) system, where the communication utilizes visible light communication for its advantages as wide spectrum, high data rate and high accuracy. The novelty of this paper is focused on improving the channel estimation between transmitter and receiver, where using Kalman Filter (KF) for channel estimation in UOWCs achieves the best results as compared to other traditional channel estimation methods. The scenario of this paper is summarized in transmitting data from transmitter to receiver via underwater harbor and coastal channels. Two channel models are utilized: weighted double gamma functions (WDGF) and a combination of exponential and arbitrary power function (CEAPF). The modulation technique used is optical orthogonal frequency division multiplexing with two kinds: direct current optical orthogonal frequency division multiplexing (DCO-OFDM) and asymmetrically clipping optical orthogonal frequency division multiplexing (ACO-OFDM). Three different techniques are used for channel estimation: Least Square (LS), minimum mean square error (MMSE), and KF. The simulation results reveal that the ACO-OFDM modulation technique with CEAPF channel modeling using KF achieves the lowest bit error rate (BER) compared to other channel estimation methods. The improvement percentage at BER = 10−1 is 13.3% for ACO-OFDM over DCO-OFDM with CEAPF in coastal water and is is 9.3% for WDGF. This indicates that CEAPF performs about 4% better than WDGF for ACO-OFDM than DCO-OFDM in terms of channel estimation.