A novel algorithm to mitigate the effect of clipping in orthogonal frequency division multiplexing underwater communication acoustic sensor system

Distinctive features of underwater communication channel pose significant challenges to effective underwater acoustic communication. Due to bandwidth limitation, orthogonal frequency division multiplexing is widely used for its high spectrum efficiency. However, orthogonal frequency division multiplexing also has its shortcomings, one of which is the relatively high peak-to-average power ratio, which leads to saturation in the power amplifier and consequent distortion of the signal. Clipping is the most commonly used method to address the high peak-to-average power ratio; however, it introduces additional noise resulting in degradation of the system’s performance. This article proposes a compressed sensing technique for mitigation of the clipping noise, which exploits pilot and data tones instead of reserved tones, thus making it distinct from the previous works and improves data rate. Moreover, in contrast with previous works, the channel is also estimated using compressed sensing technique, which provides more accurate channel characteristics for estimating the clipping noise than traditional methods like least square or minimum mean squared error. The better performance of the proposed Iterative compressed sensing algorithm is proved in simulations as well as in a pool experiment using acoustic wave sensors.