Allianced iterative compressed sensing algorithm eliminating clipping noise in underwater acoustic communication system

Due to the characteristics of the underwater acoustic (UWA) channel especially the limited bandwidth, Orthogonal frequency division multiplexing (OFDM) is widely used because of its high spectrum efficiency and ability in anti-multipath fading. However, OFDM also has its drawbacks, one of which is the relatively high peak-to-average ratio (PAPR). The problem leads to saturation in the power amplifier and consequently distorts the signal which is not allowed in the underwater acoustic communication. Clipping and C companding as the most classic and convenience algorithm is widely applied to address the high PAPR. But traditional c companding is not suitable for the underwater acoustic field and meanwhile clipping introduces additional noise which degrades the system's performance. Based on these, an improved c companding combined with clipping is promoted. As clipping algorithm introduces clipping noise into the communication system which can be recognized as sparse, compressed sensing (CS) is proposed to estimate it. The scheme exploited pilot tones and data tones instead of reserve tones, which is different from the previous works and causes less loss of data rate. Also, to minimizing the influence of underwater acoustic channel, compressed sensing (CS) in channel estimating is also adopted during mitigating clipping noise, which can provide more accurate channel characteristics than LS or MMSE algorithm. The iterative CS algorithm can significantly improve the quality of the communication system even in low SNR.