Channel Estimation Based On Compressed Sensing In High-Speed Underwater Acoustic Communication

The underwater acoustic (UA) channel is dispersive in both time and frequency. It is characterized by the attenuation that increases with signal frequency, time-varying multipath propagation, and low speed of sound (1500m/s) which lead to an extreme Doppler effect. The channel capacity depends on the distance, and may be extremely limited. Therefore, efficient channel estimation and tracking are crucial to coherent high-rate UA communication.Compressed Sensing (CS) theory is a novel signal rocessing theory which is well known in the wireless communication field. This theory can take the advantage of the sparse prior information of the original signal to reconstruct the original signal by signal reconstruction algorithm. This theory has brought a new idea on sparse channel estimation. The channel estimation method based on CS can save lots of training sequences and thus greatly improve the bandwidth efficiency. The popular channel estimation method based on CS theory includes BP method, MP method, OMP method, CoSaMP method and so on.UA channels are sparse, with only a few propagation paths carrying the significant portion of channel energy. In this paper, the channel estimation method based on CS will be applied in UA communication. Compared with traditional UA channel estimation method, the proposed CS channel estimation method takes full advantage of the sparsity of UA channel. It greatly improves the accuracy of channel estimation with a small amount of training sequences. However, the CS channel estimation method only works well in quasi-static channels. In order to keep up with the rapid pace of varying UA channel, too much training sequence is needed in channel estimation. Therefore, to increase the bandwidth efficiency of channel estimation and improve the accuracy of channel estimation, a block-by-block channel tracking method is proposed in this paper. This method combines the CS-based channel estimation and block-by-block channel tracking together. It efficiently exploits the sparsity of the UA channel, and improves the channel tracking capability of UA communication system.The proposed UA channel estimation algorithm is tested in our UA communication experiment conducted in the Indian Ocean off Rottnest Island, Western Australia. At a data rate of8kbps with QPSK constellations, average uncoded bit-error-rates of3%and14%have been achieved over1km and6km ranges, respectively. The experiment result is pretty good.