1. Advanced communication techniques of sparse channel sensing and nonbinary LDPC coding. Underwater acoustic channels are naturally sparse, but how to effectively exploit the sparsity is a challenging task. We will investigate the recently developed “compressive sensing” algorithms for sparse channel estimation in the context of multicarrier acoustic communications. On the other hand, channel ...

Estimating time-difference-of-arrival (TDOA) remains a challenging task when acoustic environments are reverberant and noisy. Blind channel identification approaches for TDOA estimation explicitly model multipath reflections and have been demonstrated to be effective in dealing with reverberation. Unfortunately, existing blind channel identification algorithms are sensitive to ambient noise. Th...

Multipath channels often exhibit sparse structures in multicarrier underwater acoustic (MC-UWA) communication systems. Conventional linear channel estimators, such as least squares (LS) and minimum mean square error (MMSE) are considered as optimal solutions under the assumption of rich multipath. However, they often result in low spectral efficiency due to neglect of the sparsity in multipath ...

This paper presents a Clustering Based Blind Channel Estimator for a special case of sparse channels – the zero pad channels. The proposed algorithm uses an unsupervised clustering technique for the estimation of data clusters. Clusters labelling is performed by a Hidden Markov Model of the observation sequence appropriately modified to exploit channel sparsity. The algorithm achieves a substan...

Motivated by the compressed sensing sparse channel estimation problem, the complete channel state is sparse under the conditions of low spectral efficiency. Other than traditional method of looking for the perception of spectrum holes, this paper focus on the sparse of occupied sub-channels. Based on compressed sensing technology, a novel cooperative wideband spectrum sensing method is proposed...