Algorithms for joint channel estimation and data recovery-application to equalization in underwater communications

Methods for joint ocean-channel estimation and data recovery are derived using an optimal, maximum likelihood (ML) estimation criterion. The resulting ML problems may be complex, thus iterative algorithms are used, e.g. the expectation-maximization (EM) algorithm. The different methods correspond to different assumptions about the ocean channel. The theoretical derivation of these methods as well as preliminary results on simulated ocean data experiments are presented.<>