Robust communications in uncertain shallow water acoustic channels

Underwater acoustic communications systems need to cope with multipath, time-varying propagation conditions. Maximum-likelihood (ML) estimators for recovering the transmitted signal under three different models for shallow water acoustic communications are presented. The models use different levels of knowledge on the propagation conditions, resulting in estimation methods with different levels of robustness or sensitivity to channel mismatch. In addition, a constant modulus (CM) algorithm is used in order to handle CM signals. The three estimators are compared for Gaussian and BPSK signals. The results show that in the presence of channel mismatch, using robust estimators can significantly improve the estimator performance