Adaptive Blind Source Separation in Underwater Wireless Speech Communication

In this article, based on Blind Source Separation (BSS) often used in the cocktail party problem, a new online BSS algorithm SIRP-NG is developed. Utilizing on the Information Maximization principle and the Infomax algorithm, it uses Spherically Invariant Random Process (SIRP) to model the univariate band-limited speech signals used in telephone and underwater wireless communications. The Meijer G function is used to simplify the derivation of the Natural Gradient (NG) algorithm for updating the weight matrix of the unmixing neural network. Simulation results showed significant improvement in terms of the signal-to-interference ratio criterion. For the more complex multipath propagation channels, Time-Frequency Domain BSS algorithm is discussed.