Distributed rao-blackwellized point mass filter for blind equalization in receiver networks

We describe new Bayesian algorithms for cooperative blind equalization in a network in which the signal broadcast by a single transmitter is received by multiple remote nodes through distinct frequency-selective channels. The algorithms are based on Rao-Blackwellized point mass filters, and approximate the posterior densities of the unknown channel parameters by Gaussian mixtures of fixed order. To keep computations treatable, density mixtures are reduced by a modified version of West´s algorithm. A reduced complexity approach which employs a single mode approximation of some remote quantities is also considered. Via numerical simulations, we verify that the proposed algorithms outperform certain particle-filtering-based algorithms with comparable communication loads.