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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...
We describe in this paper novel consensus-based distributed particle filtering algorithms which are applied to cooperative blind equalization of frequency-selective channels in a network with one transmitter and multiple receivers. The proposed algorithms employ parallel consensus averaging iterations to evaluate the product of some node-dependent quantities across the receiver network, thus eliminating...
We introduce in this paper a new distributed sequential Monte Carlo (SMC) algorithm for blind equalization of frequency-selective broadcast channels. In the considered setup, multiple receiving nodes sense independently distorted versions of the same broadcast signal and cooperate to recover it. The proposed approach innovates by using parametric approximations based on the Variational Bayes (VB)...
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