Distributed particle filtering for blind equalization in receiver networks using marginal non-parametric approximations

This paper introduces a novel distributed particle filtering algorithms for the blind equalization of frequency-selective channels in a setup where a single transmitter broadcasts to multiple remote receivers. The algorithm computes particle-independent non-parametric approximations of some posterior probability functions, which are propagated between nodes via minimum-consensus iterations. We verify via numerical simulations that the proposed algorithms exhibit bit error rate (BER) performances markedly superior to that of particle-filtering-based isolated receivers with communication requirements far inferior to that of previous distributed algorithms.