A Rao-Blackwellized Particle Filter for Blind Equalization of Frequency-Selective Channels with Unknown Order and Noise Variance

We propose in this paper a new particle filtering algorithm for blind equalization of FIR frequency-selective communication channels corrupted by additive Gaussian noise, assuming that both the channel order and noise variance are unknown. The proposed algorithm integrates out analytically the unknown parameters using a modified sequential importance sampling technique. We verify via numerical simulations that the proposed method leads to near optimal performance, greatly outperforming traditional methods under noise variance mismatch.