Adaptive Blind Equalization for Chaotic Communication Systems Using Particle Filtering

A blind channel equalization technique for chaotic communications based on particle filtering is proposed in this paper. Particularly, we consider the problem of combating various channel distortions from time varying or unvarying multipath fading. Assuming that the channel coefficients of fading are unknown parameters, blind equalization can be formulated as an estimation problem of mixed nonlinear parameters and states. Conventional methods like extended Kalman filter have relatively poor performance at low SNR. Incorporating the Rao-Blackwellisaion (RB) strategy and roughening noise method, nonlinear filter particle filtering can then be used to estimate the parameters and states sequentially. Simulations confirm that the proposed particle filtering has the improved performance of equalization compared to the extended Kalman filter in chaotic communication, especially at low SNR