The Blind Equalization Method Based on Particle Filter Theory

In this paper, particle filter theory and its Application in blind equalization are presented. The basic idea of particle filter is the recursive computation of relevant probability distributions using discrete random measures composed of the particles and its weights. Compared with the other methods for equalization, the advantage of particle filtering is in that exploited approximation doesn't involve linearization around current estimates but rather approximations in the representation of the desired distribution by discreet random measures. The simulation shows that the algorithm is feasible even under the conditions of lower signal-to-noise ratio.