Equalization based on particle filtering for mobile station receivers

In this paper, we present the application of particle filtering to build efficient equalizer structures for mobile station terminals. We begin by recalling the theory of particle filtering and we put the emphasis on the key point of such a technique, the sampling importance resampling (SIR) or the sequential importance sampling (SIS). Then, we present a mathematical model which allows to represent the transmitted symbols as the state of a stochastic system which can be estimated by particle filters. Furthermore, we propose a basic equalizer structure with particle filters and we investigate several improvement strategies which help to obtain better estimation results with a lower number of particles. Finally, simulation results in the context of GSM/EDGE are given which show that the proposed particle filter equalizer, outperforms the well known extended Kalman filter.