Applications of particle filtering to communications: A review

In the past few years, particle filtering has emerged as a powerful methodology for solving problems in communications. Many such problems can be represented as dynamic state-space models that involve nonlinear functions and non- Gaussian noise. These problems are very difficult to solve with classical methods, and as an alternative approach, particle filtering is particularly attractive. In this paper we review the literature of particle filtering that emphasizes applications to blind equalization, blind detection over frequency non-selective dispersive channels, multiuser detection, and estimation and detection of space-time trellis codes.