Blind estimation and equalization of time-varying channels using the interacting multiple model estimator

This work presents an adaptive multiple model blind equalization algorithm based on the interacting multiple model (IMM) estimator to estimate the channel and the transmitted sequence corrupted by intersymbol interference (ISI) and noise. A computationally feasible implementation based on a weighted sum of Gaussian approximation of the density functions of the data signals is introduced. The proposed method avoids the exponential growth of the number of terms used in the weighted Gaussian sum approximation of the plant noise making it practical for real-time processing. Simulations demonstrate that the proposed IMM equalizer yield substantially improved performance compared with the recently proposed equalizer based on a (non-interacting) network of extended Kalman filters.