A soft decision-directed blind equalization algorithm applied to equalization of mobile communication channels

A new approach to decision-directed (DD) blind equalization is introduced based on a neural network classification technique. The new DD algorithm, the soft decision-directed equalization algorithm, is most effective for reconstructing binary phase shift keying and quadrature phase shift keying signals. The new DD blind equalizer can converge in closed eye situations. In the simulations, the performance of the soft DD algorithm was illustrated by applying it to a two-dimensional digital mobile communications system. A time-varying multipath fading channel model was used as the transmission medium. The performance of the soft DD blind equalization algorithm is compared to that of the standard DD algorithm, the maximum-level-error (MLE) algorithm, and the fast recursive least squares decision-feedback equalization (FRLS-DFE) algorithm. The simulation results demonstrate the improvement in performance achievable with the proposed soft DD equalization algorithm