Decision Feedback Blind Equalization Based on Recurrent Least Squares Algorithm for Underwater Acoustic Channels

The cost function of constant modulus algorithm (CMA) is simplified to meet second norm form, and the blind equalizer can use recurrent least squares (RLS) algorithm to update the weights. Considering the underwater acoustic channel is usually nonlinear, decision feedback equalizer is used as the blind equalizer. According to the simplified cost function of CMA, the weights of forward part and feedback part of blind equalizer update by RLS algorithm and gradient descent algorithm respectively. Simulation results demonstrate that under conditions of underwater acoustic channel, compared with decision feedback blind equalization based on gradient descent algorithm and transversal equalizer blind equalization based on RLS algorithm, decision feedback blind equalization based on RLS algorithm has faster convergence rate and lowest convergence steady-state error, so it’s more suitable for blind equalization for nonlinear timevarying underwater acoustic channel and has better real-time tracking ability.