Orthogonal Wavelet Transform Blind Equalization Algorithm based on Chicken Swarm Optimization Algorithm

According to disadvantages of low convergence rate, big steady-state and local convergence error of traditional equalization constant modulus algorithm(CMA), combined with the orthogonal wavelet transform and the chicken swarm optimization algorithm(CSO), an orthogonal wavelet transform blind equalization algorithm based on chicken swarm optimization algorithm (CSO-WT-CMA) is proposed. Based on the CMA, the proposed algorithm improved the convergence rate by using the orthogonal wavelet transform to normalize the transmission signal (WT-CMA). Meanwhile, in order to avoid premature convergence, local optimization and can’t achieve global optimization, inertia weight factor is introduced into the location update formula of hens and chicks, improving the global search and local search ability. Computer simulations in underwater acoustic channels indicate that the proposed algorithm outperforms the WT-CMA in mean square error and convergence rate.