Orthogonal Wavelet Transform Blind Equalization Algorithm Based On The Optimization Of Genetic Algorithm

In underwater acoustic communication, Inter-Symbol Interference seriously affects the quality of communication, due to the complexity of characteristics of the acoustic channel. In order to enhance the data of the transmission speed and the reliability, the equalization is needed to balance the signal at the receiving. Compared to the conventional adaptive equalization, the blind equalize technology does not need to transmit the training sequence to be possible to effectively save bandwidth, and improve communication efficiency. The blind equalize technology is a hot research topic in modern signal processing areas. Aiming at the disadvantage of CMA (Constant Modulus Algorithm), the blind equalization algorithms are studied deep in this dissertation by using wavelet transform and genetic algorithm as analyzing tool. The main contributions are as follows:1 Analyzing blind equalization algorithm based on the optimization of genetic algorithmIn the traditional constant modulus algorithm of blind equalization, the methold of searching optimal weight vector is a gradient descent search method. First, the search methold needs to set a cost function, and the cost function must be continuous and derivable. The search method finds the minimum value by requiring the equalizer weight vector gradient to determine the equalizer weights iterative equation. But the methold is easy to fall into local convergence. Aiming at the disadvantage of the search methold, genetic algorithm is introduced to the blind equalization algorithm and the blind equalization algorithm based on genetic algorithm is proposed. In the proposed algorithm, the fitness function of genetic algorithm is provided by the construction cost function of blind equalization algorithm. It is full use of the global random search feature of the genetic algorithm to find the global optimal solution of the equalizer. Simulation results show the superiority of the proposed algorithm.2 Analyzing orthogonal wavelet transform blind equalization algorithm based on the optimization of genetic algorithm(1) The orthogonal wavelet transform blind equalization algorithm based on the optimization of genetic algorithm is proposed. The decorrelation of the orthogonal wavelet transform can speed up the convergence rate of the equalizer, and genetic algorithms can quickly find the global optimal solution of the equalizer weight vector. The proposed algorithm combines the advantages of the orthogonal wavelet transform and genetic algorithm.Its optimization results is verified by simulation results.(2) According to disadvantages of low convergence rate, big steady-state mean square error of fractionally spaced blind equalization algorithm, the orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm is proposed. The proposed algorithm combines the advantages of the fractionally spaced, orthogonal wavelet transform and genetic algorithm. It improves the performance of the algorithm. And the orthogonal wavelet transform SEI blind equalization algorithm based on the optimization of genetic algorithm is analyzed by introduceing the genetic algorithm to the super-exponential iterative wavelet blind equalization algorithm. The analyzed algorithm can ruduce the possibility of CMA local convergence using characteristics of the global search of genetic algorithm to optimize the equalizer weight vector, and has the faster convergence rate and smaller mean square error. The efficiency of the analyzed algorithm is proved by computer simulation in underwater acoustic channels.3 Analyzing orthogonal wavelet transform blind equalization algorithm based on the optimization of improved genetic algorithmIn the standard genetic algorithm, crossover probability and mutation probability are certain value. They are determined through experiments. If the value is improper, it can affect the performance and convergence of the algorithm and be prone to premature. To solve these problems, this paper introduces the adaptive algorithm and simulated annealing algorithm to improve the standard genetic algorithm. The improved algorithm is used to optimize the blind equalization algorithm.(1) In this paper, the adaptive genetic algorithm is the genetic algorithm that its crossover probability and mutation probability are adaptively changed. The algoritm is introduced into the orthogonal wavelet transform SEI blind equalization algorithm.The optimized blind equalization algorithm is called for the orthogonal wavelet transform SEI blind equalization algorithm based on adaptive genetic algorithm. (2) To improve the local search ability, the orthogonal wavelet transform blind equalization algorithm based on the optimization of simulated annealing genetic algorithm is proposed in this dissertation. The algorithm makes full use of the good global search capability of GA and local search ability of SA, and the decorrelation of orthogonal wavelet transform. It effectively improves the performance of the algorithm and the optimization result is verified by simulations.