Abstract: To overcome the disadvantages of Constant Modulus Algorithm (CMA), such as slow convergence speed, large mean square error, and easily immerging in partial minimum, an orthogonal Wavelet Transform based Constant Modulus blind equalization Algorithm based on Modified Hybrid Genetic Algorithm (MHGA-WT-CMA) was proposed. The proposed algorithm uses genetic algorithm based on modified coding method, population initialization, selection and crossover operator. The coefficient vector of the blind equalizer is regarded as the initial population. Orthogonal wavelet blind equalization algorithm is embedded into the genetic algorithm to search elite individual in the father generation population locally. The elite individual is copied into the offspring directly. The other individuals are optimized by modified genetic algorithm with binary coding method, roulette wheel selection method, POX crossover and non-uniform mutation. They are sent into offspring after decoding into real. The hybrid genetic algorithm outputs the optimal weight vector when it satisfies stopping criterion. The proposed algorithm combines advantages of both orthogonal wavelet transform based constant modulus blind equalization algorithm and modified genetic algorithm. Computer simulation shows that the proposed algorithm has fast convergence rate, small mean square error, and global optimal solution.