Blind Equalization Based on a Class of Genetic Algorithms for Wireless Communication

In this paper, a class of genetic algorithms (GA) is implemented as solutions to optimize the problem of blind equalization in wireless communication. Cost functions in blind equalization algorithms are described as fitness functions in GA; and because of the Characteristics of GA, the algorithm can search for the globe optimal equalizer weight vector. Another advantage is that researchers do not need to know the mathematic describe model. All those algorithms choose different fitness functions and based on GA belong to a same class. Both analyze and simulation result express the convergence and performance in this method are approximate to the equalization result with training sequence; and are much better than common linear blind equalization. Especially this method can be used in the non-linear equalization environment.