Blind equalization based on immune optimized genetic algorithm
The blind equalization can be seen as an optimization task of cost function. A new blind equalization algorithm using immune optimization with genetic operators is presented. The coefficients of a blind equalizer are regarded as the antibodies of a population and the optimal solutions can be obtained by replication, mutation and suppression. The effectiveness of the proposed algorithm is proved via simulations.