In this paper we have presented a novel method for blind FIR channel estimation based on higher order statistics. Aiming to improve the consistency of estimation, we present a blind channel estimation that uses covolutionary genetic algorithm (GA) to minimize the cost function in which different cumulant slices are used. This cost function provides us most of output statistics information to estimate the channel coefficients. To enhance the convergence speed an intellectual first population, based on mathematical relationships in higher order statistics, is exploited. This scheme surpasses the classical methods such as weighted slice, GMT algorithms, and simple GA method in terms of robustness and accuracy especially when high-order channels are considered.
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