A closed-form solution to blind equalization

1 Abstract In some recent papers new algorithms for blind adaptive equalization were proposed. These algorithms are based on the stochastic gradient method and thus can be regarded as a blindd counterpart to the classic LMS-(least mean squares-) algorithms. It is well-known that these algorithms show relatively slow convergence speed. The classic solution to get fast convergence is the RLS-(recursive least squares-) algorithm which makes use of the closed-form solution. The purpose of this paper is to derive a closed-form solution in the sense of blind equalization. It will be shown that the equalizer coeecients can be uniquely derived from the eigenvectors of a speciic 4th-order cumulant matrix of the received signal. By means of some examples it will be demonstrated that the eigenvector solution is near the ideal MSE-(mean square error-) solution. wird verdeutlicht, daa diese Eigenvektor-LLsung in der NNhe der idealen MSE-LLsung liegt.