A Closed Form Solution to Blind Equalization

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 jblindj 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 coeOEcients can be uniquely derived from the eigenvectors of a speciøc 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. In der letzten Zeit wurden verschiedene neue Algorithmen zur blinden adaptiven Entzerrung vorgeschlagen. Diese Algorithmen basieren auf dem stoc..