Blind decision feedback equalizer based on high order MCMA

In this paper we propose a blind adaptive algorithm for the decision feedback equalizer based on high order MCMA (modified constant modulus algorithm) and decision directed adaptation. The originality of the proposed method is that the feedforward and the feedback filters are adjusted simultaneously by using the high order MCMA algorithm and by switching to the decision directed mode when the equalized symbols are in the convergence zones. This method reduces the propagation of error caused by the DFE structure. The mean square error (MSE) between the transmitted symbols and the equalized symbols is computed as performance metric. The proposed method is compared to the classic DFE based on second order MCMA. For all simulations, the ensemble-averaged MSE is obtained from 100 Monte Carlo runs. The obtained result show that the proposed method performs well for high constellations in the presence of Gaussian noise, comparatively with other methods.