A negentropy minimization approach to adaptive beamforming assisted receivers

In this letter, we introduce a new adaptive beamforming assisted receiver based on minimizing the approximate negentropy (NEGMIN) of the estimation error. We consider the approximate negentropy by using a nonpolynomial expansion of the estimation error as a new performance criterion to improve the performance of adaptive beamforming receivers based on the minimizing minimum mean squared error (MMSE) criteria. Negentropy includes higher order statistical information and its minimization provides improved converge, performance, and accuracy compared to traditional methods such as MMSE in terms of bit error rate (BER). Copyright