A new choice of penalty function for robust multiuser detection based on M-estimation

In this letter, we propose a new robust MUD, called α detector, for non-Gaussian noise. We consider the Gaussian-mixture model for non-Gaussian or impulsive noise. Our technique outperforms the decorrelator and the minimax detectors in highly impulsive noise. The proposed method uses a parametric cost function, where the parameter α is selected using the difference between the asymptotic variance of estimation error of the α detector and that of the minimax detector.