Fractional lower-order statistics for efficient adaptive temporal and spatial methods in non-Gaussian environment

This paper addresses the problem of blind equalization for digital communications using constant modulus signals in the presence of heavy-tailed additive channel noise. We compare the performance of a temporal filter antenna system with the ones obtained with an array of sensors used at the receiver to copy the information sequence. First, we demonstrate the negative effects of channel noise to the original CMA cost function in terms of reliability and convergence. Then, we introduce a new CMA criterion for both temporal and spatial systems based on the fractional lower-order statistics (FLOS) of the received data. We perform an analytical study of the properties of the new cost function and we illustrate its convergence behavior through computer simulations