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This paper addresses the problem of blind equalization for digital communications using an array of sensors at the receiver to copy constant modulus signals in the presence of heavy-tailed additive channel noise. First, we demonstrate the negative effects of channel noise to the original CMA cost function in terms of convergence. Then, we introduce a new CMA criterion based on the fractional lower-order statistics (FLOS) of the received data. The proposed criterion is able to mitigate impulsive noise at the receiver and at the same time restores the constant modulus character of the transmitted communication signal. We perform an analytical study of the properties of the new cost function and we illustrate its convergence behavior through computer simulations.

A bst rwctThis paper nddresscs thc problem of blind equalization for digital communicntiotis using constant tnodulus signals in the prescnce of heavy-tnilcd additive channel iioisc. We compare the performance of R tcrnporal filter antenn;r systciii with the ones obtained with an array of sensors usctl at ihc receiver to copy thc information sequeiicc. First, wc deinonstrale the negative cffecls of channcl tioisc io tlic origind CMA cost function in terms of reliability and crmvcrgence. Thcri, we introduce n new CMA criterion Tor bolh tempornl aiid spatial systetiis bascd on the fractional lower-order statistics (PLOS) of thc rcccived dum.We perform an analytical study of the properties of the iicw cost function nnd we illustrntc its colivergence belinvior through cornputcr simulations.