Fast convergence algorithms for joint blind equalization and source separation based upon the cross-corr elation and constant modulus criterion

Abstract

To solve the problem of joint blind equalization and source separation, two new quasi-Newton 'adaptive algorithms with rapid convergence property are proposed based upon the cross-correlation and constant modulus (CC-CM) criterion, namely the block-Shanno cross-correlation and constant modulus algorithm (BS-CCCMA) and the fast quasi-Newton cross-correlation and constant modulus algorithm (FQN-CCCMA). Simulations studies are used to show that the convergence properties of these algorithms are much improved upon those of the conventional LMS-CCCMA algorithm.