BLIND EQUALIZATION OF FRACTIONALLY-SPACED CHANNELS
Vicente Zarzoso, Asoke Kumar Nandi · 2003
*Supported through a Postdoctoral Research Fellowship awarded by the Royal Academy of Engineering of the UK. We approach the problem of blind identification and equalization (BIE) of single-user digital communication channels from the perspective of blind source separation (BSS). A new BSS-based BIE algorithm is proposed in this paper and is compared with a subspace method as well as a normalized variant of the well-known constant modulus algorithm (NCMA). The equalization qualities of the three algorithms are assessed using channels with well-conditioned and ill-conditioned convolution matrices. It is found that the BSS-based algorithm outperforms the other algorithms except for short source data sequences. The subspace method, which inverts the estimated channel to obtain the equalizer, leads to poor results in the case of the ill-conditioned channel. The simple NCMA suffers from slow convergence or misconvergence except for well-conditioned channels of low order.