PERFORMANCE OF SVD-BASED FRACTIONALLY-SPACED EQUALIZERS IN DATA-TRANSMISSION SYSTEMS

An algorithm is presented for implementing a complex fractionally spaced equalizer (CFSE) that uses the least-mean-square (LMS) algorithm and singular value decomposition (SVD). SVD is used to reduce the eigenvalue spread of the autocorrelation matrix of the CFSE tap inputs. It is shown that SVD accelerates the convergence of the CFSE in proportion to the receiver oversampling factor but maintains the steady-state excess mean square error (MSE) at approximately the same level as that of the CFSE that does not have an SVD-based receiver prefilter. Our choice of a prefilter from the autocorrelation matrix of the received signal will facilitate easier and faster tracking of the principal components in an adaptive environment.