Title :
Performance of SVD-based fractionally spaced equalizers in data transmission systems
Author :
Barton, Melbourne
Author_Institution :
Bellcore, Morristown, NJ, USA
fDate :
9/1/1994 12:00:00 AM
Abstract :
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. The authors 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
Keywords :
convergence of numerical methods; data communication systems; eigenvalues and eigenfunctions; equalisers; filtering and prediction theory; least squares approximations; matrix algebra; signal processing; CFSE; SVD-based fractionally spaced equalizers; adaptive environment; autocorrelation matrix; complex fractionally spaced equalizer; convergence; data transmission systems; eigenvalue spread; least-mean-square algorithm; principal components; receiver oversampling factor; receiver prefilter; singular value decomposition; steady-state excess mean square error; tap inputs; tracking; Acceleration; Autocorrelation; Convergence; Eigenvalues and eigenfunctions; Equalizers; Least squares approximation; Matrix decomposition; Mean square error methods; Singular value decomposition; Steady-state;
Journal_Title :
Signal Processing, IEEE Transactions on
