Performance of SVD-based fractionally spaced equalizers in data transmission systems

Author

Barton, Melbourne

Author_Institution

Bellcore, Morristown, NJ, USA

Volume

42

Issue

9

fYear

1994

fDate

9/1/1994 12:00:00 AM

Firstpage

2499

Lastpage

2501

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;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.317872

Filename

317872