Parallel adaptive decision feedback equalizers

Author

Raghunath, Kalavai J. ; Parhi, Keshab K.

Author_Institution

Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA

Volume

41

Issue

5

fYear

1993

fDate

5/1/1993 12:00:00 AM

Firstpage

1956

Lastpage

1961

Abstract

Several algorithms for parallel implementation of adaptive decision feedback equalizers (DFEs) are proposed. The first is a double-row DFE algorithm that outperforms previous approaches. Under the no-error-propagation assumption, the algorithm will perform exactly like a serially adapting DFE. The multiplication complexity of the double-row DFE algorithm is of the same order as that of the parallel DFE algorithm and the extended least-mean-square (LMS) method. The previous algorithms and the double-row DFE algorithm may become impractical to implement due to their large computational complexity, so three additional parallel implementations of the DFE, which lead to considerable hardware savings and avoid the coding loss of the former approaches, are presented. The different algorithms are compared on the basis of convergence analysis and simulation results

Keywords

adaptive filters; computational complexity; convergence of numerical methods; equalisers; feedback; parallel algorithms; adaptive decision feedback equalizers; computational complexity; convergence analysis; double-row DFE algorithm; multiplication complexity; no-error-propagation assumption; parallel implementation; simulation; Adaptive equalizers; Adaptive filters; Convergence; Decision feedback equalizers; Error correction; Hardware; Least squares approximation; Nonlinear filters; Sampling methods; Signal processing algorithms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.215315

Filename

215315