Fast Recursive Equalizers for 1D and 2D Linear Equalization

We develop fast recursive equalizers to be used in the one-dimensional (1D) or two-dimensional (2D) linear minimum mean-squared error equalization of a known linear finite-length channel. In particular, these equalization algorithms address the communications scenario in which the channel or the pri...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2012-07, Vol.60 (7), p.3886-3891
Main Authors: Drost, R. J., Singer, A. C.
Format: Article
Language:English
Subjects:
Algorithms
Arrays
Channel equalization
Channels
Complexity theory
Decoding
Equalization
Equalizers
Estimation
intersymbol interference
Recursive
recursive estimation
Symbols
Symmetric matrices
Transaction processing
turbo equalization
Two dimensional
Vectors
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Summary:We develop fast recursive equalizers to be used in the one-dimensional (1D) or two-dimensional (2D) linear minimum mean-squared error equalization of a known linear finite-length channel. In particular, these equalization algorithms address the communications scenario in which the channel or the prior information on the transmitted symbols may be time varying. The latter case of time-varying priors is especially pertinent for turbo equalization, on which we focus here. We first consider a 1D sliding-window equalizer based on a Cholesky-factorization update and then generalize this approach to the 2D case. Finally, we develop a 2D equalizer that is based on a recursive matrix-inverse update. We summarize each of these algorithms and describe their computational complexities.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2012.2191967