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A Recursive Data Least Square Algorithm and Its Channel Equalization Application

Jun-Seok LIM,Jea-Soo KIM,Koeng-Mo SUNG

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Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.

Publication: IEICE TRANSACTIONS on CommunicationsVol.E90-B No.8 pp.2143-2146

Publication Date: 2007/08/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1093/ietcom/e90-b.8.2143

Type of Manuscript: LETTER

Category: Fundamental Theories for Communications

Authors

Jun-Seok LIM
Jea-Soo KIM
Koeng-Mo SUNG

Keyword

data least squares method, generalized eigenvalue problem, equalization

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Jun-Seok LIM, Jea-Soo KIM, Koeng-Mo SUNG, "A Recursive Data Least Square Algorithm and Its Channel Equalization Application" in IEICE TRANSACTIONS on Communications, vol. E90-B, no. 8, pp. 2143-2146, August 2007, doi:10.1093/ietcom/e90-b.8.2143.
Abstract:Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.
URL: https://globals.ieice.org/en_transactions/communications/10.1093/ietcom/e90-b.8.2143/_p

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@ARTICLE{e90-b_8_2143,
author={Jun-Seok LIM, Jea-Soo KIM, Koeng-Mo SUNG, },
journal={IEICE TRANSACTIONS on Communications},
title={A Recursive Data Least Square Algorithm and Its Channel Equalization Application},
year={2007},
volume={E90-B},
number={8},
pages={2143-2146},
abstract={Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.},
keywords={},
doi={10.1093/ietcom/e90-b.8.2143},
ISSN={1745-1345},
month={August},}

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TY - JOUR
TI - A Recursive Data Least Square Algorithm and Its Channel Equalization Application
T2 - IEICE TRANSACTIONS on Communications
SP - 2143
EP - 2146
AU - Jun-Seok LIM
AU - Jea-Soo KIM
AU - Koeng-Mo SUNG
PY - 2007
DO -10.1093/ietcom/e90-b.8.2143
JO - IEICE TRANSACTIONS on Communications
SN -1745-1345
VL - E90-B
IS - 8
JA - IEICE TRANSACTIONS on Communications
Y1 - August 2007
AB -Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.
ER -