A Recursive Data Least Square Algorithm and Its Channel Equalization Application
Summary :
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 Communications Vol.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
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
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://global.ieice.org/en_transactions/communications/10.1093/ietcom/e90-b.8.2143/_p
Copy
@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},}
Copy
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 -
English
