The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cette étude vise à explorer une méthode de convergence rapide d'égalisation aveugle utilisant des statistiques d'ordre supérieur (cumulants). Les efforts se concentrent sur l’élaboration de nouvelles solutions théoriques pour les égaliseurs aveugles plutôt que sur l’étude d’algorithmes pratiques. Sous les hypothèses courantes de ce cadre, on constate que la condition d'égalisation aveugle est directement associée à un problème propre, c'est-à-dire que les coefficients de retard de l'égaliseur peuvent être obtenus à partir des vecteurs propres d'une matrice statistique d'ordre supérieur. Une méthode de récupération en phase aveugle est également proposée pour les systèmes QAM. Les simulations informatiques montrent qu’une convergence très rapide peut être obtenue grâce à cette approche.
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.
Copier
Ling CHEN, Hiroji KUSAKA, Masanobu KOMINAMI, "Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition" in IEICE TRANSACTIONS on Communications,
vol. E82-B, no. 7, pp. 1048-1054, July 1999, doi: .
Abstract: This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e82-b_7_1048/_p
Copier
@ARTICLE{e82-b_7_1048,
author={Ling CHEN, Hiroji KUSAKA, Masanobu KOMINAMI, },
journal={IEICE TRANSACTIONS on Communications},
title={Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition},
year={1999},
volume={E82-B},
number={7},
pages={1048-1054},
abstract={This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.},
keywords={},
doi={},
ISSN={},
month={July},}
Copier
TY - JOUR
TI - Blind Channel Equalization and Phase Recovery Using Higher Order Statistics and Eigendecomposition
T2 - IEICE TRANSACTIONS on Communications
SP - 1048
EP - 1054
AU - Ling CHEN
AU - Hiroji KUSAKA
AU - Masanobu KOMINAMI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E82-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 1999
AB - This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.
ER -