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".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'identification aveugle des canaux adaptatifs des canaux de communication est un problème qui suscite d'importantes préoccupations théoriques et pratiques actuelles. Les solutions récemment proposées pour résoudre ce problème exploitent la diversité induite par le réseau d'antennes ou le suréchantillonnage temporel, conduisant aux techniques dites de statistiques de second ordre. Des techniques adaptatives d'identification de canal aveugle basées sur une approche des moindres carrés hors ligne ont été proposées, mais cette méthode suppose un cas sans bruit. La méthode fait appel à un filtre adaptatif avec une contrainte linéaire. Cet article propose une nouvelle approche basée sur la décomposition des valeurs propres. En effet, le vecteur propre correspondant à la valeur propre minimale de la matrice de covariance des signaux reçus contient la réponse impulsionnelle du canal. Et nous présentons un algorithme adaptatif pour résoudre ce problème. Les performances de la technique proposée sont évaluées sur un canal réel mesuré et comparées aux algorithmes existants.
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Kyung Seung AHN, Eul Chool BYUN, Heung Ki BAIK, "Blind Channel Identification Based on Eigenvalue Decomposition Using Constrained LMS Algorithm" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 5, pp. 961-966, May 2002, doi: .
Abstract: Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. Adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed but this method assumes noise-free case. The method resorts to an adaptive filter with a linear constraint. This paper proposes a new approach based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_5_961/_p
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@ARTICLE{e85-b_5_961,
author={Kyung Seung AHN, Eul Chool BYUN, Heung Ki BAIK, },
journal={IEICE TRANSACTIONS on Communications},
title={Blind Channel Identification Based on Eigenvalue Decomposition Using Constrained LMS Algorithm},
year={2002},
volume={E85-B},
number={5},
pages={961-966},
abstract={Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. Adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed but this method assumes noise-free case. The method resorts to an adaptive filter with a linear constraint. This paper proposes a new approach based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.},
keywords={},
doi={},
ISSN={},
month={May},}
Copier
TY - JOUR
TI - Blind Channel Identification Based on Eigenvalue Decomposition Using Constrained LMS Algorithm
T2 - IEICE TRANSACTIONS on Communications
SP - 961
EP - 966
AU - Kyung Seung AHN
AU - Eul Chool BYUN
AU - Heung Ki BAIK
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E85-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2002
AB - Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. Adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed but this method assumes noise-free case. The method resorts to an adaptive filter with a linear constraint. This paper proposes a new approach based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.
ER -