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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
Un algorithme d'estimation de canal aveugle basé sur la méthode du sous-espace pour les systèmes de multiplexage par répartition orthogonale de la fréquence (OFDM) à entrée multiple et sortie unique (SIMO) est proposé dans cette lettre. A l’aide d’un indice de répétition, l’algorithme conventionnel est un cas particulier de notre algorithme. Par rapport aux études connexes, l'algorithme proposé réduit la complexité de calcul du fonctionnement SVD et convient aux systèmes sans préfixe cyclique. En particulier, la condition nécessaire pour que la matrice de signaux proposée soit de rang complet peut être satisfaite avec moins de blocs OFDM. Les résultats de simulation démontrent que l'algorithme proposé surpasse les méthodes conventionnelles en termes d'erreur quadratique moyenne normalisée.
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Shih-Hao FANG, Ju-Ya CHEN, Ming-Der SHIEH, Jing-Shiun LIN, "Blind Channel Estimation for SIMO-OFDM Systems without Cyclic Prefix" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 1, pp. 339-343, January 2010, doi: 10.1587/transfun.E93.A.339.
Abstract: A blind channel estimation algorithm based on the subspace method for single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this letter. With the aid of a repetition index, the conventional algorithm is a special case of our algorithm. Compared with related studies, the proposed algorithm reduces the computational complexity of the SVD operation and is suitable for cyclic-prefix-free systems. In particular, the necessary condition of the proposed signal matrix to be full rank can be satisfied with fewer OFDM blocks. Simulation results demonstrate that the proposed algorithm outperforms conventional methods in normalized mean-square error.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.339/_p
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@ARTICLE{e93-a_1_339,
author={Shih-Hao FANG, Ju-Ya CHEN, Ming-Der SHIEH, Jing-Shiun LIN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Blind Channel Estimation for SIMO-OFDM Systems without Cyclic Prefix},
year={2010},
volume={E93-A},
number={1},
pages={339-343},
abstract={A blind channel estimation algorithm based on the subspace method for single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this letter. With the aid of a repetition index, the conventional algorithm is a special case of our algorithm. Compared with related studies, the proposed algorithm reduces the computational complexity of the SVD operation and is suitable for cyclic-prefix-free systems. In particular, the necessary condition of the proposed signal matrix to be full rank can be satisfied with fewer OFDM blocks. Simulation results demonstrate that the proposed algorithm outperforms conventional methods in normalized mean-square error.},
keywords={},
doi={10.1587/transfun.E93.A.339},
ISSN={1745-1337},
month={January},}
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TY - JOUR
TI - Blind Channel Estimation for SIMO-OFDM Systems without Cyclic Prefix
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 339
EP - 343
AU - Shih-Hao FANG
AU - Ju-Ya CHEN
AU - Ming-Der SHIEH
AU - Jing-Shiun LIN
PY - 2010
DO - 10.1587/transfun.E93.A.339
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2010
AB - A blind channel estimation algorithm based on the subspace method for single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this letter. With the aid of a repetition index, the conventional algorithm is a special case of our algorithm. Compared with related studies, the proposed algorithm reduces the computational complexity of the SVD operation and is suitable for cyclic-prefix-free systems. In particular, the necessary condition of the proposed signal matrix to be full rank can be satisfied with fewer OFDM blocks. Simulation results demonstrate that the proposed algorithm outperforms conventional methods in normalized mean-square error.
ER -