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
Une technique d'initialisation d'égaliseur pour l'algorithme des moindres carrés moyens (LMS), qui peut égaliser les canaux à entrées multiples et sorties multiples (MIMO) sélectifs en fréquence, est présentée et analysée. La méthode proposée effectue une étape de convergence initiale pour une formation supérieure avant d'exécuter l'algorithme LMS. Cette approche augmente les performances de la formation alors que la complexité de l'algorithme LMS, connu comme l'algorithme de formation le plus simple, est presque la même. La technique proposée est analysée pour la convergence initiale et simulée pour une éventuelle application MIMO monoporteuse dans les normes monoporteuse (SC) IEEE802.16-2004. Les performances obtenues après codage se rapprochent des performances de l'algorithme des moindres carrés récursifs (RLS) tel qu'il est présenté pour 3
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Kadir TURK, Ismail KAYA, "Analysis of Initialized LMS Equalizer for Frequency Selective MIMO Channels Using Single Carrier IEEE 802.16-2004 PHY" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 7, pp. 2413-2419, July 2009, doi: 10.1587/transcom.E92.B.2413.
Abstract: An equalizer initialization technique for least mean squares (LMS) algorithm, which can equalize frequency selective multiple input multiple output (MIMO) channels, is presented and analyzed. The proposed method conducts an initial convergence step for superior training prior to running the LMS algorithm. This approach raises the training performance while the complexity of the LMS algorithm, which is known as the simplest training algorithm, is almost the same. The proposed technique is analyzed for the initial convergence and simulated for a possible single carrier MIMO application in single carrier (SC) IEEE802.16-2004 standards. The obtained performance after coding approximates the performance of the recursive least squares (RLS) algorithm as it is presented for 3
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.2413/_p
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@ARTICLE{e92-b_7_2413,
author={Kadir TURK, Ismail KAYA, },
journal={IEICE TRANSACTIONS on Communications},
title={Analysis of Initialized LMS Equalizer for Frequency Selective MIMO Channels Using Single Carrier IEEE 802.16-2004 PHY},
year={2009},
volume={E92-B},
number={7},
pages={2413-2419},
abstract={An equalizer initialization technique for least mean squares (LMS) algorithm, which can equalize frequency selective multiple input multiple output (MIMO) channels, is presented and analyzed. The proposed method conducts an initial convergence step for superior training prior to running the LMS algorithm. This approach raises the training performance while the complexity of the LMS algorithm, which is known as the simplest training algorithm, is almost the same. The proposed technique is analyzed for the initial convergence and simulated for a possible single carrier MIMO application in single carrier (SC) IEEE802.16-2004 standards. The obtained performance after coding approximates the performance of the recursive least squares (RLS) algorithm as it is presented for 3
keywords={},
doi={10.1587/transcom.E92.B.2413},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Analysis of Initialized LMS Equalizer for Frequency Selective MIMO Channels Using Single Carrier IEEE 802.16-2004 PHY
T2 - IEICE TRANSACTIONS on Communications
SP - 2413
EP - 2419
AU - Kadir TURK
AU - Ismail KAYA
PY - 2009
DO - 10.1587/transcom.E92.B.2413
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2009
AB - An equalizer initialization technique for least mean squares (LMS) algorithm, which can equalize frequency selective multiple input multiple output (MIMO) channels, is presented and analyzed. The proposed method conducts an initial convergence step for superior training prior to running the LMS algorithm. This approach raises the training performance while the complexity of the LMS algorithm, which is known as the simplest training algorithm, is almost the same. The proposed technique is analyzed for the initial convergence and simulated for a possible single carrier MIMO application in single carrier (SC) IEEE802.16-2004 standards. The obtained performance after coding approximates the performance of the recursive least squares (RLS) algorithm as it is presented for 3
ER -