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 estimation de séquence de maximum de vraisemblance de traitement adaptatif par survivant (PSP-MLSE) utilisant les moindres carrés récursifs (RLS) basés sur l'espace d'état est proposée pour des canaux à évanouissements multi-trajets à variation rapide dans le temps. Contrairement au PSP-MLSE utilisant le filtrage de Kalman, il ne nécessite pas de connaissance des statistiques du modèle et, grâce à la modélisation de l'espace d'état, il présente des performances robustes en termes de taux de fondu, par rapport au PSP-MLSE utilisant le RLS conventionnel.
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Jung Suk JOO, "Adaptive PSP-MLSE Using State-Space Based RLS for Multi-Path Fading Channels" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 12, pp. 4024-4026, December 2008, doi: 10.1093/ietcom/e91-b.12.4024.
Abstract: An adaptive per-survivor processing maximum likelihood sequence estimation (PSP-MLSE) using state-space based recursive least-squares (RLS) is proposed for rapidly time varying multi-path fading channels. Unlike PSP-MLSE using Kalman filtering, it does not require the knowledge of model statistics, and with an aid of state-space modeling, it has a robust performance to the fade rate, compared to PSP-MLSE using conventional RLS.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.12.4024/_p
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@ARTICLE{e91-b_12_4024,
author={Jung Suk JOO, },
journal={IEICE TRANSACTIONS on Communications},
title={Adaptive PSP-MLSE Using State-Space Based RLS for Multi-Path Fading Channels},
year={2008},
volume={E91-B},
number={12},
pages={4024-4026},
abstract={An adaptive per-survivor processing maximum likelihood sequence estimation (PSP-MLSE) using state-space based recursive least-squares (RLS) is proposed for rapidly time varying multi-path fading channels. Unlike PSP-MLSE using Kalman filtering, it does not require the knowledge of model statistics, and with an aid of state-space modeling, it has a robust performance to the fade rate, compared to PSP-MLSE using conventional RLS.},
keywords={},
doi={10.1093/ietcom/e91-b.12.4024},
ISSN={1745-1345},
month={December},}
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TY - JOUR
TI - Adaptive PSP-MLSE Using State-Space Based RLS for Multi-Path Fading Channels
T2 - IEICE TRANSACTIONS on Communications
SP - 4024
EP - 4026
AU - Jung Suk JOO
PY - 2008
DO - 10.1093/ietcom/e91-b.12.4024
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2008
AB - An adaptive per-survivor processing maximum likelihood sequence estimation (PSP-MLSE) using state-space based recursive least-squares (RLS) is proposed for rapidly time varying multi-path fading channels. Unlike PSP-MLSE using Kalman filtering, it does not require the knowledge of model statistics, and with an aid of state-space modeling, it has a robust performance to the fade rate, compared to PSP-MLSE using conventional RLS.
ER -