Titre :

Joint estimation of carrier frequency offset and channel complex gains for OFDM systems in fast time-varying vehicular environments

Auteur(s) :

Simon, Eric [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Hijazi, Hussein [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Ros, Laurent [Auteur]
GIPSA-Services [GIPSA-Services]
Berbineau, Marion [Auteur]
Laboratoire Electronique, Ondes et Signaux pour les Transports [INRETS/LEOST]
degauque, pierre [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]

Titre de la manifestation scientifique :

IEEE International Conference on Communications, ICC 2010, Workshop W3 on Vehicular Connectivity

Ville :

Cape Town

Pays :

Afrique du Sud

Date de début de la manifestation scientifique :

2010-05-23

Titre de l’ouvrage :

Proceedings of 2010 IEEE International Conference on Communications, ICC 2010, Workshop W3 on Vehicular Connectivity

Éditeur :

_

Date de publication :

2010

Mot(s)-clé(s) en anglais :

Frequency estimation
OFDM
Time varying systems
Iterative algorithms
Delay estimation
Rayleigh channels
Parameter estimation
Filtering algorithms
Recursive estimation
Kalman filters

Discipline(s) HAL :

Sciences de l'ingénieur [physics]

Résumé en anglais : [en]

In this paper, the physical nature of the radio-channel is considered by using an L-path channel model to developing an algorithm for OFDM systems operating in fast time-varying vehicular environment. Assuming the path ...
Lire la suite >In this paper, the physical nature of the radio-channel is considered by using an L-path channel model to developing an algorithm for OFDM systems operating in fast time-varying vehicular environment. Assuming the path delays are known, a novel iterative pilot-aided algorithm for joint estimation of multi-path Rayleigh channel complex gains and Carrier Frequency Offset (CFO) is introduced. Each complex gain time-variation, within one OFDM symbol, is approximated by a Basis Expansion Model (BEM) representation. An auto-regressive (AR) model is built for the parameters to be estimated (the AR model for the BEM coefficients is based on the Jakes process). The algorithm performs recursive estimation using Extended Kalman Filtering. Hence, the channel matrix is easily computed, and the data symbol is estimated with free inter-sub-carrier-interference (ICI) when the channel matrix is QR-decomposed. It is shown that only one iteration is sufficient to achieve the performance of the ideal case where knowledge of channel response and CFO is available.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL