Title :

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

Author(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]

Conference title :

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

City :

Cape Town

Country :

Afrique du Sud

Start date of the conference :

2010-05-23

Book title :

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

Publisher :

_

Publication date :

2010

English keyword(s) :

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

HAL domain(s) :

Sciences de l'ingénieur [physics]

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

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

Source :

Harvested from HAL