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Second-order modeling for Rayleigh flat ...
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Document type :
Communication dans un congrès avec actes
Title :
Second-order modeling for Rayleigh flat fading channel estimation with Kalman filter
Author(s) :
Ros, Laurent [Auteur]
GIPSA - Communication Information and Complex Systems [GIPSA-CICS]
Simon, Eric [Auteur] refId
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Conference title :
DSP 2011 - 17th IEEE International Conference on Digital Signal Processing
City :
Corfou
Country :
Grèce
Start date of the conference :
2011-07-06
Book title :
Proceedings of the 17th International Conference on Digital Signal Processing (DSP 2011)
Publication date :
2011-07
English keyword(s) :
Rayleigh Channel estimation
Jakes' Doppler spectrum
Flat fading
Kalman Filter
steady-state.
steady-state
HAL domain(s) :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
This paper deals with channel estimation over flat fading Rayleigh channel with Jakes' Doppler spectrum. Many estimation algorithms exploit the time-domain correlation of the channel by employing Kalman Filter based on an ...
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This paper deals with channel estimation over flat fading Rayleigh channel with Jakes' Doppler spectrum. Many estimation algorithms exploit the time-domain correlation of the channel by employing Kalman Filter based on an approximation of the time-varying channel. A common method used in the literature is based on a first-order auto-regressive (AR1) model for the channel approximation, combined with a Correlation Matching (CM) criterion to fix the value of the AR1-parameter. In this paper, we propose first to replace the AR1 model by a specific second-order (Or2) model (as the one used for the phase estimation in presence of frequency offset), which is more appropriate for slow fading variations. Secondly, we propose a criterion based on the Minimization of the Asymptotic Variance (MAV) of the Kalman estimator to fix the parameter of the Or2-model. Closed-form expressions of the optimum Or2-parameter and of the corresponding Mean Square Error (MSE) are derived for a given channel state (Doppler spread, SNR). MSE theoretical analysis and simulation results prove a significant improvement with the Or2-MAV approach compared to more conventional AR1-CM approach (or even AR1-MAV optimized approach) in terms of MSE, especially for slow fading variations.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 :
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