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Article Dans Une Revue Signal Processing Année : 2012

On the Use of First-order Autoregressive Modeling for Rayleigh Flat Fading Channel Estimation with Kalman Filter

Résumé

This letter deals with the estimation of a flat fading Rayleigh channel with Jakes's spectrum. The channel is approximated by a first-order autoregressive (AR(1)) model and tracked by a Kalman Filter (KF). The common method used in the literature to estimate the parameter of the AR(1) model is based on a Correlation Matching (CM) criterion. However, for slow fading variations, another criterion based on the Minimization of the Asymptotic Variance (MAV) of the KF is more appropriate, as already observed in few works [1]. This letter gives analytic justification by providing approximated closed-form expressions of the estimation variance for the CM and MAV criteria, and of the optimal AR(1) parameter.
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Dates et versions

hal-00638787 , version 1 (07-11-2011)

Identifiants

Citer

Soukayna Ghandour - Haidar, Laurent Ros, Jean-Marc Brossier. On the Use of First-order Autoregressive Modeling for Rayleigh Flat Fading Channel Estimation with Kalman Filter. Signal Processing, 2012, 92 (2), pp.601-606. ⟨10.1016/j.sigpro.2011.08.014⟩. ⟨hal-00638787⟩
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