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IEEE Transactions on Communications (2010) pp.
A Rao-Blackwellized particle filter for joint channel/symbol estimation in MC-DS-CDMA systems
Audrey Giremus 1, Eric Grivel 1, Julie Grolleau 1, Mohamed Najim 1
(2010)

This paper deals with the joint estimation of Rayleigh fading channels and symbols in a MC-DS-CDMA system. Formerly, particle filtering has been introduced as a set of promising methods to solve communication problems. PF consists in simulating possible values of the unkwnown parameters and selecting the most likely candidates with regard to the received signal. Here, the Rao-Blackwellized particle filter (RBPF) is used to significantly decrease the variance of the channel/symbol estimates. Our contribution is twofold. Firstly, sinusoidal stochastic models have been shown to better represent the statistical properties of Rayleigh channels than classical autoregressive models. Therefore, the proposed RBPF estimator is based on these models which are expressed as the sum of two sinusoids in quadrature at the maximum Doppler frequency with autoregressive processes as amplitudes. The model parameters are unknown and need to be estimated. Since PFs are not wellsuited to recover non-varying parameters, we propose to crosscouple the RBPF with a Kalman filter which makes use of the RBPF ouputs to sequentially update the parameters. Secondly, the choice of an efficient proposal distribution to simulate the particles is crucial for PF performance. We suggest using a suboptimal distribution which simulates likely values of the symbols at a reasonable computational cost.
1 :  Laboratoire de l'intégration, du matériau au système (IMS)
CNRS : UMR5218 – Université Sciences et Technologies - Bordeaux I – Institut Polytechnique de Bordeaux
Informatique/Traitement du signal et de l'image

Sciences de l'ingénieur/Traitement du signal et de l'image
Rayleigh channels – modeling – bandlimited stochastic processes – adaptive estimation – monte carlo methods – parameter estimation – CDMA.

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