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Wavelet Based Semi-blind Channel Estimation For Multiband OFDM

Abstract : This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet coefficients of the unknown channel impulse response in order to model a sparseness property of the wavelet representation. This prior yields, in maximum a posteriori estimation, a thresholding rule within the EM algorithm. We particularly focus on reducing the number of estimated parameters by iteratively discarding ``unsignificant'' wavelet coefficients from the estimation process. Simulation results using UWB channels issued from both models and measurements show that under sparsity conditions, the proposed algorithm outperforms pilot based channel estimation in terms of mean square error and bit error rate and enhances the estimation accuracy with less computational complexity than traditional semi-blind methods.
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Contributor : Sajad Sadough Connect in order to contact the contributor
Submitted on : Thursday, August 9, 2007 - 8:18:26 PM
Last modification on : Saturday, December 4, 2021 - 3:01:50 AM
Long-term archiving on: : Friday, April 9, 2010 - 12:31:37 AM


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  • HAL Id : hal-00166717, version 1
  • ARXIV : 0708.1414


Sajad Sadough, Mahieddine Ichir, Emmanuel Jaffrot, Pierre Duhamel. Wavelet Based Semi-blind Channel Estimation For Multiband OFDM. European Wireless, Apr 2007, Paris, France. European Wireless. ⟨hal-00166717⟩



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