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Maximum Likelihood BSC Parameter Estimation for the Slepian-Wolf Problem

Velotiaray Toto-Zarasoa 1 Aline Roumy 1 Christine Guillemot 1 
1 TEMICS - Digital image processing, modeling and communication
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In the context of Distributed Source Coding, we propose a low complexity algorithm for the estimation of the cross-over probability p of the Binary Symmetric Channel (BSC) modeling the correlation between two binary sources. The coding is done with linear block codes. We propose a novel method to estimate p prior to decoding and show that it is the Maximum Likelihood estimator of p with respect to the syndromes of the correlated sources. The method can be utilized for the parameter estimation for channel coding of binary sources over the BSC.
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Submitted on : Tuesday, October 18, 2011 - 2:58:27 PM
Last modification on : Friday, February 4, 2022 - 3:15:26 AM
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Velotiaray Toto-Zarasoa, Aline Roumy, Christine Guillemot. Maximum Likelihood BSC Parameter Estimation for the Slepian-Wolf Problem. IEEE Communications Letters, 2011, 15 (2), ⟨10.1109/LCOMM.2011.122810.102182⟩. ⟨inria-00628996v2⟩



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