TAILIEUCHUNG - Báo cáo hóa học: " Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver | EURASIP Journal on Wireless Communications and Networking 2005 4 483-492 2005 Javier Del Ser et al. Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver Javier Del Ser Centro de Estudios e Investigaciones Tecnicas de Gipuzkoa CEIT Parque Tecnologico de San Sebastian Paseo Mikeletegi N48 20009 Donostia San Sebastian Spain Email jdelser@ Pedro M. Crespo Centro de Estudios e Investigaciones Tecnicas de Gipuzkoa CEIT Parque Tecnologico de San Sebastián Paseo Mikeletegi N48 20009 Donostia San Sebastian Spain Email pcrespo@ Olaia Galdos Centro de Estudios e Investigaciones Tecnicas de Gipuzkoa CEIT Parque Tecnologico de San Sebastian Paseo Mikeletegi N48 20009 Donostia San Sebastian Spain Email ogaldos@ Received 25 October 2004 Revised 17 May 2005 We consider the case of two correlated sources S1 and S2. The correlation between them has memory and it is modelled by a hidden Markov chain. The paper studies the problem of reliable communication of the information sent by the source S1 over an additive white Gaussian noise AWGN channel when the output of the other source S2 is available as side information at the receiver. We assume that the receiver has no a priori knowledge of the correlation statistics between the sources. In particular we propose the use of a turbo code for joint source-channel coding of the source S1. The joint decoder uses an iterative scheme where the unknown parameters of the correlation model are estimated jointly within the decoding process. It is shown that reliable communication is possible at signal-to-noise ratios close to the theoretical limits set by the combination of Shannon and Slepian-Wolf theorems. Keywords and phrases distributed source coding hidden Markov model parameter estimation Slepian-Wolf theorem joint source-channel coding. 1. INTRODUCTION Communication networks are multiuser communication systems. Therefore their performance is best understood when viewed

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