We propose an iterative channel decoding scheme for two or more multiple correlated sources. The correlated sources are separately turbo encoded without knowledge of the correlation and transmitted over noisy channels. The proposed decoder exploits the correlation of the multiple sources in an iterative soft decision decoding manner for joint detection of each of the transmitted data. Simulation results show that achieved performance for the more than two sources is also close to the Shannon and Slepian-Wolf limit and large additional SNR gain is obtained in comparison with the case of two sources. We also verify through simulation that no significant penalty results from the estimation of the source correlation in the decoding process and the code with a low error floor achieves good performance for a large number of the correlated sources.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Kentaro KOBAYASHI, Takaya YAMAZATO, Masaaki KATAYAMA, "Decoding of Separately Encoded Multiple Correlated Sources Transmitted over Noisy Channels" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 10, pp. 2402-2410, October 2009, doi: 10.1587/transfun.E92.A.2402.
Abstract: We propose an iterative channel decoding scheme for two or more multiple correlated sources. The correlated sources are separately turbo encoded without knowledge of the correlation and transmitted over noisy channels. The proposed decoder exploits the correlation of the multiple sources in an iterative soft decision decoding manner for joint detection of each of the transmitted data. Simulation results show that achieved performance for the more than two sources is also close to the Shannon and Slepian-Wolf limit and large additional SNR gain is obtained in comparison with the case of two sources. We also verify through simulation that no significant penalty results from the estimation of the source correlation in the decoding process and the code with a low error floor achieves good performance for a large number of the correlated sources.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.2402/_p
Copy
@ARTICLE{e92-a_10_2402,
author={Kentaro KOBAYASHI, Takaya YAMAZATO, Masaaki KATAYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Decoding of Separately Encoded Multiple Correlated Sources Transmitted over Noisy Channels},
year={2009},
volume={E92-A},
number={10},
pages={2402-2410},
abstract={We propose an iterative channel decoding scheme for two or more multiple correlated sources. The correlated sources are separately turbo encoded without knowledge of the correlation and transmitted over noisy channels. The proposed decoder exploits the correlation of the multiple sources in an iterative soft decision decoding manner for joint detection of each of the transmitted data. Simulation results show that achieved performance for the more than two sources is also close to the Shannon and Slepian-Wolf limit and large additional SNR gain is obtained in comparison with the case of two sources. We also verify through simulation that no significant penalty results from the estimation of the source correlation in the decoding process and the code with a low error floor achieves good performance for a large number of the correlated sources.},
keywords={},
doi={10.1587/transfun.E92.A.2402},
ISSN={1745-1337},
month={October},}
Copy
TY - JOUR
TI - Decoding of Separately Encoded Multiple Correlated Sources Transmitted over Noisy Channels
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2402
EP - 2410
AU - Kentaro KOBAYASHI
AU - Takaya YAMAZATO
AU - Masaaki KATAYAMA
PY - 2009
DO - 10.1587/transfun.E92.A.2402
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2009
AB - We propose an iterative channel decoding scheme for two or more multiple correlated sources. The correlated sources are separately turbo encoded without knowledge of the correlation and transmitted over noisy channels. The proposed decoder exploits the correlation of the multiple sources in an iterative soft decision decoding manner for joint detection of each of the transmitted data. Simulation results show that achieved performance for the more than two sources is also close to the Shannon and Slepian-Wolf limit and large additional SNR gain is obtained in comparison with the case of two sources. We also verify through simulation that no significant penalty results from the estimation of the source correlation in the decoding process and the code with a low error floor achieves good performance for a large number of the correlated sources.
ER -