The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Desenvolvemos uma estrutura matemática para a análise de transferência extrínseca de informações (EXIT) para avaliar o comportamento de convergência da decodificação iterativa conjunta baseada em máximo a posteriori (MAP) de fontes correlacionadas, que são codificadas separadamente e transmitidas por canais ruidosos. Ao contrário do trabalho anterior, nossa abordagem concentra-se no caso, as informações sobre a correlação não são perfeitamente fornecidas no decodificador conjunto, mas são extraídas da saída do decodificador e atualizadas de maneira iterativa. A estrutura apresentada fornece uma maneira conveniente de comparar esquemas. Mostramos que isso nos permite prever com facilidade e precisão o ganho de decodificação conjunta e a posição do turbo cliff.
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Kentaro KOBAYASHI, Takaya YAMAZATO, Masaaki KATAYAMA, "EXIT Analysis for MAP-Based Joint Iterative Decoding of Separately Encoded Correlated Sources" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 12, pp. 3509-3513, December 2010, doi: 10.1587/transcom.E93.B.3509.
Abstract: We develop a mathematical framework for the extrinsic information transfer (EXIT) analysis to assess the convergence behavior of maximum a posteriori (MAP)-based joint iterative decoding of correlated sources, which are separately encoded and transmitted over noisy channels. Unlike the previous work, our approach focuses on the case side information about the correlation is not perfectly given at the joint decoder but is extracted from decoder output and updated in an iterative manner. The presented framework provides a convenient way to compare between schemes. We show that it allows us to easily and accurately predict joint decoding gain and turbo cliff position.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.3509/_p
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@ARTICLE{e93-b_12_3509,
author={Kentaro KOBAYASHI, Takaya YAMAZATO, Masaaki KATAYAMA, },
journal={IEICE TRANSACTIONS on Communications},
title={EXIT Analysis for MAP-Based Joint Iterative Decoding of Separately Encoded Correlated Sources},
year={2010},
volume={E93-B},
number={12},
pages={3509-3513},
abstract={We develop a mathematical framework for the extrinsic information transfer (EXIT) analysis to assess the convergence behavior of maximum a posteriori (MAP)-based joint iterative decoding of correlated sources, which are separately encoded and transmitted over noisy channels. Unlike the previous work, our approach focuses on the case side information about the correlation is not perfectly given at the joint decoder but is extracted from decoder output and updated in an iterative manner. The presented framework provides a convenient way to compare between schemes. We show that it allows us to easily and accurately predict joint decoding gain and turbo cliff position.},
keywords={},
doi={10.1587/transcom.E93.B.3509},
ISSN={1745-1345},
month={December},}
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TY - JOUR
TI - EXIT Analysis for MAP-Based Joint Iterative Decoding of Separately Encoded Correlated Sources
T2 - IEICE TRANSACTIONS on Communications
SP - 3509
EP - 3513
AU - Kentaro KOBAYASHI
AU - Takaya YAMAZATO
AU - Masaaki KATAYAMA
PY - 2010
DO - 10.1587/transcom.E93.B.3509
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2010
AB - We develop a mathematical framework for the extrinsic information transfer (EXIT) analysis to assess the convergence behavior of maximum a posteriori (MAP)-based joint iterative decoding of correlated sources, which are separately encoded and transmitted over noisy channels. Unlike the previous work, our approach focuses on the case side information about the correlation is not perfectly given at the joint decoder but is extracted from decoder output and updated in an iterative manner. The presented framework provides a convenient way to compare between schemes. We show that it allows us to easily and accurately predict joint decoding gain and turbo cliff position.
ER -