Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer

<p/> <p>The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper, a novel theoretical framework for improving the performance of turbo decoding schemes that use the max-log-MAP algorithm is proposed. This fr...

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Main Authors: Karimi Hamid Reza, Claussen Holger, Mulgrew Bernard
Format: Article
Language:English
Published: SpringerOpen 2005-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/ASP.2005.820
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spelling doaj-76f4b7c8470c4677aa7315b871d10c102020-11-24T20:44:20ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802005-01-0120056212018Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information TransferKarimi Hamid RezaClaussen HolgerMulgrew Bernard<p/> <p>The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper, a novel theoretical framework for improving the performance of turbo decoding schemes that use the max-log-MAP algorithm is proposed. This framework is based on the concept of maximizing the transfer of mutual information between the component decoders. The improvements in performance can be achieved by using optimized iteration-dependent correction weights to scale the a priori information at the input of each component decoder. A method for the offline computation of the correction weights is derived. It is shown that a performance which approaches that of a turbo decoder using the optimum MAP algorithm can be achieved, while maintaining the advantages of low complexity and insensitivity to input scaling inherent in the max-log-MAP algorithm. The resulting improvements in convergence of the turbo decoding process and the expedited transfer of mutual information between the component decoders are illustrated via extrinsic information transfer (EXIT) charts.</p>http://dx.doi.org/10.1155/ASP.2005.820turbo decodingmax-log-MAPcorrection weightsEXIT chartsmutual information
collection DOAJ
language English
format Article
sources DOAJ
author Karimi Hamid Reza
Claussen Holger
Mulgrew Bernard
spellingShingle Karimi Hamid Reza
Claussen Holger
Mulgrew Bernard
Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
EURASIP Journal on Advances in Signal Processing
turbo decoding
max-log-MAP
correction weights
EXIT charts
mutual information
author_facet Karimi Hamid Reza
Claussen Holger
Mulgrew Bernard
author_sort Karimi Hamid Reza
title Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
title_short Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
title_full Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
title_fullStr Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
title_full_unstemmed Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer
title_sort improved max-log-map turbo decoding by maximization of mutual information transfer
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2005-01-01
description <p/> <p>The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper, a novel theoretical framework for improving the performance of turbo decoding schemes that use the max-log-MAP algorithm is proposed. This framework is based on the concept of maximizing the transfer of mutual information between the component decoders. The improvements in performance can be achieved by using optimized iteration-dependent correction weights to scale the a priori information at the input of each component decoder. A method for the offline computation of the correction weights is derived. It is shown that a performance which approaches that of a turbo decoder using the optimum MAP algorithm can be achieved, while maintaining the advantages of low complexity and insensitivity to input scaling inherent in the max-log-MAP algorithm. The resulting improvements in convergence of the turbo decoding process and the expedited transfer of mutual information between the component decoders are illustrated via extrinsic information transfer (EXIT) charts.</p>
topic turbo decoding
max-log-MAP
correction weights
EXIT charts
mutual information
url http://dx.doi.org/10.1155/ASP.2005.820
work_keys_str_mv AT karimihamidreza improvedmaxlogmapturbodecodingbymaximizationofmutualinformationtransfer
AT claussenholger improvedmaxlogmapturbodecodingbymaximizationofmutualinformationtransfer
AT mulgrewbernard improvedmaxlogmapturbodecodingbymaximizationofmutualinformationtransfer
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