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International Colloquium on Coding Theory and Applications

Coding Theory 1986: Coding Theory and Applications pp 154–158Cite as

A weighted-output symbol-by-symbol decoding algorithm of binary convolutional codes

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 311))

Abstract

A weighted-output symbol-by-symbol soft-decision decoding algorithm for convolutional codes is described. Its main intended use concerns concatenation schemes. If a convolutional code is used as inner code, it makes soft-decision decoding of the outer code possible, which improves the overall error rate. This algorithm relies on Bayesian estimation. Its comparison with Battail algorithm using cross-entropy minimisation shows that the latter is a special case of the former.

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References

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Authors and Affiliations

  1. Ecole Nationale Supérieure des Télécommunications, 46, rue Barrault, 75634, Paris Cedex 13, France

    J. C. Belfiore

Authors
  1. J. C. Belfiore
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Editor information

G. Cohen P. Godlewski

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© 1988 Springer-Verlag Berlin Heidelberg

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Belfiore, J.C. (1988). A weighted-output symbol-by-symbol decoding algorithm of binary convolutional codes. In: Cohen, G., Godlewski, P. (eds) Coding Theory and Applications. Coding Theory 1986. Lecture Notes in Computer Science, vol 311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19368-5_17

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  • DOI: https://doi.org/10.1007/3-540-19368-5_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19368-5

  • Online ISBN: 978-3-540-39243-9

  • eBook Packages: Springer Book Archive

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