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Décodage Syndromique à Complexité Réduite Pour Codes Convolutifs

Low complexity syndrome algorithm for the decoding of convolutional codes

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Résumé

Le décodage au sens du maximum de vraisemblance des codes convolutifs est effectué de manière classique à l’aide l’algorithme de Viterbi (Va). Nous proposons un décodeur à entrées fermes ou pondérées dans lequel l’algorithme de Viterbi, associé à une métrique appropriée, est employé pour identifier le vecteur d’erreur plutôt que le message d’information. Ce type de décodage permet d’éviter la mise en uvre d’un nombre important d’opérations Acs (Addition Comparaison Sélection). Nous montrons que les performances atteintes sont optimales pour un décodage à décisions fermes et très proches de l’optimum dans le cas d’entrées pondérées, tout en procurant une réduction de la complexité qui est d’autant plus importante que le rapport Ec/No (énergie par bit transmis sur densité de puissance monolatérale de bruit) est élevé (par exemple, pour des rapports Ec/No supérieurs à 3 dB, plus de 80 % des opérations ACS peuvent être évitées). Nous proposons également un algorithme permettant de rejeter un paquet sans avoir à effectuer les itérations de l’algorithme de Viterbi.

Abstract

The decoding of convolutional codes in the maximum likelihood sense is carried out in a traditional way with the Viterbi algorithm (Va). We proposed a soft and hard input decoder where theVa, associated with an relevant metric, is applied to identify the error vector rather than the information message. In this paper, we show that, with this type of decoding, the exhaustive computation of a majority ofAcs (Add Compare Select) is unnecessary. Moreover, we show that optimal performance is achieved in the case of a hard input decoder, and that performance closed to the optimum is achieved in the case of a soft input decoder, while offering of a reduction of the complexity which is all the more important than the Ec/No ratio is high (e. g. for ratio Ec/No greater than 3 dB, more than 80 % of theAcs can be avoided). We also propose an algorithm allowing rejecting a frame without having to carry out any iteration of theVa.

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Authors and Affiliations

  1. École Supérieure d’Électricité, Dpt. Telecommunications, SUPELEC, Plateau de Moulon, 91192, Gif-sur-Yvette, France

    Jacques Antoine, Lionel Husson, Armelle Wautier & Jean-Claude Dany

  2. Alcatel Research and Innovation, Route de Nozay, 91461, Marcoussis cedex, France

    Nicolas Paul & Jérôme Brouet

Authors
  1. Jacques Antoine
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  2. Lionel Husson
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  3. Armelle Wautier
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  4. Nicolas Paul
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  5. Jean-Claude Dany
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  6. Jérôme Brouet
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Antoine, J., Husson, L., Wautier, A. et al. Décodage Syndromique à Complexité Réduite Pour Codes Convolutifs. Ann. Télécommun. 60, 1080–1102 (2005). https://doi.org/10.1007/BF03219960

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  • DOI: https://doi.org/10.1007/BF03219960

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