• DocumentCode
    169290
  • Title

    A complete MacWilliams theorem for convolutional codes

  • Author

    Ching-Yi Lai ; Min-Hsiu Hsieh ; Hsiao-feng Lu

  • Author_Institution
    Centre for Quantum Comput. & Intell. Syst., Univ. of Technol. Sydney, Sydney, NSW, Australia
  • fYear
    2014
  • fDate
    2-5 Nov. 2014
  • Firstpage
    157
  • Lastpage
    161
  • Abstract
    In this paper, we prove a MacWilliams identity for the weight adjacency matrices based on the constraint codes of a convolutional code (CC) and its dual. Our result improves upon a recent result by Gluesing-Luerssen and Schneider, where the requirement of a minimal encoder is assumed. We can also establish the MacWilliams identity for the input-parity weight adjacency matrices of a systematic CC and its dual. Most importantly, we show that a type of Hamming weight enumeration functions of all codewords of a CC can be derived from the weight adjacency matrix, which thus provides a connection between these two very different notions of weight enumeration functions in the convolutional code literature. Finally, the relations between various enumeration functions of a CC and its dual are summarized in a diagram. This explains why no MacWilliams identity exists for the free-distance enumerators.
  • Keywords
    Hamming codes; convolutional codes; matrix algebra; Gluesing-Luerssen; Hamming weight enumeration functions; MacWilliams identity; MacWilliams theorem; Schneider; codewords; convolutional codes; input-parity weight adjacency matrices; Convolutional codes; Fourier transforms; Hamming weight; Kernel; Optical wavelength conversion; Systematics; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Workshop (ITW), 2014 IEEE
  • Conference_Location
    Hobart, TAS
  • ISSN
    1662-9019
  • Type

    conf

  • DOI
    10.1109/ITW.2014.6970812
  • Filename
    6970812