• DocumentCode
    3126976
  • Title

    Distance spectrum estimation of LDPC convolutional codes

  • Author

    Hua Zhou ; Mitchell, David ; Goertz, N. ; Costello, Daniel J.

  • Author_Institution
    Inst. of Telecommun., Vienna Univ. of Technol., Vienna, Austria
  • fYear
    2012
  • fDate
    1-6 July 2012
  • Firstpage
    473
  • Lastpage
    477
  • Abstract
    Time-invariant low-density parity-check convolutional codes (LDPC-CCs) derived from corresponding quasi-cyclic (QC) LDPC block codes (LDPC-BCs) can be described by a polynomial syndrome former matrix (polynomial-domain transposed parity-check matrix). In this paper, an estimation of the distance spectrum of time-invariant LDPC-CCs is obtained by splitting the polynomial syndrome former matrix into submatrices representing “super codes” and then evaluating the linear dependence between codewords of the corresponding super codes. This estimation results in an upper bound on the minimum free distance of the original code and, additionally, a lower bound on the number of codewords Aw with Hamming weight w.
  • Keywords
    block codes; convolutional codes; cyclic codes; parity check codes; Hamming weight; LDPC convolutional codes; LDPC-B; distance spectrum estimation; low density parity check codes; polynomial domain transposed parity check matrix; polynomial syndrome former matrix; quasicyclic LDPC block codes; super codes; Block codes; Complexity theory; Convolutional codes; Hamming weight; Parity check codes; Polynomials; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
  • Conference_Location
    Cambridge, MA
  • ISSN
    2157-8095
  • Print_ISBN
    978-1-4673-2580-6
  • Electronic_ISBN
    2157-8095
  • Type

    conf

  • DOI
    10.1109/ISIT.2012.6284234
  • Filename
    6284234