• DocumentCode
    1283046
  • Title

    On Universal LDPC Code Ensembles Over Memoryless Symmetric Channels

  • Author

    Sason, Igal ; Shuval, Boaz

  • Author_Institution
    Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
  • Volume
    57
  • Issue
    8
  • fYear
    2011
  • Firstpage
    5182
  • Lastpage
    5202
  • Abstract
    A design of robust error-correcting codes that achieve reliable communication over various channels is of great theoretical and practical interest. Such codes are termed universal. This paper considers the universality of low-density parity-check (LDPC) code ensembles over families of memoryless binary-input output-symmetric (MBIOS) channels. Universality is considered both under belief-propagation (BP) and maximum-likelihood (ML) decoding. For the BP decoding case, we derive a density-evolution-based analytical method for designing LDPC code ensembles that are universal over various families of MBIOS channels. We also derive a necessary condition for universality of LDPC code ensembles under BP decoding; this condition is used to provide bounds on the universally achievable fraction of capacity. These results enable us to provide conditions for reliable/unreliable communications under BP decoding that are based on the Bhattacharyya parameter of the channel. For the ML decoding case, we prove that properly selected regular LDPC code ensembles are universally capacity-achieving for the set of equi-capacity MBIOS channels and extend this result to punctured regular LDPC code ensembles.
  • Keywords
    linear programming; maximum likelihood decoding; memoryless systems; parity check codes; sparse matrices; belief-propagation; error-correcting codes; low-density parity-check code; maximum-likelihood decoding; memoryless symmetric channels; reliable communication; universal LDPC code ensembles; Asymptotic stability; Channel capacity; Error probability; Iterative decoding; Maximum likelihood decoding; Belief propagation (BP); Bhattacharyya parameter (B-parameter); density evolution (DE); linear programming (LP) bounds; low-density parity-check (LDPC) codes; maximum-likelihood (ML); memoryless binary-input output-symmetric (MBIOS) channels; stability;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2011.2158489
  • Filename
    5961846