• DocumentCode
    1454207
  • Title

    Efficient encoding of low-density parity-check codes

  • Author

    Richardson, Thomas J. ; Urbanke, Rüdiger L.

  • Author_Institution
    Lucent Technol. Bell Labs., Murray Hill, NJ, USA
  • Volume
    47
  • Issue
    2
  • fYear
    2001
  • fDate
    2/1/2001 12:00:00 AM
  • Firstpage
    638
  • Lastpage
    656
  • Abstract
    Low-density parity-check (LDPC) codes can be considered serious competitors to turbo codes in terms of performance and complexity and they are based on a similar philosophy: constrained random code ensembles and iterative decoding algorithms. We consider the encoding problem for LDPC codes. More generally we consider the encoding problem for codes specified by sparse parity-check matrices. We show how to exploit the sparseness of the parity-check matrix to obtain efficient encoders. For the (3,6)-regular LDPC code, for example, the complexity of encoding is essentially quadratic in the block length. However, we show that the associated coefficient can be made quite small, so that encoding codes even of length n≃100000 is still quite practical. More importantly, we show that “optimized” codes actually admit linear time encoding
  • Keywords
    computational complexity; error detection codes; iterative decoding; optimisation; random codes; sparse matrices; binary erasure channel; block length; code length; coefficient; complexity; constrained random code ensembles; efficient encoding; iterative decoding algorithms; linear time encoding; low-density parity-check codes; optimized codes; performance; regular LDPC code; sparse parity-check matrices; turbo codes; Algorithm design and analysis; Channel capacity; Encoding; Iterative algorithms; Iterative decoding; Parity check codes; Physics; Sparse matrices; Technological innovation; Turbo codes;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.910579
  • Filename
    910579