• DocumentCode
    1454180
  • Title

    Efficient erasure correcting codes

  • Author

    Luby, Michael G. ; Mitzenmacher, Michael ; Shokrollahi, M. Amin ; Spielman, Daniel A.

  • Author_Institution
    Int. Comput. Sci. Inst., Berkeley, CA, USA
  • Volume
    47
  • Issue
    2
  • fYear
    2001
  • fDate
    2/1/2001 12:00:00 AM
  • Firstpage
    569
  • Lastpage
    584
  • Abstract
    We introduce a simple erasure recovery algorithm for codes derived from cascades of sparse bipartite graphs and analyze the algorithm by analyzing a corresponding discrete-time random process. As a result, we obtain a simple criterion involving the fractions of nodes of different degrees on both sides of the graph which is necessary and sufficient for the decoding process to finish successfully with high probability. By carefully designing these graphs we can construct for any given rate R and any given real number ε a family of linear codes of rate R which can be encoded in time proportional to ln(1/ε) times their block length n. Furthermore, a codeword can be recovered with high probability from a portion of its entries of length (1+ε)Rn or more. The recovery algorithm also runs in time proportional to n ln(1/ε). Our algorithms have been implemented and work well in practice; various implementation issues are discussed
  • Keywords
    decoding; error correction codes; graph theory; linear codes; probability; random processes; block length; code rate; codeword recovery; decoding; discrete-time random process; efficient erasure correcting codes; erasure recovery algorithm; linear codes; linear error correcting codes; probability; sparse bipartite graphs; Algorithm design and analysis; Bipartite graph; Computer science; Decoding; Error correction codes; Galois fields; Linear code; Parity check codes; Random processes; Vectors;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.910575
  • Filename
    910575