• DocumentCode
    2945367
  • Title

    Adaptive Linear Programming Decoding

  • Author

    Taghavi, Mohammad H. ; Siegel, Paul H.

  • Author_Institution
    Dept. of ECE, California Univ., San Diego, CA
  • fYear
    2006
  • fDate
    9-14 July 2006
  • Firstpage
    1374
  • Lastpage
    1378
  • Abstract
    The ability of linear programming (LP) decoding to detect failures, and its potential for improvement by the addition of new constraints, motivates the use of an adaptive approach in selecting the constraints for the underlying LP problem. In this paper, we show that the application of such adaptive methods can significantly reduce the complexity of the LP decoding algorithm, which, in the standard formulation, is exponential in the maximum row weight of the parity-check matrix. We further show that adaptively adding new constraints, e.g. by combining parity checks, can provide large gains in LP decoder performance
  • Keywords
    adaptive decoding; linear programming; matrix algebra; parity check codes; LP decoder performance; adaptive linear programming decoding; failure detection; maximum row weight; parity-check matrix; Degradation; Iterative algorithms; Iterative decoding; Iterative methods; Linear programming; Maximum likelihood decoding; Maximum likelihood detection; Parity check codes; Performance gain; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2006 IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    1-4244-0505-X
  • Electronic_ISBN
    1-4244-0504-1
  • Type

    conf

  • DOI
    10.1109/ISIT.2006.262071
  • Filename
    4036191