• DocumentCode
    2974741
  • Title

    Detection and blind identification of m-sequence codes using higher order statistics

  • Author

    Batty, K.E. ; Adams, E.R.

  • Author_Institution
    RMCS, Cranfield Univ., UK
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    16
  • Lastpage
    20
  • Abstract
    The blind identification of m-sequences from short noisy intercepts remains intractable using second-order statistics. Previous work has shown that the triple correlation function provides a basis for such identification. By extending the field theory of m-sequences, new techniques are developed which allow the automatic derivation of their generator polynomials. Statistical theory is presented for the triple correlation of m-sequences with discrete errors resulting from hard decoding. Efficient C-implemented algorithms enable extended simulation to assess the new technique´s performance for varying noise level and intercept length
  • Keywords
    correlation theory; higher order statistics; m-sequences; polynomials; sequential decoding; sequential estimation; signal detection; C-implemented algorithms; blind identification; detection; discrete errors; field theory; generator polynomials; hard decoding; higher order statistics; m-sequence codes; noise level; performance; short noisy intercepts; simulation; statistical theory; triple correlation function; Additive white noise; Code standards; Decoding; Galois fields; Gaussian noise; Higher order statistics; Noise level; Polynomials; Signal detection; Spread spectrum communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
  • Conference_Location
    Caesarea
  • Print_ISBN
    0-7695-0140-0
  • Type

    conf

  • DOI
    10.1109/HOST.1999.778683
  • Filename
    778683