• DocumentCode
    2945327
  • Title

    Pseudo-Codewords in LDPC Convolutional Codes

  • Author

    Smarandache, R. ; Pusane, Ali E. ; Vontobel, P.O. ; Costello, D.J.

  • Author_Institution
    Dept. of Math. & Stat., San Diego State Univ., CA
  • fYear
    2006
  • fDate
    9-14 July 2006
  • Firstpage
    1364
  • Lastpage
    1368
  • Abstract
    Iterative message-passing decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of message-passing decoding to be worse than that predicted by the maximum-likelihood decoding union bound. In this paper we study the pseudo-codeword problem for the class of LDPC convolutional codes decoded continuously using an iterative, sliding window, message-passing decoder. In particular, for an LDPC convolutional code derived by unwrapping a quasi-cyclic LDPC block code, we show that the free pseudo-weight of the convolutional code is at least as large as the minimum pseudo-weight of the underlying quasi-cyclic code. This result parallels the well-known relationship between the free Hamming distance of convolutional codes and the minimum Hamming distance of their quasi-cyclic counterparts. Finally, simulation results are included that show improved performance for unwrapped LDPC convolutional codes compared to their underlying quasi-cyclic codes
  • Keywords
    Hamming codes; block codes; convolutional codes; cyclic codes; maximum likelihood decoding; parity check codes; Hamming distance; decoding failures; iterative sliding window message-passing decoders; low-density parity-check block codes; maximum-likelihood decoding union bound; minimum pseudo-weight; pseudo-codeword problem; quasi-cyclic LDPC block code; signal-to-noise ratio performance; unwrapped LDPC convolutional codes; Bit error rate; Block codes; Convolutional codes; Hamming distance; Iterative decoding; Linear code; Maximum likelihood decoding; Parity check codes; Polynomials; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2006 IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    1-4244-0505-X
  • Type

    conf

  • DOI
    10.1109/ISIT.2006.262069
  • Filename
    4036189