• DocumentCode
    1893644
  • Title

    An efficient decoding algorithm for cycle-free convolutional codes and its applications

  • Author

    Li, Jing ; Narayanan, Krishna R. ; Georghlades, C.N.

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1063
  • Abstract
    This paper proposes an efficient graph-based sum-product algorithm for decoding 1/(1+Dn) code, whose Tanner (1981) graph is cycle-free. A rigorous proof is given which shows the proposed algorithm is equivalent to the MAP decoding implementing the BCJR algorithm, but with a lower complexity magnitude. The paper presents an explicit example which confirms the claim that the sum-product algorithm is optimal on cycle-free graphs. A parallel realization is then discussed and shown to resemble low density parity check (LDPC) decoding. The paper further proposes a min-sum algorithm which is equivalent to the max-log-MAP algorithm. Prospective applications which can take advantage of the proposed decoding algorithms are discussed and simulations are provided
  • Keywords
    approximation theory; convolutional codes; decoding; graph theory; BCJR algorithm; LDPC decoding; MAP decoding; cycle-free Tanner graph; cycle-free convolutional codes; decoding algorithms; efficient decoding algorithm; graph-based sum-product algorithm; low density parity check; low-complexity approximation; max-log-MAP algorithm; min-sum algorithm; simulations; Approximation algorithms; Bayesian methods; Convolutional codes; Geometry; Iterative algorithms; Iterative decoding; Parity check codes; Signal processing algorithms; Sum product algorithm; Turbo codes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE
  • Conference_Location
    San Antonio, TX
  • Print_ISBN
    0-7803-7206-9
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2001.965634
  • Filename
    965634