• DocumentCode
    1848016
  • Title

    A study on quick simulation for estimation of low FER of LDPC codes

  • Author

    Sakai, Takakazu ; Shibata, Koji

  • Author_Institution
    Dept. of Comput. Sci., Kitami Inst. of Technol., Kitami, Japan
  • fYear
    2009
  • fDate
    15-17 Dec. 2009
  • Firstpage
    468
  • Lastpage
    473
  • Abstract
    This study shows a new design method of a simulation probability density function (PDF) for a fast frame error rate (FER) evaluation of low-density parity-check (LDPC) codes. It is difficult to evaluate a very low FER of LDPC codes by Monte Carlo simulation methods since it has excellent performance under iterative decoding. Cole et al. proposed a three-step estimation method of the low FER of LDPC codes of moderate block length. By applying the importance sampling method, which is one of the fast simulation methods, the simulation time of the error performance of LDPC codes can be reduced. Another simulation PDF, which can treat more dominant trapping sets (TS) than Cole et al.´s method, is proposed. The selection of the dominant TS as proportional to its probability reduces the number of simulation runs without deteriorating the accuracy of the estimator. Unbiased estimator is given as well as that that of the Cole et al.´s method. Some numerical examples are shown to demonstrate the effectiveness of the proposed method. The simulation time for an LDPC code of length 504 is reduced to 1/10 when we evaluate FER of around 10-14.
  • Keywords
    Monte Carlo methods; block codes; parity check codes; set theory; FER estimation; LDPC codes; Monte Carlo simulation methods; block length; fast frame error rate; importance sampling method; low-density parity-check; probability density function; three-step estimation method; trapping sets; AWGN; Design methodology; Error analysis; Error probability; Frequency estimation; Iterative decoding; Monte Carlo methods; Parity check codes; Probability density function; Signal to noise ratio; LDPC codes; fast simulation; importance sampling; simulation probability density function; trapping set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (MICC), 2009 IEEE 9th Malaysia International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-5531-7
  • Type

    conf

  • DOI
    10.1109/MICC.2009.5431553
  • Filename
    5431553