• DocumentCode
    3160507
  • Title

    Encoding and decoding algorithm of LT codes based on chaotic combination and redundancies

  • Author

    Gao, Hongfeng ; Shi, Ge

  • Author_Institution
    Electron. & Inf. Eng. Coll., Henan Univ. of Sci. & Technol., Luoyang, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    3953
  • Lastpage
    3956
  • Abstract
    According to the traditional encoding and decoding algorithm of LT codes, the degrees and the sets of neighbors of the encoding symbols are chosen uniformly at random via linear congruential method (LCG). The random series generated through this way have poor independence and the disadvantage of correlation between its period and the word size of computer. Those problems considered, chaos map is applied in the implementation of LT codes. The design of the encoding and decoding algorithm of LT codes is based on chaotic combination. In this way, the choice of degrees and the sets of neighbors of the encoding symbols will bring better result. Meanwhile, the exploiting redundancies method is applied to improve the performance of LT decoding. Simulation results show that the encoding and decoding algorithm of LT does based on chaotic combination has the advantage of smaller header packets costs, easier realization. What´s more, its efficiency is higher than that of LCG method. When the number of source samples is small, applying the exploiting redundancies method will further reduce the decoding overhead.
  • Keywords
    chaos; decoding; linear codes; random codes; redundancy; transform coding; LT codes; Luby transform codes; chaotic combination; decoding algorithm; encoding symbol algorithm; header packets costs; linear congruential method; random series code; redundancy method; Algorithm design and analysis; Chaotic communication; Complexity theory; Decoding; Encoding; Redundancy; LT codes; chaotic combination; exploiting redundancies method; kent map; parabolic map; pesudo-random cumber generator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6009899
  • Filename
    6009899