Advertisement

On the Fly Belief Propagation Decoding Algorithm for LT Codes

  • Longlong Suo
  • Gengxin Zhang
  • Dongmin Bian
  • Jing Lv
  • Haiping Chen
  • Zijun Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

As the first realisation of Fountain Codes, Luby Transform (LT) codes provide high reliability and scalability and low complexities for data transmission in networks. Two basic algorithms, Belief Propagation (BP) and Gaussian Elimination (GE), were introduced to decode LT codes. However, both of them execute their decoding process only after all the encoded symbols have been received by decoder, which results in the waste of time, storage space and computing resource. In this paper, an improved decoding algorithm termed on the fly belief propagation (OFBP) for LT codes is proposed. Based on the BP algorithm, OFBP performs the decoding processing once each encoded symbol arrives thus distributing the decoding work during all symbols reception. Compared with the traditional BP algorithm, the actual decoding time of the proposed algorithm is highly shortened. Moreover, without processing all the encoded symbols, the actual storage space and decoding complexity are greatly reduced while maintaining the same performance relative to the traditional BP decoding scheme.

Keywords

Fountain codes LT codes Belief Propagation On the fly Decoding algorithm 

References

  1. 1.
    Byers, J.W., Luby, M., Mitzenmacher, M., Rege, A.: A digital fountain approach to reliable distribution of bulk data. ACM SIGCOMM 28(4), 56–67 (1998)Google Scholar
  2. 2.
    Luby M.: LT codes. In: Proceedings 43rd Annual IEEE Symposium on Foundations of Computer Science, pp. 271–282 (2002)Google Scholar
  3. 3.
    Mackay, D.J.C.: Fountain codes. IEEE Proc. Commun. 152(6), 1062–1068 (2005)Google Scholar
  4. 4.
    Shokrollahi, A.: Raptor codes. IEEE Trans. Inf. Theory 52(6), 2551–2567 (2006)Google Scholar
  5. 5.
    Luby, M., Mitzenmacher, M., Shokrollahi, A., Spielman, A.: Efficient erasure correcting codes. IEEE Trans. Inf. Theory 47(2), 569–584 (2001)Google Scholar
  6. 6.
    Puducheri, S., Kliewer, J., Fuja, T.E.: Distributed LT codes. In: IEEE International Symposium Information Theory, pp. 987–991 (2006)Google Scholar
  7. 7.
    Yuan, X., Ping, L.: On systematic LT codes. IEEE Commun. Lett. 12(9), 681–683 (2008)Google Scholar
  8. 8.
    Sorensen, J.H., Popovski, P., Ostergaard, J.: Design and analysis of LT codes with decreasing ripple size. IEEE Trans. Commun. 60(11), 3191–3197 (2012)Google Scholar
  9. 9.
    Huang, Y., Lei, J., Wei, J.: Joint network and fountain codes design for relay-assisted multi-user system. China Commun. 12(7), 96–107 (2015)Google Scholar
  10. 10.
    Kim, S., Ko, K., Chung, S.Y.: Incremental Gaussian elimination decoding of raptor codes over BEC. IEEE Commun. Lett. 12(4), 307–309 (2008)Google Scholar
  11. 11.
    Anglano, C., Gaeta, R., Grangetto, M.: Exploiting rateless codes in cloud storage systems. IEEE Trans. Parallel Distrib. Syst. 26(5), 1313–1322 (2015)Google Scholar
  12. 12.
    Bioglio, V., Grangetto, M., Gaeta, R., Sereno, M.: On the fly Gaussian elimination for LT codes. IEEE Commun. Lett. 13(12), 953–955 (2009)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Longlong Suo
    • 1
  • Gengxin Zhang
    • 2
  • Dongmin Bian
    • 1
  • Jing Lv
    • 1
  • Haiping Chen
    • 3
  • Zijun Liu
    • 4
  1. 1.The PLA University of Science and TechnologyNanjingChina
  2. 2.Nanjing University of Posts and TelecommunicationsNanjingChina
  3. 3.The Chongqing Communication InstituteChongqingChina
  4. 4.The First Engineers Scientific Research InstituteWuxiChina

Personalised recommendations