• DocumentCode
    2946868
  • Title

    On Convolutional Network Coding

  • Author

    Li, Shuo-Yen Robert ; Yeung, Raymond W.

  • Author_Institution
    Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin
  • fYear
    2006
  • fDate
    9-14 July 2006
  • Firstpage
    1743
  • Lastpage
    1747
  • Abstract
    Convolutional network coding deals with the propagation of a message pipeline through a cyclic network. We formulate a Convolutional network code by associating every pair of adjacent channels with a rational power series over the base field, called the local encoding kernel, and every channel with a concomitant global encoding kernel, which is a vector of rational power series. Given a complete set of local encoding kernels, a close-form formula is derived for calculating the global encoding kernels. A convolutional multicast is a convolutional network code that every qualified receiving node can decode the message. We offer a construction algorithm for a convolutional multicast as well as a decoding algorithm
  • Keywords
    channel coding; convolutional codes; multicast communication; telecommunication networks; adjacent channels; close-form formula; convolutional multicast; convolutional network coding; local encoding kernel; message decoding; message pipeline; Communication networks; Convolution; Convolutional codes; Decoding; Galois fields; Kernel; Multicast algorithms; Network coding; Power engineering and energy; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2006 IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    1-4244-0505-X
  • Electronic_ISBN
    1-4244-0504-1
  • Type

    conf

  • DOI
    10.1109/ISIT.2006.261653
  • Filename
    4036266