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Construction of convolutional network coding for cyclic multicast networks

  • Qin Guo*
  • , Mingxing Luo
  • , Lixiang Li
  • , Licheng Wang
  • , Yixian Yang
  • *Corresponding author for this work
  • Beijing University of Posts and Telecommunications

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we present a practical algorithm to construct the convolutional multicast network coding over any finite directed cyclic network. The dual line graph of a directed cyclic graph is considered as a system. By regarding the global encoding kernels in the original graph as the corresponding inputs or outputs of some subsystem and the local encoding kernels in original graph as gains of channels, we can construct the convolutional network code through randomly choosing the local encoding kernels of the directed cycles in networks. By using Mason formula, the construction becomes very efficient.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE 2nd Symposium on Web Society, SWS 2010
Pages336-341
Number of pages6
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE 2nd Symposium on Web Society, SWS 2010 - Beijing, China
Duration: 16 Aug 201017 Aug 2010

Publication series

NameProceedings - 2010 IEEE 2nd Symposium on Web Society, SWS 2010

Conference

Conference2010 IEEE 2nd Symposium on Web Society, SWS 2010
Country/TerritoryChina
CityBeijing
Period16/08/1017/08/10

Keywords

  • Convolutional multicast
  • Convolutional network code
  • Dual line graph
  • Mason formula

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