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
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;
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
DOI :
10.1109/ISIT.2006.261653