Abstract
Similar to acyclic networks, over cyclic networks, there also exist four classes of optimal convolutional network codes, which are referred to as basic convolutional network code (BCNC), convolutional dispersion (CD), convolutional broadcast (CB), and convolutional multicast (CM), respectively. And from the perspective of linear independence among the global encoding kernels (GEKs), BCNC is with the best strength. In this paper, we present an efficient construction algorithm for BCNC over cyclic networks. Our algorithm can positively provide the maximal required cardinality of the local encoding kernels (LEKs). Another advantage of this algorithm is that for an existing code, when some non-source nodes and associated edges are added, our algorithm can correspondingly modify the already assigned LEKs in a localized manner. And we can just reset the LEKs along some special flow paths educed by the added nodes and edges, rather than reconstructing the whole code in its expanding network.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: AEUE - International Journal of Electronics and Communications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
