Multicast Convolutional Network Codes via Local Encoding Kernels

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dc.contributor.authorRekab-Eslami, Morteza
dc.contributor.authorEsmaeili, Morteza
dc.contributor.authorGulliver, Thomas Aaron
dc.date.accessioned2018-07-19T14:19:40Z
dc.date.available2018-07-19T14:19:40Z
dc.date.copyright2017en_US
dc.date.issued2017
dc.description.abstractA convolutional network (CN) code can be described by either global encoding kernels (GEKs) or local encoding kernels (LEKs). In the literature, the multicast property of a CN code is described using GEKs, so the design algorithms for multicast CN codes employ GEKs to check this property. For cyclic networks, using GEKs makes the design algorithms time-consuming. In this paper, a new approach is proposed for the design of multicast CN codes for networks with cycles. First, a formula is presented to describe the multicast property using LEKs rather than GEKs. Then, this formula is used to develop a design algorithm for multicast CN codes. This algorithm does not use GEKs, which makes it more efficient than GEK-based algorithms, particularly for large cyclic networks.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.identifier.citationRekab-Eslami, M.; Esmaeili, M.; & Gulliver, T. A. (2017). Multicast convolutional network codes via local encoding kernels. IEEE Access, 5, 6464-6470.en_US
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2017.2689781
dc.identifier.urihttp://hdl.handle.net/1828/9723
dc.language.isoenen_US
dc.publisherIEEE Accessen_US
dc.subjectcyclic network
dc.subjectmulticast
dc.subjectedge-disjoint cycles
dc.subjectflow
dc.subjectlocal encoding kernel
dc.subject.departmentDepartment of Electrical and Computer Engineering
dc.titleMulticast Convolutional Network Codes via Local Encoding Kernelsen_US
dc.typeArticleen_US

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