Multicast Convolutional Network Codes via Local Encoding Kernels

A 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...

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Main Authors:	Morteza Rekab-Eslami, Morteza Esmaeili, Thomas Aaron Gulliver
Format:	Article
Language:	English
Published:	IEEE 2017-01-01
Series:	IEEE Access
Subjects:	Cyclic network multicast edge-disjoint cycles flow local encoding kernel
Online Access:	https://ieeexplore.ieee.org/document/7895122/

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spelling	doaj-3de0ad2008334051b1a2828a002c130b2021-03-29T20:09:35ZengIEEEIEEE Access2169-35362017-01-0156464647010.1109/ACCESS.2017.26897817895122Multicast Convolutional Network Codes via Local Encoding KernelsMorteza Rekab-Eslami0Morteza Esmaeili1Thomas Aaron Gulliver2https://orcid.org/0000-0001-9919-0323Isfahan University of Technology, Isfahan, IranIsfahan University of Technology, Isfahan, IranUniversity of Victoria, Victoria, BC, CanadaA 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.https://ieeexplore.ieee.org/document/7895122/Cyclic networkmulticastedge-disjoint cyclesflowlocal encoding kernel
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Morteza Rekab-Eslami Morteza Esmaeili Thomas Aaron Gulliver
spellingShingle	Morteza Rekab-Eslami Morteza Esmaeili Thomas Aaron Gulliver Multicast Convolutional Network Codes via Local Encoding Kernels IEEE Access Cyclic network multicast edge-disjoint cycles flow local encoding kernel
author_facet	Morteza Rekab-Eslami Morteza Esmaeili Thomas Aaron Gulliver
author_sort	Morteza Rekab-Eslami
title	Multicast Convolutional Network Codes via Local Encoding Kernels
title_short	Multicast Convolutional Network Codes via Local Encoding Kernels
title_full	Multicast Convolutional Network Codes via Local Encoding Kernels
title_fullStr	Multicast Convolutional Network Codes via Local Encoding Kernels
title_full_unstemmed	Multicast Convolutional Network Codes via Local Encoding Kernels
title_sort	multicast convolutional network codes via local encoding kernels
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2017-01-01
description	A 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.
topic	Cyclic network multicast edge-disjoint cycles flow local encoding kernel
url	https://ieeexplore.ieee.org/document/7895122/
work_keys_str_mv	AT mortezarekabeslami multicastconvolutionalnetworkcodesvialocalencodingkernels AT mortezaesmaeili multicastconvolutionalnetworkcodesvialocalencodingkernels AT thomasaarongulliver multicastconvolutionalnetworkcodesvialocalencodingkernels
_version_	1724195188957511680

Multicast Convolutional Network Codes via Local Encoding Kernels

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