arrow
Return

Multicast Convolutional Network Codes via Local Encoding Kernels

delete2017-01-01
delete5
delete
OA
AI
M
Morteza Esmaeili
T
T. Aaron Gulliver *
DOI:10.1109/ACCESS.2017.2689781delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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.
Keywords:
Cyclic network
multicast
edge-disjoint cycles
flow
local encoding kernel
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

U
University of Victoria
Scholars:
1.0W
Papers: 1.0W
Citations: 1.5W
I
Isfahan University of Technology
Scholars:
9.0K
Papers: 8.6K
Citations: 8.7K