On Design and Efficient Decoding of Sparse Random Linear Network Codes

While random linear network coding is known to improve network reliability and throughput, its high costs for delivering coding coefficients and decoding represent an obstacle where nodes have limited power to transmit and decode packets. In this paper, we propose sparse network codes for scenarios...

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Main Authors:	Ye Li, Wai-Yip Chan, Steven D. Blostein
Format:	Article
Language:	English
Published:	IEEE 2017-01-01
Series:	IEEE Access
Subjects:	Network coding sparse codes random codes generations code overhead efficient decoding
Online Access:	https://ieeexplore.ieee.org/document/8013650/

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spelling	doaj-27bc15acb79a460b933b211b7dba2a762021-03-29T20:05:03ZengIEEEIEEE Access2169-35362017-01-015170311704410.1109/ACCESS.2017.27419728013650On Design and Efficient Decoding of Sparse Random Linear Network CodesYe Li0https://orcid.org/0000-0002-3279-8083Wai-Yip Chan1Steven D. Blostein2School of Electronics and Information, Nantong University, Nantong, ChinaDepartment of Electrical and Computer Engineering, Queen’s University, Kingston, ON, CanadaDepartment of Electrical and Computer Engineering, Queen’s University, Kingston, ON, CanadaWhile random linear network coding is known to improve network reliability and throughput, its high costs for delivering coding coefficients and decoding represent an obstacle where nodes have limited power to transmit and decode packets. In this paper, we propose sparse network codes for scenarios where low coding vector weights and low decoding cost are crucial. We consider generation-based network codes where source packets are grouped into overlapping subsets called generations, and coding is performed only on packets within the same generation in order to achieve sparseness and low complexity. A sparse code is proposed that is comprised of a precode and random overlapping generations. The code is shown to be much sparser than existing codes that enjoy similar code overhead. To efficiently decode the proposed code, a novel low-complexity overhead-optimized decoder is proposed where code sparsity is exploited through local processing and multiple rounds of pivoting. Through extensive simulation comparison with existing schemes, we show that short transmissions of the order of 10<sup>2</sup> -10<sup>3</sup> source packets, a denomination convenient for many applications of interest, can be efficiently decoded by the proposed decoder.https://ieeexplore.ieee.org/document/8013650/Network codingsparse codesrandom codesgenerationscode overheadefficient decoding
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Ye Li Wai-Yip Chan Steven D. Blostein
spellingShingle	Ye Li Wai-Yip Chan Steven D. Blostein On Design and Efficient Decoding of Sparse Random Linear Network Codes IEEE Access Network coding sparse codes random codes generations code overhead efficient decoding
author_facet	Ye Li Wai-Yip Chan Steven D. Blostein
author_sort	Ye Li
title	On Design and Efficient Decoding of Sparse Random Linear Network Codes
title_short	On Design and Efficient Decoding of Sparse Random Linear Network Codes
title_full	On Design and Efficient Decoding of Sparse Random Linear Network Codes
title_fullStr	On Design and Efficient Decoding of Sparse Random Linear Network Codes
title_full_unstemmed	On Design and Efficient Decoding of Sparse Random Linear Network Codes
title_sort	on design and efficient decoding of sparse random linear network codes
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2017-01-01
description	While random linear network coding is known to improve network reliability and throughput, its high costs for delivering coding coefficients and decoding represent an obstacle where nodes have limited power to transmit and decode packets. In this paper, we propose sparse network codes for scenarios where low coding vector weights and low decoding cost are crucial. We consider generation-based network codes where source packets are grouped into overlapping subsets called generations, and coding is performed only on packets within the same generation in order to achieve sparseness and low complexity. A sparse code is proposed that is comprised of a precode and random overlapping generations. The code is shown to be much sparser than existing codes that enjoy similar code overhead. To efficiently decode the proposed code, a novel low-complexity overhead-optimized decoder is proposed where code sparsity is exploited through local processing and multiple rounds of pivoting. Through extensive simulation comparison with existing schemes, we show that short transmissions of the order of 10<sup>2</sup> -10<sup>3</sup> source packets, a denomination convenient for many applications of interest, can be efficiently decoded by the proposed decoder.
topic	Network coding sparse codes random codes generations code overhead efficient decoding
url	https://ieeexplore.ieee.org/document/8013650/
work_keys_str_mv	AT yeli ondesignandefficientdecodingofsparserandomlinearnetworkcodes AT waiyipchan ondesignandefficientdecodingofsparserandomlinearnetworkcodes AT stevendblostein ondesignandefficientdecodingofsparserandomlinearnetworkcodes
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On Design and Efficient Decoding of Sparse Random Linear Network Codes

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