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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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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