Performance Analysis of Raptor Codes under Maximum Likelihood Decoding

Wang, P; Mao, G; Lin, Z; Ding, M; Liang, W; Ge, X

Performance Analysis of Raptor Codes under Maximum Likelihood Decoding

Wang, P Mao, G

Lin, Z Ding, M Liang, W Ge, X

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Communications, 2016, 64 (3), pp. 906 - 917
Issue Date:: 2016-03-01

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Field	Value	Language
dc.contributor.author	Wang, P	en_US
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949	en_US
dc.contributor.author	Lin, Z	en_US
dc.contributor.author	Ding, M	en_US
dc.contributor.author	Liang, W	en_US
dc.contributor.author	Ge, X	en_US
dc.date.issued	2016-03-01	en_US
dc.identifier.citation	IEEE Transactions on Communications, 2016, 64 (3), pp. 906 - 917	en_US
dc.identifier.issn	0090-6778	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122545
dc.description.abstract	© 2016 IEEE. In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic low-density generator-matrix code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds on the decoding failure probability. The accuracy of our analysis is validated through simulations. Results of extensive Monte Carlo simulations demonstrate that for Raptor codes with different degree distributions and pre-codes, the bounds obtained in this paper are of high accuracy. The derived bounds can be used to design near-optimum Raptor codes with short and moderate lengths.	en_US
dc.relation.ispartof	IEEE Transactions on Communications	en_US
dc.relation.isbasedon	10.1109/TCOMM.2016.2522403	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Performance Analysis of Raptor Codes under Maximum Likelihood Decoding	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	64	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0804 Data Format	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access	*
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	64	en_US

Abstract:

© 2016 IEEE. In this paper, we analyze the maximum likelihood decoding performance of Raptor codes with a systematic low-density generator-matrix code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds on the decoding failure probability. The accuracy of our analysis is validated through simulations. Results of extensive Monte Carlo simulations demonstrate that for Raptor codes with different degree distributions and pre-codes, the bounds obtained in this paper are of high accuracy. The derived bounds can be used to design near-optimum Raptor codes with short and moderate lengths.

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http://hdl.handle.net/10453/122545