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Low-Floor Tanner Codes via Hamming-Node or RSCC-Node Doping

Abu-Surra, Shadi and Liva, Gianluigi and Ryan, William E. (2006) Low-Floor Tanner Codes via Hamming-Node or RSCC-Node Doping. Lecture Notes in Computer Science, pp. 245-254. ISBN 3-540-31423-7

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Abstract

We study the design of structured Tanner codes with low error-rate floors on the AWGN channel. The design technique involves the “doping” of standard LDPC (proto-)graphs, by which we mean Hamming or recursive systematic convolutional (RSC) code constraints are used together with single-parity-check (SPC) constraints to construct a code’s protograph. We show that the doping of a “good” graph with Hamming or RSC codes is a pragmatic approach that frequently results in a code with a good threshold and very low error-rate floor. We focus on low-rate Tanner codes, in part because the design of low-rate, low-floor LDPC codes is particularly difficult. Lastly, we perform a simple complexity analysis of our Tanner codes and examine the performance of lower-complexity, suboptimal Hamming-node decoders.

Item URL in elib:https://elib.dlr.de/47267/
Document Type:Article
Title:Low-Floor Tanner Codes via Hamming-Node or RSCC-Node Doping
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Abu-Surra, ShadiUniversity of ArizonaUNSPECIFIED
Liva, GianluigiUNSPECIFIEDUNSPECIFIED
Ryan, William E.University of ArizonaUNSPECIFIED
Date:January 2006
Journal or Publication Title:Lecture Notes in Computer Science
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 245-254
Editors:
EditorsEmail
Springer, UNSPECIFIED
ISBN:3-540-31423-7
Status:Published
Keywords:LDPC codes, Generalised LDPC codes, Turbo codes
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation > Digital Networks
Deposited By: Liva, Dr. Gianluigi
Deposited On:17 Nov 2008
Last Modified:31 Jul 2019 19:19

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