Near maximum-likelihood decoding of Generalized LDPC and Woven graph codes

Irina Bocharova, Boris Kudryashov, Nikolay Makarov, Rolf Johannesson

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


Relations between Generalized LDPC codes, nonbinary LDPC codes, and woven graph codes are considered. Focus is on rather short codes suitable, for example, for coding control signaling information in mobile communications. In particular, codes of lengths less than 200 bits are studied. Low-complexity near maximum-likelihood (ML) decoding for these classes of codes is introduced and analyzed. Frame error rate (FER) performance of the new decoding procedure is compared with the same performance of ML and belief propagation (BP) decoding. It is shown that unlike BP decoding whose performances are mainly governed by the girth of the Tanner graph the new decoding procedure has performances which significantly depend on the minimum distance and spectrum of the woven code. Short woven graph codes with large minimum distances are tabulated.
Original languageEnglish
Title of host publicationIEEE International Symposium on Information Theory (ISIT)
Number of pages5
Publication statusPublished - 2013
EventIEEE International Symposium on Information Theory, 2013 - Istanbul, Turkey
Duration: 2013 Jul 72013 Jul 12

Publication series

ISSN (Print)2157-8095
ISSN (Electronic)2157-8117


ConferenceIEEE International Symposium on Information Theory, 2013
Abbreviated titleISIT13

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering


Dive into the research topics of 'Near maximum-likelihood decoding of Generalized LDPC and Woven graph codes'. Together they form a unique fingerprint.

Cite this