Information-propagation-based scheduling for the fast convergence of shuffled decoding

Taehyun Kim, Jun Heo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This letter presents a scheduling scheme for the fast convergence of shuffled decoding. The messages from the variable node group that is expected to propagate the most reliable information are updated first. Mutual information is used to measure the information reliability. Simulation results show that the average number of iterations is reduced by adopting the proposed schedule, compared with previous scheduling schemes. In addition, information-theoretic analysis results show that mutual information in the proposed scheme increases faster than in the previous scheme.

Original languageEnglish
Pages (from-to)1314-1317
Number of pages4
JournalIEEE Communications Letters
Volume22
Issue number7
DOIs
Publication statusPublished - 2018 Jul

Bibliographical note

Funding Information:
Manuscript received March 8, 2018; accepted April 7, 2018. Date of publication April 24, 2018; date of current version July 10, 2018. This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2018-2015-0-00385) supervised by the IITP(Institute for Information & communications Technology Promotion) and the ICT R&D program of MSIP/IITP [1711057505, Reliable crypto-system standards and core technology development for secure quantum key distribution network]. The associate editor coordinating the review of this paper and approving it for publication was Z. Ma. (Corresponding author: Jun Heo.) The authors are with the School of Electrical Engineering, Korea University, Seoul 02841, South Korea (e-mail: samecorey@korea.ac.kr; junheo@korea.ac.kr). Digital Object Identifier 10.1109/LCOMM.2018.2829739

Publisher Copyright:
© 1997-2012 IEEE.

Keywords

  • Low-density parity-check codes
  • mutual information
  • scheduling
  • shuffled decoding

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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