Study on reduction on average computational complexity of GMD decoding using property of bounded distance decoding

Shunsuke Ueda, Takuya Kusaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, high reliability is required in digital communications. Research on error correcting codes are actively conducted to achieve high reliable communications. In this study, a method to reduce average computational complexity of Generalized Minimum Distance (GMD) decoding is proposed. GMD decoding can be implemented by several times bounded distance decoding (BDD). The proposed method reduces the average number of BDDs. The effectiveness of reduction on average execution time of the proposed method is confirmed against a simple method by computer simulations.

Original languageEnglish
Title of host publicationProceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages584-588
Number of pages5
Volume2018-January
ISBN (Electronic)9781538620878
DOIs
Publication statusPublished - Apr 23 2018
Event5th International Symposium on Computing and Networking, CANDAR 2017 - Aomori, Japan
Duration: Nov 19 2017Nov 22 2017

Other

Other5th International Symposium on Computing and Networking, CANDAR 2017
CountryJapan
CityAomori
Period11/19/1711/22/17

Keywords

  • average computational complexity
  • bounded distance decoding
  • erasure decoding
  • erasure position
  • GMD decoding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture

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  • Cite this

    Ueda, S., & Kusaka, T. (2018). Study on reduction on average computational complexity of GMD decoding using property of bounded distance decoding. In Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017 (Vol. 2018-January, pp. 584-588). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CANDAR.2017.10