An analysis of computational complexity of low level quantizers for block turbo decoding for product codes of binary linear code

Shinichi Kageyama, Ken Ikuta, Yuki Nanjo, Yuta Kodera, Takuya Kusaka, Yasuyuki Nogami

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

Abstract

Block Turbo Decodings (BTDs) with Soft-In SoftOut (SISO) decodings for two-dimensional product codes of linear codes can achieve good error performance. However, since large computational complexity of the BTDs can be a problem, a method which can reduce average computational complexity is needed. In this research, the authors focus on an early termination condition as the method for the reduction on the computational complexity. From the tendency of the output of SISO ordered statistics decoding, a condition is proposed. Based on simulation results for the two-dimensional product code of the (32,26,4) Reed-Muller code, analysis on a parameter of the condition are given. The results show that the computational complexity can be reduced to more than one fourth at the SN ratios higher than 7[dB] of Eb/No without degradation on error performance by choosing an appropriate parameter.

Original languageEnglish
Title of host publicationProceedings - 2019 7th International Symposium on Computing and Networking Workshops, CANDARW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages425-429
Number of pages5
ISBN (Electronic)9781728152684
DOIs
Publication statusPublished - Nov 2019
Event7th International Symposium on Computing and Networking Workshops, CANDARW 2019 - Nagasaki, Japan
Duration: Nov 26 2019Nov 29 2019

Publication series

NameProceedings - 2019 7th International Symposium on Computing and Networking Workshops, CANDARW 2019

Conference

Conference7th International Symposium on Computing and Networking Workshops, CANDARW 2019
CountryJapan
CityNagasaki
Period11/26/1911/29/19

Keywords

  • AWGN
  • Block Turbo Decoding
  • Early Termination Condition
  • Quantization
  • Soft-in Soft-out OSD

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'An analysis of computational complexity of low level quantizers for block turbo decoding for product codes of binary linear code'. Together they form a unique fingerprint.

  • Cite this

    Kageyama, S., Ikuta, K., Nanjo, Y., Kodera, Y., Kusaka, T., & Nogami, Y. (2019). An analysis of computational complexity of low level quantizers for block turbo decoding for product codes of binary linear code. In Proceedings - 2019 7th International Symposium on Computing and Networking Workshops, CANDARW 2019 (pp. 425-429). [8951689] (Proceedings - 2019 7th International Symposium on Computing and Networking Workshops, CANDARW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CANDARW.2019.00080