An advanced low-complexity decoding algorithm for turbo product codes based on the syndrome

Sungsik Yoon, Byungkyu Ahn, Jun Heo

Research output: Contribution to journalReview articlepeer-review

Abstract

This paper introduces two effective techniques to reduce the decoding complexity of turbo product codes (TPC) that use extended Hamming codes as component codes. We first propose an advanced hard-input soft-output (HISO) decoding algorithm, which is applicable if an estimated syndrome stands for double-error. In conventional soft-input soft-output (SISO) decoding algorithms, 2p (p: the number of least reliable bits) number of hard decision decoding (HDD) operations are performed to correct errors. However, only a single HDD is required in the proposed algorithm. Therefore, it is able to lower the decoding complexity. In addition, we propose an early termination technique for undecodable blocks. The proposed early termination is based on the difference in the ratios of double-error syndrome detection between two consecutive half-iterations. Through this early termination, the average iteration number is effectively lowered, which also leads to reducing the overall decoding complexity. Simulation results show that the computational complexity of TPC decoding is significantly reduced via the proposed techniques, and the error correction performance remains nearly the same in comparison with that of conventional methods.

Original languageEnglish
Article number126
JournalEurasip Journal on Wireless Communications and Networking
Volume2020
Issue number1
DOIs
Publication statusPublished - 2020 Dec 1

Keywords

  • Early termination
  • Hard-input soft-output decoding
  • Soft-input soft-output decoding
  • Syndrome-based decoding
  • Turbo product codes

ASJC Scopus subject areas

  • Signal Processing
  • Computer Science Applications
  • Computer Networks and Communications

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