Maximum Likelihood Channel Decoding with Quantum Annealing Machine

Naoki Ide, Tetsuya Asayama, Hiroshi Ueno, Masayuki Ohzeki

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

Abstract

We formulate maximum likelihood (ML) channel decoding as a quadratic unconstraint binary optimization (QUBO) and simulate the decoding by the current commercial quantum annealing machine, D-Wave 2000Q. We prepared two implementations with Ising model formulations, generated from the generator matrix and the parity-check matrix respectively. We evaluated these implementations of ML decoding for low-density parity-check (LDPC) codes, analyzing the number of spins and connections and comparing the decoding performance with belief propagation (BP) decoding and brute-force ML decoding with classical computers. The results show that these implementations are superior to BP decoding in relatively short length codes, and while the performance in the long length codes deteriorates, theimplementation from the parity-check matrix formulation still works up to 1k length with fewer spins and connections than that of the generator matrix formulation due to the sparseness of parity-check matrices of LDPC.

Original languageEnglish
Title of host publicationProceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages91-95
Number of pages5
ISBN (Electronic)9784885523304
Publication statusPublished - 2020 Oct 24
Externally publishedYes
Event16th International Symposium on Information Theory and its Applications, ISITA 2020 - Virtual, Kapolei, United States
Duration: 2020 Oct 242020 Oct 27

Publication series

NameProceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020

Conference

Conference16th International Symposium on Information Theory and its Applications, ISITA 2020
CountryUnited States
CityVirtual, Kapolei
Period20/10/2420/10/27

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Software
  • Theoretical Computer Science

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