An improved upper bound on block error probability of least squares superposition codes with unbiased Bernoulli dictionary

Yoshinari Takeishi, Jun'Ichi Takeuchi

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

1 Citation (Scopus)

Abstract

For the additive white Gaussian noise channel with average power constraint, it is shown that sparse superposition codes, proposed by Barron and Joseph in 2010, achieve the capacity. We study the upper bounds on its block error probability with least squares decoding when a dictionary with which we make codewords is drawn from an unbiased Bernoulli distribution. We improve the upper bounds shown by Takeishi et.al. in 2014 with fairly simplified form.

Original languageEnglish
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1168-1172
Number of pages5
ISBN (Electronic)9781509018062
DOIs
Publication statusPublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2016-August
ISSN (Print)2157-8095

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
CountrySpain
CityBarcelona
Period7/10/167/15/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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    Takeishi, Y., & Takeuchi, JI. (2016). An improved upper bound on block error probability of least squares superposition codes with unbiased Bernoulli dictionary. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory (pp. 1168-1172). [7541483] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2016-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541483