Least squares superposition codes with Bernoulli dictionary are still reliable at rates up to capacity

Yoshinari Takeishi, Masanori Kawakita, Jun'Ichi Takeuchi

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

3 Citations (Scopus)

Abstract

For the additive white Gaussian noise channel with average power constraint, sparse superposition codes with least squares decoding were proposed by Barron and Joseph in 2010. The codewords are designed by using a dictionary which is drawn from a Gaussian distribution. The error probability is shown to be exponentially small in code length for all rates up to the capacity. This paper proves that when the dictionary is drawn from a Bernoulli distribution, the error probability is also exponentially small for all rates up to the capacity.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages1396-1400
Number of pages5
DOIs
Publication statusPublished - Dec 19 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: Jul 7 2013Jul 12 2013

Publication series

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

Other

Other2013 IEEE International Symposium on Information Theory, ISIT 2013
CountryTurkey
CityIstanbul
Period7/7/137/12/13

All Science Journal Classification (ASJC) codes

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

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