Sparse symbol detection by a greedy tree search

Jaeseok Lee, Byonghyo Shim

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

1 Citation (Scopus)

Abstract

In this paper, we consider a detection problem of the underdetermined system when the input vector is sparse and its elements are chosen from a set of finite alphabets. We propose a greedy sparse recovery algorithm dubbed as the sparse detection matching pursuit (SDMP) that is effective in recovering the sparse signals with integer constraint. In our performance guarantee analysis and empirical simulations, we show that SDMP is effective in recovering sparse signals in both noiseless and noisy scenarios.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3024-3027
Number of pages4
Volume2015-August
ISBN (Print)9781467369978
DOIs
Publication statusPublished - 2015 Aug 4
Externally publishedYes
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: 2014 Apr 192014 Apr 24

Other

Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
CountryAustralia
CityBrisbane
Period14/4/1914/4/24

Keywords

  • compressed sensing
  • greedy algorithm
  • Sparse detection
  • tree search
  • underdetermined system

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Lee, J., & Shim, B. (2015). Sparse symbol detection by a greedy tree search. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 2015-August, pp. 3024-3027). [7178526] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2015.7178526