Data mining of modulation types using cyclostationarity-based decision tree

Haifeng Xiao, Chunhua Chen, Wei Su, John Kosinskiand, Yun Q. Shi

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

Abstract

We describe data mining of modulation types of radio frequency signals in civilian and military communications. The cyclostationary pattern and five features derived from the spectrum of the received communication signals are examined to formulate a decision tree in order to identify the modulation format. The developed decision tree structure has been tested with both digital and analog simulation data, and has demonstrated its promising performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 International Conference on Data Mining, DMIN 2008
EditorsR. Stahlbock, S.F. Crone, S. Lessmann
Pages3-9
Number of pages7
StatePublished - 2008
Event2008 International Conference on Data Mining, DMIN 2008 - Las Vegas, NV, United States
Duration: Jul 14 2008Jul 17 2008

Publication series

NameProceedings of the 2008 International Conference on Data Mining, DMIN 2008

Other

Other2008 International Conference on Data Mining, DMIN 2008
Country/TerritoryUnited States
CityLas Vegas, NV
Period7/14/087/17/08

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computational Theory and Mathematics

Keywords

  • Cyclostationarity
  • Data mining
  • Decision tree
  • Modulation classification

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