Higher-order statistics based modulation classification using hierarchical approach

Afan Ali, Yangyu Fan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Hierarchical based digital modulation classifier is designed using feature-extraction based method with AWGN channel. A characteristic parameter of the received information samples is used to separate between amplitude and angular modulated signals. M-ary ASK signals are separated using instantaneous amplitude of the received samples. Combination of higher-order cumulants up to order eight are computed to classify between M-ary PSK modulated signals. A new feature is proposed in the decision tree of the classifier to separate QPSK and 8PSK modulation. Simulation results are used to verify that this approach is robust under low SNR.

Original languageEnglish
Title of host publicationProceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
EditorsBing Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-374
Number of pages5
ISBN (Electronic)9781467396127
DOIs
StatePublished - 28 Feb 2017
Event2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 - Xi'an, China
Duration: 3 Oct 20165 Oct 2016

Publication series

NameProceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016

Conference

Conference2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Country/TerritoryChina
CityXi'an
Period3/10/165/10/16

Keywords

  • Classification
  • Digital modulation
  • Higher order statistics

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