Higher-order statistics based modulation classification using hierarchical approach

Afan Ali; Yangyu Fan

doi:10.1109/IMCEC.2016.7867236

Higher-order statistics based modulation classification using hierarchical approach

Afan Ali
, Yangyu Fan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 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 language	English
Title of host publication	Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Editors	Bing Xu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	370-374
Number of pages	5
ISBN (Electronic)	9781467396127
DOIs	https://doi.org/10.1109/IMCEC.2016.7867236
State	Published - 28 Feb 2017
Externally published	Yes
Event	2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 - Xi'an, China Duration: 3 Oct 2016 → 5 Oct 2016

Publication series

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

Conference

Conference	2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Country/Territory	China
City	Xi'an
Period	3/10/16 → 5/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Classification
Digital modulation
Higher order statistics

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Information Systems and Management
Control and Systems Engineering

Access to Document

10.1109/IMCEC.2016.7867236

Cite this

Ali, A., & Fan, Y. (2017). Higher-order statistics based modulation classification using hierarchical approach. In B. Xu (Ed.), Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 (pp. 370-374). Article 7867236 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMCEC.2016.7867236

Ali, Afan ; Fan, Yangyu. / Higher-order statistics based modulation classification using hierarchical approach. Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. editor / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 370-374 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016).

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title = "Higher-order statistics based modulation classification using hierarchical approach",

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.",

keywords = "Classification, Digital modulation, Higher order statistics",

author = "Afan Ali and Yangyu Fan",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 ; Conference date: 03-10-2016 Through 05-10-2016",

year = "2017",

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doi = "10.1109/IMCEC.2016.7867236",

language = "English",

series = "Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Ali, A & Fan, Y 2017, Higher-order statistics based modulation classification using hierarchical approach. in B Xu (ed.), Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016., 7867236, Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016, Institute of Electrical and Electronics Engineers Inc., pp. 370-374, 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016, Xi'an, China, 3/10/16. https://doi.org/10.1109/IMCEC.2016.7867236

Higher-order statistics based modulation classification using hierarchical approach. / Ali, Afan; Fan, Yangyu.
Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. ed. / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2017. p. 370-374 7867236 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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KW - Higher order statistics

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PB - Institute of Electrical and Electronics Engineers Inc.

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Ali A, Fan Y. Higher-order statistics based modulation classification using hierarchical approach. In Xu B, editor, Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 370-374. 7867236. (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016). doi: 10.1109/IMCEC.2016.7867236

Higher-order statistics based modulation classification using hierarchical approach

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this