Automatic modulation classification using hierarchical polynomial classifier and stepwise regression

Ameen Abdelmutalab; Khaled Assaleh; Mohamed El-Tarhuni

doi:10.1109/WCNC.2016.7565127

Automatic modulation classification using hierarchical polynomial classifier and stepwise regression

Ameen Abdelmutalab
, Khaled Assaleh
, Mohamed El-Tarhuni

American University of Sharjah

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

16 Scopus citations

Abstract

This paper presents a simplified automatic modulation classification system based on stepwise regression and Hierarchical Polynomial Classifier. The proposed system applies High Order Cumulants of the received signal to a polynomial network in order to calculate their second order polynomial expansion. Then, stepwise regression model is used as a feature selection system; whereas important features are identified and used for the classification problem and the insignificant features are discarded. With this optimization step, the complexity of the classifier is reduced significantly while maintaining the same classification accuracy as the original Hierarchical Polynomial Classifier with all the expanded features.

Original language	English
Title of host publication	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467398145
DOIs	https://doi.org/10.1109/WCNC.2016.7565127
State	Published - 2016
Externally published	Yes
Event	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 - Doha, Qatar Duration: 3 Apr 2016 → 7 Apr 2016

Publication series

Name	IEEE Wireless Communications and Networking Conference, WCNC
Volume	0
ISSN (Electronic)	1558-2612

Conference

Conference	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Country/Territory	Qatar
City	Doha
Period	3/04/16 → 7/04/16

Keywords

Automatic Modulation Classification (AMC)
Hierarchical Polynomial Classifiers (HPC)
High Order Cumulants (HOCs) and Stepwise Regression

Access to Document

10.1109/WCNC.2016.7565127

Cite this

Abdelmutalab, A., Assaleh, K., & El-Tarhuni, M. (2016). Automatic modulation classification using hierarchical polynomial classifier and stepwise regression. In 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 Article 7565127 (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCNC.2016.7565127

@inproceedings{ca94d9cea8e64a3fa0063fcc7d2e6568,

title = "Automatic modulation classification using hierarchical polynomial classifier and stepwise regression",

abstract = "This paper presents a simplified automatic modulation classification system based on stepwise regression and Hierarchical Polynomial Classifier. The proposed system applies High Order Cumulants of the received signal to a polynomial network in order to calculate their second order polynomial expansion. Then, stepwise regression model is used as a feature selection system; whereas important features are identified and used for the classification problem and the insignificant features are discarded. With this optimization step, the complexity of the classifier is reduced significantly while maintaining the same classification accuracy as the original Hierarchical Polynomial Classifier with all the expanded features.",

keywords = "Automatic Modulation Classification (AMC), Hierarchical Polynomial Classifiers (HPC), High Order Cumulants (HOCs) and Stepwise Regression",

author = "Ameen Abdelmutalab and Khaled Assaleh and Mohamed El-Tarhuni",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 ; Conference date: 03-04-2016 Through 07-04-2016",

year = "2016",

doi = "10.1109/WCNC.2016.7565127",

language = "English",

series = "IEEE Wireless Communications and Networking Conference, WCNC",

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

booktitle = "2016 IEEE Wireless Communications and Networking Conference, WCNC 2016",

address = "United States",

}

Abdelmutalab, A, Assaleh, K & El-Tarhuni, M 2016, Automatic modulation classification using hierarchical polynomial classifier and stepwise regression. in 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016., 7565127, IEEE Wireless Communications and Networking Conference, WCNC, vol. 0, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016, Doha, Qatar, 3/04/16. https://doi.org/10.1109/WCNC.2016.7565127

Automatic modulation classification using hierarchical polynomial classifier and stepwise regression. / Abdelmutalab, Ameen; Assaleh, Khaled; El-Tarhuni, Mohamed.
2016 IEEE Wireless Communications and Networking Conference, WCNC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7565127 (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 0).

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

TY - GEN

T1 - Automatic modulation classification using hierarchical polynomial classifier and stepwise regression

AU - Abdelmutalab, Ameen

AU - Assaleh, Khaled

AU - El-Tarhuni, Mohamed

PY - 2016

Y1 - 2016

N2 - This paper presents a simplified automatic modulation classification system based on stepwise regression and Hierarchical Polynomial Classifier. The proposed system applies High Order Cumulants of the received signal to a polynomial network in order to calculate their second order polynomial expansion. Then, stepwise regression model is used as a feature selection system; whereas important features are identified and used for the classification problem and the insignificant features are discarded. With this optimization step, the complexity of the classifier is reduced significantly while maintaining the same classification accuracy as the original Hierarchical Polynomial Classifier with all the expanded features.

AB - This paper presents a simplified automatic modulation classification system based on stepwise regression and Hierarchical Polynomial Classifier. The proposed system applies High Order Cumulants of the received signal to a polynomial network in order to calculate their second order polynomial expansion. Then, stepwise regression model is used as a feature selection system; whereas important features are identified and used for the classification problem and the insignificant features are discarded. With this optimization step, the complexity of the classifier is reduced significantly while maintaining the same classification accuracy as the original Hierarchical Polynomial Classifier with all the expanded features.

KW - Automatic Modulation Classification (AMC)

KW - Hierarchical Polynomial Classifiers (HPC)

KW - High Order Cumulants (HOCs) and Stepwise Regression

UR - https://www.scopus.com/pages/publications/84989957479

U2 - 10.1109/WCNC.2016.7565127

DO - 10.1109/WCNC.2016.7565127

M3 - Conference contribution

AN - SCOPUS:84989957479

T3 - IEEE Wireless Communications and Networking Conference, WCNC

BT - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016

Y2 - 3 April 2016 through 7 April 2016

ER -

Abdelmutalab A, Assaleh K, El-Tarhuni M. Automatic modulation classification using hierarchical polynomial classifier and stepwise regression. In 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7565127. (IEEE Wireless Communications and Networking Conference, WCNC). doi: 10.1109/WCNC.2016.7565127

Automatic modulation classification using hierarchical polynomial classifier and stepwise regression

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