On the Investigation of Wireless Signal Identification Using Spectral Correlation Function and SVMs

Kursat Tekbiyik, Ozkan Akbunar, Ali Riza Ekti, Gunes Karabulut Kurt, Ali Gorcin

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

6 Scopus citations

Abstract

Signal identification is an important notion that leads to significant performance improvements for adaptive wireless spectrum access techniques. Besides identifying the modulation types and other features, standard-based identification has also an important place in signal identification domain. In this paper, a generalized identification method which utilizes the outputs of spectral correlation function as the training inputs for the support vector machines to distinguish wireless signals is introduced. The proposed method eliminates the dependence on the distinct features to identify different signals. The method's performance is tested using the measurements taken in the laboratory environment and various wireless signals are successfully distinguished from each other. The comparative performance of the proposed method is also quantified by the classification confusion matrix.

Original languageEnglish
Title of host publication2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538676462
DOIs
StatePublished - Apr 2019
Externally publishedYes
Event2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 - Marrakesh, Morocco
Duration: Apr 15 2019Apr 19 2019

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2019-April
ISSN (Print)1525-3511

Conference

Conference2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Country/TerritoryMorocco
CityMarrakesh
Period04/15/1904/19/19

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