Deep Learning Based Identification of Wireless Protocols in the PHY layer

Alex Berian, Irmak Aykin, Marwan Krunz, Tamal Bose

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

Abstract

The need for Artificial Intelligence algorithms for future Cognitive Radio (CR) systems is unavoidable. For a CR to operate as best as possible it must identify who is present in spectrum of interest, and what they are doing (jamming, communicating, rogue transmission, etc.). Using this information, a CR can accordingly decide what to do next. Furthermore, being able to determine which wireless protocols are occupying spectrum is an important ability in heterogeneous wireless networks. In this work, we investigate the robustness of various Neural Network (NN) algorithms for classification of wireless protocols when looking at base-band In-phase/Quadrature (IQ) data without needing to decode. We propose a spectrum sensing algorithm based on NNs or other similarly behaved classification algorithms for identifying wireless technologies occupying spectrum. In previous literature, using base-band IQ data, researchers have shown that NN models can classify different modulation formats with promising accuracy. This work explores the potentials, usage, and limitations of using base-band IQ data for classifying various wireless network protocols that employ the same modulation format.

Original languageEnglish (US)
Title of host publication2020 International Conference on Computing, Networking and Communications, ICNC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages287-293
Number of pages7
ISBN (Electronic)9781728149059
DOIs
StatePublished - Feb 2020
Event2020 International Conference on Computing, Networking and Communications, ICNC 2020 - Big Island, United States
Duration: Feb 17 2020Feb 20 2020

Publication series

Name2020 International Conference on Computing, Networking and Communications, ICNC 2020

Conference

Conference2020 International Conference on Computing, Networking and Communications, ICNC 2020
CountryUnited States
CityBig Island
Period2/17/202/20/20

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Keywords

  • Cognitive Radio
  • Neural Networks
  • Signal Classification
  • Wireless Protocols

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Control and Optimization

Cite this

Berian, A., Aykin, I., Krunz, M., & Bose, T. (2020). Deep Learning Based Identification of Wireless Protocols in the PHY layer. In 2020 International Conference on Computing, Networking and Communications, ICNC 2020 (pp. 287-293). [9049732] (2020 International Conference on Computing, Networking and Communications, ICNC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICNC47757.2020.9049732