Learning-Based Optimal Channel Selection in the Presence of Jammer for Cognitive Radio Networks

Aohan Li, Fereidoun H. Panahi, Tomoaki Ohtsuki, Guangjie Han

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

1 Citation (Scopus)

Abstract

Cognitive Radio (CR) technique has been proposed for improving spectrum efficiency by dynamic spectrum access. In Cognitive Radio Networks (CRNs), unlicensed Secondary Users (SUs) with CR can utilize licensed spectrum without interfering licensed Primary Users (PUs). For effectively avoiding interference with licensed PUs and malicious attacks from jammers, a two-stage Learning-based Optimal Channel Selection (LOCS) algorithm for unlicensed SUs in distributed heterogeneous CRNs is proposed in this paper. The LOCS algorithm enables SUs to obtain real states of the licensed channels without knowing their information. Hence, SUs using LOCS algorithm can efficiently avoid collision and attack with PUs and jammers. Besides, the LOCS algorithm considers hardware limitation of the SUs, i.e., SUs can only sense and access parts of the license spectrum during any given time. SUs can select the optimal channels for spectrum sensing and data transmission by using the LOCS algorithm. Simulation results show the efficiency of our proposed algorithm in terms of collision and attack avoidance.

Original languageEnglish
Title of host publication2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647271
DOIs
Publication statusPublished - 2019 Feb 20
Event2018 IEEE Global Communications Conference, GLOBECOM 2018 - Abu Dhabi, United Arab Emirates
Duration: 2018 Dec 92018 Dec 13

Publication series

Name2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings

Conference

Conference2018 IEEE Global Communications Conference, GLOBECOM 2018
CountryUnited Arab Emirates
CityAbu Dhabi
Period18/12/918/12/13

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ASJC Scopus subject areas

  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality
  • Signal Processing
  • Modelling and Simulation
  • Instrumentation
  • Computer Networks and Communications

Cite this

Li, A., Panahi, F. H., Ohtsuki, T., & Han, G. (2019). Learning-Based Optimal Channel Selection in the Presence of Jammer for Cognitive Radio Networks. In 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings [8647307] (2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2018.8647307