Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey on Machine Learning-based Methods

• Autorzy: Khamayseh Sundous , Halawani Alaa

Identyfikatory

DOI

10.26636/jtit.2020.137219

• Języki publikacji: EN

Abstrakty

EN

The continuous growth of demand experienced by wireless networks creates a spectrum availability challenge. Cognitive radio (CR) is a promising solution capable of overcoming spectrum scarcity. It is an intelligent radio technology that may be programmed and dynamically configured to avoid interference and congestion in cognitive radio networks (CRN). Spectrum sensing (SS) is a cognitive radio life cycle task aiming to detect spectrum holes. A number of innovative approaches are devised to monitor the spectrum and to determine when these holes are present. The purpose of this survey is to investigate some of these schemes which are constructed based on machine learning concepts and principles. In addition, this review aims to present a general classification of these machine learningbased schemes.

Słowa kluczowe

EN

cognitive radio; cooperative spectrum sensing; IEEE 802.22; machine learning; spectrum sensing

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2020
• Tom: nr 3
• Strony: 36--46
• Opis fizyczny: Bibliogr. 29 poz., rys., tab.

Twórcy

autor

Khamayseh Sundous

• College of Information Technology and Computer Engineering, Palestine Polytechnic University
• Intelligent Systems Research Center, Palestine Polytechnic University

autor

Halawani Alaa

• College of Information Technology and Computer Engineering, Palestine Polytechnic University

Bibliografia

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