Tytuł:

Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey on Machine Learning-based Methods, Journal of Telecommunications and Information Technology, 2020, nr 3

Autor:

Khamayseh, Sundous ; Halawani, Alaa

Temat i słowa kluczowe:

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

Opis:

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

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Data wydania:

2020, nr 3

Typ zasobu:

artykuł

Format:

application/pdf

Identyfikator zasobu:

ISSN 1509-4553, on-line: ISSN 1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności