Detection of spectrum hole from n ‐number of primary users using machine learning algorithms-Reference-Cited by-同舟云学术

Detection of spectrum hole from n ‐number of primary users using machine learning algorithms

Published:2020-05 Issue:5 Volume:2020 Page:175-188
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Venkateshkumar Udayamoorthy¹,Ramakrishnan Srinivansan²

Affiliation:

1. Department of ECESri Krishna College of TechnologyCoimbatore 641042TNIndia

2. Department of ITDr. Mahalingam College of Engineering and TechnologyPollachi 642003TNIndia

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0024

Reference18 articles.

1. TRAI.: ‘Telecommunication in select countries polices‐statistics’ TRAI November 2018 pp.5–23

2. MarcusM. BurtleJ. FrancaB.et al.: ‘Report of the unlicensed devices and experimental licenses working group’ Federal Communications Commission Spectrum Policy Task Force November 2002 pp.1–24

3. MitolaJ.: ‘Cognitive radio for flexible mobile multimedia communications’.IEEE Int. Workshop on Mobile Multimedia Communications (MoMuC'99) 1999 pp.3–10

4. Cognitive radio: brain-empowered wireless communications

5. Cooperative spectrum sensing in cognitive radio networks: A survey

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