A survey of machine learning algorithms and their applications in cognitive radio

Mustafa Alshawaqfeh, Xu Wang, Ali Riza Ekti, Erchin Serpedin, Muhammad Zeeshan Shakir, Khalid Qaraqe

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

3 Citations (Scopus)

Abstract

Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.
Original languageEnglish
Title of host publicationCognitive Radio Oriented Wireless Networks
Subtitle of host publication10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers
EditorsMark Weichold, Mounir Hamdi, Muhammad Zeeshan Shakir, Mohamed Abdallah, George K. Karagiannidis
PublisherSpringer Nature
Pages790-801
Number of pages12
Volume156
ISBN (Electronic)9783319245409
ISBN (Print)9783319245393
DOIs
Publication statusPublished - 23 Apr 2015
Externally publishedYes
Event10th International Conference on Cognitive Radio Oriented Wireless Networks - Hilton Hotel, Doha, Qatar
Duration: 21 Apr 201523 Apr 2015
http://crowncom.org/2015/show/home

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
PublisherSpringer
Volume156
ISSN (Print)1867-8211

Conference

Conference10th International Conference on Cognitive Radio Oriented Wireless Networks
Abbreviated titleCrownCom'2015
CountryQatar
CityDoha
Period21/04/1523/04/15
Internet address

Keywords

  • cognitive radio
  • machine learning
  • learning engine
  • spectrum sensing
  • modulation classification

Fingerprint Dive into the research topics of 'A survey of machine learning algorithms and their applications in cognitive radio'. Together they form a unique fingerprint.

  • Cite this

    Alshawaqfeh, M., Wang, X., Ekti, A. R., Serpedin, E., Shakir, M. Z., & Qaraqe, K. (2015). A survey of machine learning algorithms and their applications in cognitive radio. In M. Weichold, M. Hamdi, M. Z. Shakir, M. Abdallah, & G. K. Karagiannidis (Eds.), Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers (Vol. 156, pp. 790-801). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 156). Springer Nature. https://doi.org/10.1007/978-3-319-24540-9_66