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The Scientific World Journal
Volume 2014, Article ID 209810, 23 pages
Review Article

Application of Reinforcement Learning in Cognitive Radio Networks: Models and Algorithms

1Faculty of Science and Technology, Sunway University, No. 5 Jalan Universiti, Bandar Sunway, 46150 Petaling Jaya, Selangor, Malaysia
2University Malaysia of Computer Science & Engineering, Jalan Alamanda 2, Presint 16, 62150 Putrajaya, Wilayah Persekutuan Putrajaya, Malaysia
3Department of Mathematical Modeling Laboratory, Mimos Berhad, Technology Park Malaysia, 57000 Kuala Lumpur, Malaysia

Received 11 April 2014; Accepted 25 April 2014; Published 5 June 2014

Academic Editor: T. O. Ting

Copyright © 2014 Kok-Lim Alvin Yau et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [4 citations]

The following is the list of published articles that have cited the current article.

  • Sharada Tubachi, Mithra Venkatesan, and A. V. Kulkarni, “Predictive learning model in cognitive radio using reinforcement learning,” 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), pp. 564–567, . View at Publisher · View at Google Scholar
  • Mee Hong Ling, Kok-Lim Alvin Yau, Junaid Qadir, Geong Sen Poh, and Qiang Ni, “Application of Reinforcement Learning for Security Enhancement in Cognitive Radio Networks,” Applied Soft Computing, 2015. View at Publisher · View at Google Scholar
  • P. Subbulakshmi, and M. Prakash, “Mitigating eavesdropping by using fuzzy based MDPOP-Q learning approach and multilevel Stackelberg game theoretic approach in wireless CRN,” Cognitive Systems Research, vol. 52, pp. 853–861, 2018. View at Publisher · View at Google Scholar
  • Aouatef El Biari, Badr Benmammar, Amine Hamdouchi, and Youness Tabii, “Towards the use of cognitive radio to solve cellular network challenges,” Advances in Intelligent Systems and Computing, vol. 725, pp. 3–10, 2018. View at Publisher · View at Google Scholar