Title: Possible adoption of various machine learning techniques in cognitive radio - a survey

Authors: Barnali Dey; Ashraf Hossain; Rabindranath Bera

Addresses: Department of Electronics and Communication Engineering, National Institute of Technology Silchar, India ' Department of Electronics and Communication Engineering, National Institute of Technology Silchar, India ' Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India

Abstract: The concept of cognitive radio (CR) system is the need for next generation wireless communication technology in terms of providing intelligence and superior performance to a wireless device. The CR is mainly an intelligent system which is aware of its environment and is well capable to adapt in accordance with the changing environment and user needs. The concept of adaptation of the communication system can be realised well with machine learning capability inculcated within the system. It is a well-known fact that, the key strengths of any machine learning paradigm is its ability to adapt with respect to the dynamic changing system parameters. In this paper, an attempt has been made to compile various applications of machine learning techniques for different activities of CR cycle. Further, this note reviews the work on development of machine learning techniques for spectrum sensing of CR in order to make the CR system as a whole practically feasible and robust, thus mitigating its existing computational limitations due to the use of conventional techniques.

Keywords: cognitive radio; machine learning; spectrum sensing; energy detection.

DOI: 10.1504/IJAIP.2021.113782

International Journal of Advanced Intelligence Paradigms, 2021 Vol.18 No.4, pp.439 - 463

Received: 27 Oct 2016
Accepted: 06 Jan 2017
Published online: 31 Mar 2021 *

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