Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Survey of Artificial Intelligence Approaches in Cognitive Radio Networks

  • Morabit, Yasmina EL (Laboratory of Signals, System and Components, Sidi Mohammed Ben Abdellah University) ;
  • Mrabti, Fatiha (Laboratory of Signals, System and Components, Sidi Mohammed Ben Abdellah University) ;
  • Abarkan, El Houssein (Laboratory of Signals, System and Components, Sidi Mohammed Ben Abdellah University)
  • Received : 2018.11.25
  • Accepted : 2019.01.20
  • Published : 2019.03.31
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Abstract

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

Keywords

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Fig. 1. Artificial intelligence approaches for cognitive radio networks.

Table 1. Main application of artificial intelligence techniques to cognitive radio networks

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Table 2. Applications in cognitive radio spectrum sensing based artificial intelligence techniques

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Table 3. Advantages and disadvantages of artificial intelligence techniques used in spectrum sensing issue

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Table 4. Advantages and disadvantages of different evolutionary algorithms used in spectrum management

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Table 5. Applications in cognitive radio spectrum management based artificial intelligence techniques

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Table 6. Advantages and disadvantages of artificial intelligence techniques used in spectrum management issue

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Table 7. Applications in cognitive radio spectrum sharing based artificial intelligence techniques

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Table 8. Advantages and disadvantages of artificial intelligence techniques used in spectrum sharing issue

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Table 9. Applications in cognitive radio spectrum handoff based artificial intelligence techniques

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Table 10. Advantages and disadvantages of artificial intelligence techniques used in spectrum handoff issue

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