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Artificial intelligence (AI) and machine learning (ML) as an application of AI, has today become an inevitable part of major industries such as healthcare, financial trending, and transportation. Future urgent need to intelligently utilize wireless resources to meet the need of ever-increasing diversity in services and user behavior, has actuated the wireless communication industry to deploy AI and ML techniques. Intelligent wireless communication aims at maximizing the efficiency of resource allocation by enabling the system to first recognize the available resources, then perceive and learn the wireless environment, and finally reconfigure its operating mode to adapt to the perceived wireless environment. The cognition capability and reconfigurability are the essential features of intelligent radio (also called cognitive radio-CR) in which machine learning techniques mark immense potential in system adaptation.
The concept of CR was first proposed by Joseph Mitola  in order for mitigating the scarcity in limited radio spectrum by improving spectrum allocation efficiency by allowing unlicensed users (cognitive radio users) to identify and transmit over the frequency bands which are already assigned to the licensed users (primary users), but idle over specific time/space (spectrum holes). Spectrum hole identification is usually achieved by sensing the radio frequency (RF) environment through a process called spectrum sensing. It should be noted that the title of CR is not limited only to unlicensed wireless users and implied to any wireless user that adds the cognition capability along with reconfigurability to its system function.
The current applications of machine learning in CR can be listed as follows.
We offer the major application scenarios for cognitive radio networks, wherein machine learning techniques have been widely deployed. It shows the significance of machine learning in realizing the future of intelligent wireless communication.
 J. Mitola and G. Q. Maguire, Jr., "Cognitive radio: making software radios more personal," IEEE Pers. Commun., vol. 6, no. 4, pp. 13–18, Aug. 1999,