In this paper, a Cognitive Radio Network (CRN) based on artificialintelligence is proposed to distribute the limited radio spectrum resourcesmore efficiently. The CRN framework can analyze the time-sensitive signal dataclose to the signal source using fog computing with different types of machinelearning techniques. Depending on the computational capabilities of the fognodes, different features and machine learning techniques are chosen tooptimize spectrum allocation. Also, the computing nodes send the periodicsignal summary which is much smaller than the original signal to the cloud sothat the overall system spectrum source allocation strategies are dynamicallyupdated. Applying fog computing, the system is more adaptive to the localenvironment and robust to spectrum changes. As most of the signal data isprocessed at the fog level, it further strengthens the system security byreducing the communication burden of the communications network.
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