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Spectrum sensing is an essential functionality of cognitive radio networks. In this paper, a non-cooperative game framework is proposed for studying the interactions between multiple secondary strategic users in spectrum sensing. The licensed spectrum of single primary user is divided into K sub-bands, each secondary user operates exclusively in one sub-band. In each time interval, secondary users are optimally selected to perform cooperative sensing. The authors model this scenario as a non-cooperative game and analyze it by exploring the properties of Nash equilibrium point. They further develop a distributed learning algorithm so that the secondary users approach the NE solely based on their own payoff observations.
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