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'Cognitive radio' has emerged as a new design paradigm for next-generation wireless networks that aims to increase utilization of the scarce radio spectrum (both licensed and unlicensed). Learning and adaptation are two significant features of a cognitive radio transceiver. Intelligent algorithms are used to learn the surrounding environment, and the knowledge thus obtained is utilized by the transceiver to choose the frequency band (i.e., channel) of transmission as well as transmission parameters to achieve the best performance. In this article we first provide an overview of the different components to achieve adaptability in a cognitive radio transceiver and discuss the related approaches. A survey of the cognitive radio techniques used in the different wireless systems is then presented. To this end, a dynamic opportunistic channel selection scheme based on the cognitive radio concept is presented for an IEEE 802.11-based wireless mesh network.