Dynamic Channel Aggregation Strategies in Cognitive Radio Networks with Spectrum Adaptation

In cognitive radio networks, channel aggregation techniques which combine several channels together as one channel have been proposed in many MAC protocols. In this paper, spectrum adaptation is proposed in channel aggregation and two strategies which dynamically adjust channel occupancy of ongoing traffic flows are further developed. The performance of these strategies is evaluated using continuous time Markov chain models. Moreover, models in the quasi-stationary regime are analyzed and the closed-form capacity expression is derived in this regime. Numerical results demonstrate that the capacity of the secondary network can be improved by using channel aggregation with spectrum adaptation.