Scalability of cognitive radio control algorithms

Cognitive radios with their intelligent mechanisms of avoiding interference and their ability to automatically discover and utilize unoccupied spectrum have frequently been proposed for pervasive wireless deployments. In recent years, a variety of control algorithms managing such cognitive radios have been developed, following many different types of strategies and implementing the whole range from centralized control to distributed control principles. As future wireless deployments are expected to be very dense, the ability of a cognitive radio control algorithm to scale well to large network sizes becomes crucial. In this paper, we review and discuss a wide variety of previously proposed algorithms for managing cognitive radio networks. For each of these algorithms, we theoretically analyze performance in pervasive, dense deployments and compare their ability to scale.