Optimal sensing order in cognitive radio networks with channel stability and traffic differentiation

Cognitive radio networks (CRNs) benefit from several features, such as decision-making, spectrum-awareness and reconfigurability, which enable them to perform spectrum migration in order to recover the link when the operating channel becomes occupied. The time spent for channel migration and recovery is a function of the order in which the channels are selected to be sensed. For optimal sensing order, the parameters which have mostly been considered in the literature are the availability and the quality of the channels. Another important parameter is the channel stability, which is the duration that a channel remains continuously available. We extend in this paper a single-slot model to propose novel decision making dynamic programming (DP) models where availability, quality and stability of the channels are taken into account. Considering the need for differentiation in cognitive radio network, we also propose a differentiated dynamic programming model considering different classes of traffic where the sensing order is determined based on an aggregated cost function. Simulation results show the superiority of decision-making based on DP models compared to other common schemes such as myopic, random or average-based.