Dynamic Selection of Priority Queueing Discipline in Cognitive Radio Networks

In this paper, for the purpose of service differentiation in opportunistic spectrum access (OSA) enabled networks, we take different priority queueing disciplines into account as decision variables in a dynamic optimization model. The objective is to optimize, after the departure of each packet, a weighted utility function of the performance of different classes of cognitive radio traffic by dynamically deciding the priority queueing discipline. A dynamic programming (DP) model, which takes into account the channel availability and channel handover recovery periods of the OSA network, is provided for two classes of traffic to solve this problem. Simulation results are presented.