Opportunistic Scheduling and Channel Allocation in MC-MR Cognitive Radio Networks

In this paper, we use the Lyapunov optimization technique to develop scheduling policies for multiradio multichannel cognitive networks to optimize jointly the throughput and the average delay of a secondary network, with limited interference to primary users (PUs)' transmission. In particular, we consider three scenarios, including a static single-hop secondary network, a static multihop secondary network, and a mobile secondary network. For these cases, with the consideration of general mobility and interference models, we design efficient scheduling and channel allocation algorithms based on the concept of Lyapunov drift and give the corresponding performance bound. Furthermore, our theoretical analysis demonstrates that the proposed algorithms can achieve a flexible tradeoff between network throughput and average backlogs by using the Lyapunov optimization technique. Finally, the efficiency of the proposed algorithms is verified by the numerical simulations.