Energy-efficient scheduling and power control via stochastic network optimisation in cognitive radio networks

In this work, the authors consider a joint scheduling and power control problem via stochastic network optimisation in interweave cognitive radio networks subject to an energy-efficiency (EE) constraint, scheduling constraints, and power constraints, which is solved by traffic admission control, channel allocation, and power allocation. The authors' objective is to maximise the total utility of secondary user equipment, while satisfying the minimum throughput requirement of primal user equipment, the EE requirement, and the performance requirement. In particular, their optimisation on the stochastic system is obtained by using the Lyapunov drift-plus-penalty framework to deal with the time-varying channels and traffics so that the long-term stability on the data queues and virtual queues involved can be guaranteed. Given that, the scheduling algorithm is conducted with polynomial time efficiency, and despite the system to dynamically vary its power, the power control algorithms as well as the admission control proposed are simply threshold-based and thus very computationally efficient. Finally, in addition to the theoretical analysis, their simulation studies further confirm the performance trade-off between throughput and delay as [O(1/V),O(V)] with a system parameter V , and also show the trade-off between throughput and EE, while satisfying all the requirements concerned.