Energy-Aware Scheduling for Multi-Hop Cognitive Radio Networks

Cognitive radio (CR) technology, which enables unlicensed secondary users to opportunistically access the unused licensed spectrum, has attracted more and more attention from both academia and industry due to its potential to significantly improve the spectrum utilization. Considering both temporal and spatial variations of spectrum availability, this paper focuses on improving the energy efficiency in CR networks by opportunistically serving the delay-tolerant data only when enough spectrum is available. Based on this idea, a stochastic optimization problem is formulated to integrate the power control, link scheduling, and routing, which minimizes the expected power consumption while guaranteeing the system stability. To obtain the solution, we use the Lyapunov optimization technique and design an online algorithm, which solves a sub-problem without future knowledge of the related stochastic models (e.g., random data arrival and spectrum supply). Besides, in view of the NP-hardness of the sub-problem, we also develop a heuristic algorithm based on branch-and-bound framework to obtain the approximate solution with low computing complexity. Theoretical analysis shows that our algorithm offers an explicit tradeoff between energy consumption and delay performance. Numerical results also confirm the effectiveness of our solutions.