Low Complexity Uplink Schedulers for Energy-Efficient Cognitive Radio Networks

We formulate and solve energy-efficient uplink scheduling problem, and propose two low-complexity schedulers for a cognitive radio (CR) network with a white space database access. The proposed schedulers - one applying power adaptation- evaluate each frequency and CR pair considering spectrum switching, transmission, and idling times. As CRs are expected to operate in a wide spectrum, channel switching has to be considered in CRNs since it increases energy consumption and leaves less time for transmission. Simulations demonstrate that our proposals attain significantly higher energy efficiency without sacrificing throughput under sufficient spectrum resources while achieving similar performance for low spectrum resources.