Scheduling in centralized cognitive radio networks for energy efficiency

Abstract—With growing concern on environmental issues and emerging green communications paradigm, cognitive radio (CR) networks have to be considered from energy efficiency perspec-tive. In this work, we focus on scheduling in CR networks (CRNs) in which cognitive base station (CBS) makes frequency allocations to the CRs at the beginning of each frame. A cognitive scheduler must consider the diversity among CRs ’ queues and channel capacities in terms of number of bits as well as the channel switching cost from one frequency to another. Taking all these into account, we formulate the scheduling problem as energy efficiency maximization problem which is a nonlinear integer programming (NLP) problem and thereby hard to solve. We seek for alternate computationally easier solutions. To this aim, we propose a polynomial time heuristic algorithm, energy-efficient heuristic scheduler, which allocates each idle frequency to the CR that attains the highest energy efficiency at this frequency. Next, we reformulate the original problem first as throughput maximization problem subject to energy consumption restrictions and next, as energy consumption minimization problem subject to minimum throughput guarantees. These two schedulers have also the power to provide fairness in resource allocation. We analyze the energy efficiency and successful transmission prob-ability of the proposed schedulers under both contiguous and fragmented spectrum scenarios. Performance studies show that compared to a pure opportunistic scheduler with a throughput maximization objective, proposed schedulers can attain almost the same throughput performance with better energy efficiency. Index Terms—Cognitive radio (CR), energy efficiency, channel switching, fragmented spectrum. I