Abstract: In our work, we focus on energy efficiency of centralized frequency allocation in a Cognitive Radio Network (CRN)- a network that can opportunistically access unused spectrum bands. We formulate the scheduling problem as energy efficiency maximization problem, which is a nonlinear integer-programming (NLP) problem, and propose various polynomial time heuristic algorithms. All our schedulers are queue-aware, channel-quality-aware, and different from the literature channel-switching-aware. 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 probability 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.
Bio: Suzan Bayhan received her B.Sc., M.Sc., and Ph.D. degrees in computer engineering from Bogaziçi University, Istanbul, Turkey in 2003, 2006, and 2012, respectively. In August 2012, she joined Helsinki Institute for Information Technology (HIIT) as a post-doctoral researcher. Her current research interests include cognitive radio networks, small cells, green communications and analytical modeling of communication networks.
Host: Sohan Seth
Last updated on 22 Oct 2012 by Sohan Seth - Page created on 22 Oct 2012 by Sohan Seth