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Mobile Information Systems
Volume 2016 (2016), Article ID 6024928, 12 pages
Research Article

Channel Selection Policy in Multi-SU and Multi-PU Cognitive Radio Networks with Energy Harvesting for Internet of Everything

1The College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2The Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China
3The Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada V6T 1Z4

Received 22 September 2016; Accepted 17 November 2016

Academic Editor: Beniamino Di Martino

Copyright © 2016 Feng Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Cognitive radio, which will become a fundamental part of the Internet of Everything (IoE), has been identified as a promising solution for the spectrum scarcity. In a multi-SU and multi-PU cognitive radio network, selecting channels is a fundamental problem due to the channel competition among secondary users (SUs) and packet collision between SUs and primary users (PUs). In this paper, we adopt cooperative sensing method to avoid the packet collision between SUs and PUs and focus on how to collect the spectrum sensing data of SUs for cooperative sensing. In order to reduce the channel competition among SUs, we first consider the hybrid transmission model for single SU where a SU can opportunistically access both idle channels operating either the Overlay or the Underlay model and the busy channels by using the energy harvesting technology. Then we propose a competitive set based channel selection policy for multi-SU where all SUs competing for data transmission or energy harvesting in the same channel will form a competitive set. Extensive simulations show that the proposed cooperative sensing method and the channel selection policy outperform previous solutions in terms of false alarm, average throughput, average waiting time, and energy harvesting efficiency of SUs.