Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing
Modeling and analysis for proactive-decision spectrum handoff in cognitive radio networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Sensing-Throughput Tradeoff for Cognitive Radio Networks
IEEE Transactions on Wireless Communications
IEEE Transactions on Multimedia
A survey on spectrum management in cognitive radio networks
IEEE Communications Magazine
Load-Balancing Spectrum Decision for Cognitive Radio Networks
IEEE Journal on Selected Areas in Communications
A fair spectrum sharing approach in Cognitive Radio Networks
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
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In this paper, we discuss the spectrum management technologies including spectrum sensing, spectrum decision, spectrum sharing, and spectrum handoff schemes in cognitive radio (CR) networks. In order to evaluate performance of different spectrum management schemes, the preemptive resume priority (PRP) M/G/1 queuing model is suggested to characterize the spectrum usage behavior between the primary and the secondary users. Based on this model, we derive a new performance measure - the overall system time of the secondary connections. The overall system time is an important performance measure to provide the quality of service (QoS) provisioning service for the secondary users. It is defined as the duration from the instant that data arrives at system until the instant of finishing the whole transmission. Clearly, multiple interruptions from the high-priority primary users will increase the overall system time of the low-priority secondary users. Based on the PRP M/G/1 queuing model, the impacts of multiple interruptions on the overall system time can be evaluated. On top of this model, a spectrum sensing, a spectrum decision, a spectrum sharing, and a spectrum handoff algorithms are investigated to reduce the overall system time. From the numerical results, we can design better spectrum management policies to satisfy the QoS requirement of the secondary users in CR networks and provide useful insight into the design tradeoff for different spectrum management technologies.