Eigenvalue-based spectrum sensing algorithms for cognitive radio
IEEE Transactions on Communications
Design and analysis for an 802.11-based cognitive radio network
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Sensing-Throughput Tradeoff for Cognitive Radio Networks
IEEE Transactions on Wireless Communications
Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework
IEEE Journal on Selected Areas in Communications
Cognitive Medium Access: Constraining Interference Based on Experimental Models
IEEE Journal on Selected Areas in Communications
Design and analysis for an 802.11-based cognitive radio network
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Cross-layer optimal spectrum sensing duration and scheduling in cognitive networks
CoRoNet '11 Proceedings of the 3rd ACM workshop on Cognitive radio networks
Mobile Networks and Applications
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In cognitive radio networks, the secondary users (SUs) are allowed to use the spectrum originally allocated to primary users (PUs) as long as the PUs are not using it temporarily. This operation is called opportunistic spectrum access (OSA), and it is assisted through spectrum sensing. In distributed OSA, the SUs sense the channel independently; once the channel is available, they contend for channel access on a frame-by-frame basis. In this paper, we study the random medium access control (MAC) in conjunction with the sensing protocol design. In particular, we are interested in the design of frame duration, sensing time and MAC random access to maximize the secondary network throughput performance while protecting the PUs from the interference of secondary users' operations. We formulate the nonlinear constrained optimization problems for the described system model with cross-layered and layered approaches. Simulations show that the cross-layered approach performs much better than layered approach especially when the frame duration is small.