End-to-end routing behavior in the Internet
IEEE/ACM Transactions on Networking (TON)
Simulation
Wireless Communications
NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Mining spectrum usage data: a large-scale spectrum measurement study
Proceedings of the 15th annual international conference on Mobile computing and networking
ACM SIGMOBILE Mobile Computing and Communications Review
A two-stage sensing technique for dynamic spectrum access
IEEE Transactions on Wireless Communications
Opportunistic energy-efficient contact probing in delay-tolerant applications
IEEE/ACM Transactions on Networking (TON)
Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Optimal channel probing and transmission scheduling for opportunistic spectrum access
IEEE/ACM Transactions on Networking (TON)
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
A Comparison of Poisson and Uniform Sampling for Active Measurements
IEEE Journal on Selected Areas in Communications
Defense against Primary User Emulation Attacks in Cognitive Radio Networks
IEEE Journal on Selected Areas in Communications
Simple Channel Sensing Order in Cognitive Radio Networks
IEEE Journal on Selected Areas in Communications
Channel Estimation for Opportunistic Spectrum Access: Uniform and Random Sensing
IEEE Transactions on Mobile Computing
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In cognitive radio networks, secondary users must constantly probe the spectrum to promptly detect the arrival and the departure of primary users (PUs). However, spectrum probing is an energy-consuming process. This indicates the tradeoff between the frequency of spectrum probing and the delay of detecting the PU state change, and highlights the need for energy-conscious spectrum-probing strategies. In this paper, we provide a theoretical framework to find the optimal spectrum-probing methods that minimize the probing delay under a constraint on energy consumption in real stochastic environments. Moreover, we design a practical, sub-optimal adaptive-probing strategy that self-learns the behavior of the PU's dynamics and exploits the proposed optimal probing method. Specifically, we find that the most widely used spectrum-probing scheme, i.e., periodic probing, is not optimal when the arrival rate of the PU state change is not constant or when the distribution of PU channel occupancy/vacancy is not uniform. On the other hand, the derived optimal and adaptive strategies can adapt to the dynamics of PUs and adjust the probing intervals based on the time-varying arrival rate of the PU state changes or the non-uniform distribution of PU channel occupancy/vacancy. Our simulation results show that the optimal spectrum-probing strategies and adaptive-probing methods perform much better and consume much less energy than periodic probing in realistic environments.