NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Weighted Cooperative Spectrum Sensing in Cognitive Radio Networks
ICCIT '08 Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology - Volume 01
A Spectrum Decision Framework for Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Spectrum sensing: A distributed approach for cognitive terminals
IEEE Journal on Selected Areas in Communications
FMAC for coexisting ad hoc cognitive radio networks
WASA'13 Proceedings of the 8th international conference on Wireless Algorithms, Systems, and Applications
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Spectrum sensing plays a critical role in cognitive radio networks. A good sensing scheme can reduce the false alarm probability and the miss detection probability, and thus improves spectrum utilization. This paper presents a weighted cooperative spectrum sensing framework for infrastructure-based cognitive radio networks, to increase the spectrum sensing accuracy. The framework contains two modules. In the first module, each cognitive radio performs local spectrum sensing and computes the total error probability, which combines the false alarm probability and the miss detection probability. The total error probability and the energy signal from the primary user are then sent to the base station. In the second module, the base station makes a final decision after combining the weighted energy signals from all cognitive radios. The final decision is then broadcasted back to all cognitive radios. To reduce the computation complexity and communication overhead, the base station also instructs the cognitive radios that have large total error probabilities not to report their local sensing results. We have developed a theoretical model for the proposed framework, and derived the optimal detection threshold, as well as the minimum number of cognitive radios required to participate in cooperative sensing, subject to a given total error probability. Numerical results verify that the proposed weighted cooperative spectrum sensing framework significantly improves the sensing accuracy.