Analysis and design of cognitive radio networks and distributed radio resource management algorithms
Analysis and design of cognitive radio networks and distributed radio resource management algorithms
Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff
Wireless Communications & Mobile Computing - Cognitive Radio, Software Defined Radio And Adaptive Wireless Systems
Weighted-Clustering Cooperative Spectrum Sensing in Cognitive Radio Context
CMC '09 Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01
Clustering-Based Compressive Wide-Band Spectrum Sensing in Cognitive Radio Network
MSN '09 Proceedings of the 2009 Fifth International Conference on Mobile Ad-hoc and Sensor Networks
Cluster-based energy efficient cooperative spectrum sensing in cognitive radios
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Wireless Personal Communications: An International Journal
Sensing-Throughput Tradeoff for Cognitive Radio Networks
IEEE Transactions on Wireless Communications
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This paper proposes clustering schemes to solve the sensing throughput tradeoff problem in cooperative cognitive radio networks (CCRNs). The throughput of CCRNs extremely depends on the spectrum sensing performance and data transmission time. In CCRNs, the more secondary users (SUs) for cooperation, the better performance of spectrum sensing. However, the overhead consumption increases as the quantity of cooperative SUs becomes huge, which will lead to less time for data transmission. In this paper, we propose a frame structure that takes the sensing results reporting time into consideration. In order to reduce the reporting time consumption, a centralized cluster-based cooperative cognitive radio system model is created based on the frame structure. The sensing-throughput tradeoff problem under both the perfect reporting channel and imperfect reporting channel scenarios are formulated. The proposed clustering schemes reduce the reporting time consumption and ensure the maximum transmission time of each SU. Numerical results show that the proposed clustering schemes achieve satisfying performance.