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| Fast Adaptive Threshold for Cooperative Spectrum Sensing |
| Xia Wen-fang; Wang Shu; Gong Shi-min; Liu Wei |
| Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China |
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Abstract Spectrum sensing is a key functional part for cognitive radio networks. In heterogeneous networks, the mobility of cognitive nodes will lead to changes in the received signal strength and noise power, which make it difficult for cognitive users to achieve optimal sensing performance at all times using traditional spectrum sensing methods with fixed thresholds. To solve this problem, an adaptive threshold scheme is proposed in this paper. The Steepest Descent Algorithm (SDA) is used to adjust thresholds of all cooperative nodes and the optimal data fusion rule is adopted in the control center to decrease the average Bayesian risk. No prior information of primary signals, channel fading and noise power is needed and the optimal sensing performance is achieved by applying the proposed scheme. Simulation results confirm that the proposed method can quickly converge to optimal sensing parameters in spatial temporal varying environment.
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Received: 19 June 2009
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Corresponding Authors:
Xia Wen-fang
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2010, Vol. 32 
