In this paper we consider cooperative spectrum sensing to detect incumbent spectrum users (ISU) in cognitive radio (CR) networks. We propose a time-divisional cooperative periodic spectrum sensing (TD-CPSS) technique and analyze the detection performance based on the blind energy based detection scheme. The CR detects the presence of the ISU by means of TD-CPSS and opportunistically uses the spectrum for secondary communications. The proposed technique saves energy at the local CR nodes due to periodic sensing and at the same time maintains the minimum required detection probability by optimizing the sensing period. The detection probability together with the false alarm probability are derived for the TD-CPSS technique based on the additive noise at the sensing node and the temporal statistics of the ISU transmissions. In our model, we consider additive white Gaussian noise (AWGN) for local sensing and the Poisson-Pareto spectral occupancy model for the temporal behavior of the ISU transmissions. We also provide expression for the required time period for the proposed sensing technique which attains the minimum required detection probability whilst minimizing the energy consumption considering the noise and temporal statistics.

Time-Divisional cooperative periodic spectrum sensing for cognitive radio networks

GIORGETTI, ANDREA;CHIANI, MARCO
2010

Abstract

In this paper we consider cooperative spectrum sensing to detect incumbent spectrum users (ISU) in cognitive radio (CR) networks. We propose a time-divisional cooperative periodic spectrum sensing (TD-CPSS) technique and analyze the detection performance based on the blind energy based detection scheme. The CR detects the presence of the ISU by means of TD-CPSS and opportunistically uses the spectrum for secondary communications. The proposed technique saves energy at the local CR nodes due to periodic sensing and at the same time maintains the minimum required detection probability by optimizing the sensing period. The detection probability together with the false alarm probability are derived for the TD-CPSS technique based on the additive noise at the sensing node and the temporal statistics of the ISU transmissions. In our model, we consider additive white Gaussian noise (AWGN) for local sensing and the Poisson-Pareto spectral occupancy model for the temporal behavior of the ISU transmissions. We also provide expression for the required time period for the proposed sensing technique which attains the minimum required detection probability whilst minimizing the energy consumption considering the noise and temporal statistics.
2010
Proc. IEEE Int. Conf. on Commun. (ICC 2010)
1
6
S. Kandeepan; A. Giorgetti; M. Chiani
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/94036
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