Abstract-Reliability and energy consumption in detection are key objectives for distributed spectrum sensing in cognitive sensor networks. In conventional distributed sensing approaches, although the detection performance improves with the number of radios, so does the network energy consumption. We consider a combined sleeping and censoring scheme as an energy efficient spectrum sensing technique for cognitive sensor networks. Our objective is to minimize the energy consumed in distributed sensing subject to constraints on the detection performance, by optimally choosing the sleeping and censoring design parameters. The constraint on the detection performance is given by a minimum target probability of detection and a maximum permissible probability of false alarm. Depending on the availability of prior knowledge about the probability of primary user presence, two cases are considered. The case where a priori knowledge is not available defines the blind setup; otherwise the setup is called knowledge-aided. By considering a sensor network based on IEEE 802.15.4/ZigBee radios, we show that significant energy savings can be achieved by the proposed scheme.Index Terms-Cognitive sensor networks, detection and fusion performance, distributed spectrum sensing.

We present a compressive wide-band spectrum sensing scheme for cognitive radios. The received analog signal at the cognitive radio sensing receiver is transformed in to a digital signal using an analog-to-information converter. The autocorrelation of this compressed signal is then used to reconstruct an estimate of the signal spectrum. We evaluate the performance of this scheme in terms of the mean squared error of the power spectrum density estimate and the probability of detecting signal occupancy.

We consider a two-stage sensing scheme for cognitive radios where coarse sensing based on energy detection is performed in the first stage and, if required, fine sensing based on cyclostationary detection in the second stage. We design the detection threshold parameters in the two sensing stages so as to maximize the probability of detection, given constraints on the probability of false alarm. We compare this scheme with ones where only energy detection or cyclostationary detection is performed. The performance comparison is made based on the probability of detection, probability of false alarm and mean detection time.

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