References of "Pandharipande, Ashish"
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See detailEnergy-Efficient Distributed Spectrum Sensing for Cognitive Sensor Networks
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in IEEE Sensors Journal (2011), 11(3), 565-573

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 ... [more ▼]

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. [less ▲]

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See detailTwo-stage spectrum sensing for cognitive radios
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) (2010, March)

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 ... [more ▼]

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. [less ▲]

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See detailEnergy-efficient distributed spectrum sensing with convex optimization
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 (2009, December)

We consider the problem of distributed spectrum sensing in cognitive radio networks with a central fusion center, from an energy efficiency viewpoint. In our scheme, each cognitive radio adopts a ... [more ▼]

We consider the problem of distributed spectrum sensing in cognitive radio networks with a central fusion center, from an energy efficiency viewpoint. In our scheme, each cognitive radio adopts a combination of sleeping and censoring to obtain a sensing result based on energy detection, while the fusion center combines all the sensing results using an OR decision rule. Our goal is to minimize the network energy consumption, given constraints on the global probabilities of detection and false-alarm. We show that the underlying optimization problem can be solved as a convex optimization problem. We then show the energy efficiency of our scheme via simulations using a ZigBee transceiver model. [less ▲]

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See detailEnergy-efficient spectrum sensing for cognitive sensor networks
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in 35th Annual Conference of IEEE Industrial Electronics, 2009. IECON '09 (2009, November)

We consider a combined sleeping and censoring scheme for energy-efficient spectrum sensing in cognitive sensor networks. We analyze the detection performance of this scheme by theoretically deriving the ... [more ▼]

We consider a combined sleeping and censoring scheme for energy-efficient spectrum sensing in cognitive sensor networks. We analyze the detection performance of this scheme by theoretically deriving the global probabilities of detection and false-alarm. Our goal is to minimize the energy consumption incurred in distributed sensing, given constraints on the global probabilities of detection and false-alarm, by optimally designing the sleeping rate and the censoring thresholds. Using specific transceiver models for sensors based on IEEE 802.15.4/ZigBee, we show the energy savings achieved under an optimum choice of the design parameters. [less ▲]

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