Energy-efficient distributed spectrum sensing with convex optimization

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.