A novel resource allocation for energy-efficient Cognitive Radio

This paper investigates the energy efficiency (EE) maximization problem in soft decision fusion (SDF) based cooperative spectrum sensing (CSS) system framework. Specifically, we emphasize in optimizing the sensing time and power allocation to the secondary users (SUs) with optimally selected users for both single threshold and double threshold based sensing scheme under the constraint of transmit power, interference to the primary user (PU), outage of SUs and probability of false alarm. To this end, we first propose an efficient algorithm for selecting optimal number of SUs and suitable users that take part in spectrum sensing and data transmission. Then, we formulate the EE maximization problem by using a novel iterative resource allocation (NIRA) algorithm which is based on parametric transformation method. The aid of Lagrangian duality theorem with this novel iterative process jointly helps in optimizing the sensing time and transmit power allocation to the SUs. Extensive simulation results are carried out to validate our proposed algorithm and demonstrate the effectiveness by comparing its performance with the other existing scheme.