Cluster-Based Collaborative Spectrum Sensing for Energy Harvesting Cognitive Wireless Communication Network

We consider a cluster-based collaborative spectrum sensing (CSS) scheme in energy harvesting cognitive wireless communication network (EH-CWCN), where cognitive nodes (CNs) are clustered based on their received power levels for enhancing sensing performance. In CSS scheme, time resource is limited and shared by energy harvesting, spectrum sensing, and data transmission. The purpose of this paper is to maximize the average throughput of EH-CWCN by identifying the optimal parameter set, including the durations of energy harvesting and spectrum sensing, local detection threshold, and the number of CNs. Moreover, it is hard to confirm the optimal local detection threshold at CNs with different received power levels. By constructing a fictitious cognitive node (FCN), which is assumed to have the same sensing performance as the sink node, the process for finding the optimal local detection threshold can be converted into the process for searching the optimal received signal-to-noise ratio of the FCN. Then, we formulate the general optimization problem under the collision constraint and energy constraint. Then, the existence and uniqueness of time fractions for energy harvesting and spectrum sensing are proved in this paper. The optimal parameter set is achieved by using the bisection method and a simplified linear search method. Finally, the theoretical analysis and the impact of the optimized parameters on the system performance are verified and shown through numerical simulations.