Cluster-Based Energy Efficient Collaborative Spectrum Sensing for Cognitive Sensor Network

Abstract

The high energy efficiency for cognitive sensor network (CSN) has been widely studied for supporting various applications in military and civil fields. By identifying time fraction, local detection threshold, and the number of cognitive sensors, we discuss some design considerations for a cluster-based collaborative spectrum sensing scheme. We formulate the optimization problem to maximize energy efficiency of CSN under a collision constraint and false alarm probability constraint. In order to overcome the problem of finding the optimal detection threshold when k-out-of-M fusion rule is used by the sink node (SN), we design a fictitious cognitive sensor (FCS), which has the same sensing performance as SN. The process for finding the optimal local detection threshold can be converted into the process for searching an optimal received SNR of FCS. Theoretical analysis shows that there exists a unique time fraction to maximize the energy efficiency. Finally, our theoretical analysis is verified through numeric simulations.