Energy-Efficient Cooperative Spectrum Sensing Scheme Based on Spatial Correlation for Cognitive Internet of Things
Runze Wan, Mou Wu, Luokai Hu, Haijun Wang
Abstract
Due to the negative impact from spatial correlation, spatially correlated cognitive radio (CR) based devices participating in cooperative spectrum sensing may be harmful to the detection performance. In this paper, we propose an energy-efficient cooperative spectrum sensing scheme based on spatial correlation for cognitive Internet of Things (CIoT). To mitigate the communication overhead and ensure sufficient sensing accuracy, the CR-based devices (CRDs) can be grouped into several clusters. The member nodes undertake cooperative spectrum sensing tasks in turn, and send the local test statistic to their cluster head nearby. Then, by exploiting the spatial correlation of the members, the cluster head combines the sensing results and makes use of likelihood ratio test to obtain the cluster decision. After receiving the decisions from all clusters, the fusion center employs hard fusion scheme to make the final decision about spectrum occupancy. The simulation results show that our scheme not only provides the better sensing performance, but also improve the energy efficiency.