A high-efficiency framework for Cooperative Spectrum Sensing

To utilize effectively the reporting slots in Cooperative Spectrum Sensing (CSS) and enhance the sensing performance, a novel CSS framework is designed. The core idea of the proposed framework is that, when a Secondary User (SU) is reporting the sensing results, the following Sus continue local sensing until their turns to report. Since a half of idle reporting slots are appropriately utilized for sensing, the proposed framework behaves more efficiently. Moreover, based on Neyman-Pearson criteria, the optimal schedules for AND rule and OR rule are investigated respectively, followed by the discussions of the sensing performance gains under the proposed framework. Simulation results demonstrate that, the proposed framework enhances the CSS performance considerately without any additional sensing delay.