Enhanced Asynchronous Cooperative Spectrum Sensing Based on Dempster-Shafer Theory

In cognitive radio (CR) networks, the cooperative spectrum sensing can greatly improve the sensing performance. However, several existing cooperative spectrum sensing methods have time asynchronization assumption, which will inevitably bring the waste of waiting time, and will cause many limitations in the practical application. In this paper, we propose an enhanced asynchronous cooperative spectrum sensing framework based on the Dempster-Shafer (D-S) theory. Within such a framework, each SU calculates the trust functions with the double threshold spectrum sensing method, which improves the reliability of the local sensing results. In fusion center (FC), it uses the sliding-window method to ensure the real- time performance and the asynchronism of the fusion data. In addition, to reduce the amount of data fusion in FC, we propose a node selection algorithm using the correlations of trust functions. Our analysis and simulation results show that this method can reduce the number of sensing nodes remarkably and improve the spectrum sensing efficiency significantly.