Cooperative spectrum sensing based on double threshold detection and Dempster-Shafer theory

Cognitive radio is an effective way to improve the utilization of spectrum source. To improve the detection probability in cognitive radio, cooperative spectrum sensing has been proposed. In this paper, we propose a novel algorithm for cooperative spectrum sensing based on double threshold detection and Dempster-Shafer (D-S) theory. Double threshold is used in local detection, which makes the local decision more reliable. The data fusion center uses D-S theory to deal with the observation values that secondary users can't handle with by double threshold energy detection. Final decision is made by combining the results of local detection and data fusion. Simulation results show our proposed algorithm gives significant improvement in detection probability, while the false alarm rate is reduced.