A robust cooperative spectrum sensing scheme based on Dempster-Shafer theory and trustworthiness degree calculation in cognitive radio networks

Cognitive radio (CR) is a promising technology that brings about remarkable improvement in spectrum utilization. To tackle the hidden terminal problem, cooperative spectrum sensing (CSS) which benefits from the spatial diversity has been studied extensively. Since CSS is vulnerable to the attacks initiated by malicious secondary users (SUs), several secure CSS schemes based on Dempster-Shafer theory have been proposed. However, the existing works only utilize the current difference of SUs, such as the difference in SNR or similarity degree, to evaluate the trustworthiness of each SU. As the current difference is only one-sided and sometimes inaccurate, the statistical information contained in each SU's historical behavior should not be overlooked. In this article, we propose a robust CSS scheme based on Dempster-Shafer theory and trustworthiness degree calculation. It is carried out in four successive steps, which are basic probability assignment (BPA), trustworthiness degree calculation, selection and adjustment of BPA, and combination by Dempster-Shafer rule, respectively. Our proposed scheme evaluates the trustworthiness degree of SUs from both current difference aspect and historical behavior aspect and exploits Dempster-Shafer theory's potential to establish a ‘soft update’ approach for the reputation value maintenance. It can not only differentiate malicious SUs from honest ones based on their historical behaviors but also reserve the current difference for each SU to achieve a better real-time performance. Abundant simulation results have validated that the proposed scheme outperforms the existing ones under the impact of different attack patterns and different number of malicious SUs.