The Novel Crowdsourcing Algorithm for Cooperative Spectrum Sensing

Abstract

Cooperative spectrum sensing with the crowdsourcing model has become an innovative and efficient technique for obtaining the spectrum state information (SSI) under the cognitive radio networks. Specifically, the secondary users sense the licensed spectrum then send the SSI back to the fusion center according to the crowdsourcing model. In practice, the users with malicious or erroneous behavior are always existing among those secondary users. Thus the accuracy of spectrum sensing would be influenced by those users. In this paper, a novel crowdsourcing algorithm for cooperative spectrum sensing is proposed to detect the malicious users and further improve the accuracy of spectrum sensing. The agreement ratio is introduced in the proposed scheme, which is an important information under the crowdsourcing framework. Simulation results show that the proposed algorithm possesses better performance than the existing approaches.