Double Thresholds of Trusted Hard Decision Fusion Algorithm in Cooperative Spectrum Sensing

Hard decision fusion algorithm improves the accuracy of cooperative spectrum sensing. However, traditional hard decision fusion algorithms receive all sensing data without filtering, which provides an opportunity to malicious users. To defense malicious users’ spectrum sensing data falsification attack, this paper proposes a double thresholds of reputation-based hard decision fusion algorithm (RHDF). Only trusted secondary users’ sensing reports will be received by fusion center. Meanwhile RHDF algorithm adopts priority to take half fusion method with double thresholds to improve the efficiency of fusion decision, and better to avoid the impact of malicious users. The simulation results show that compared with traditional hard decision fusion algorithms, RHDF algorithm can more effectively defense SSDF attacks and ensure better cooperation spectrum sensing performance.