A Robust and Efficient Cooperative Spectrum Sensing Scheme in Cognitive Radio Networks

Abstract

Cooperation can improve the performance of spectrum sensing by taking advantage of diversity gains. However, in the process of cooperative spectrum sensing, malicious users could send false local sensing results to the fusion center, which can cause severe distortion to the final sensing decision. To improve the immunity of cooperative spectrum sensing against false sensing information, we propose a robust cooperative spectrum sensing scheme which is based on weighted sequential probability ratio test (WSPRT) technology. Through reputation maintenance, weight allocation and multi-threaded detection, the proposed scheme can effectively deal with different kinds of attack patterns. Simulation results show that our robust scheme can identify and weed out malicious users accurately and efficiently.