Robust Collaborative Spectrum Sensing Using PHY-Layer Fingerprints in Mobile Cognitive Radio Networks

Abstract

Collaborative spectrum sensing has been proposed to significantly improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, a serious attack, called a primary user emulation attack (PUEA), could decrease the performance of collaborative spectrum sensing. In this letter, according to mobile CRNs, we propose a novel robust collaborative spectrum sensing method using physical-layer fingerprints power in a multipath Rayleigh fading channel. Moreover, a fingerprints-power-belief-based noncentral detection algorithm is designed to defend against PUEAs. Simulation results show that our proposed method can rapidly detect the presence of a primary user under PUEAs with good performance.