Robust and Secure Spectrum Sensing in Cognitive Radio Networks
Author | : Changlong Chen |
Publisher | : |
Total Pages | : 103 |
Release | : 2013 |
Genre | : Cognitive radio networks |
ISBN | : |
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With wireless devices and applications booming, the problem of inefficient utilization of the precious radio spectrum has arisen. Cognitive radio is a key technology to improve spectrum utilization. A major challenge in cognitive radio networks is spectrum sensing, which detects if a spectrum band is being used by a primary user. Spectrum sensing plays a critical role in cognitive radio networks. However, spectrum sensing is vulnerable to security attacks from malicious users. In this dissertation, we propose a malicious user detection scheme, a density based SSDF detection scheme, a conjugate prior based SSDF detection scheme, and an anti-jamming algorithm to achieve robust and secure cooperative spectrum sensing in cognitive radio networks. Performance analysis and simulation results show that our proposed schemes can achieve very good performance in detecting malicious users, excluding abnormal sensing reports, and defending the jamming attack, thus improve spectrum sensing performance in cognitive radio networks.