Research Article
Eigenvalues based spectrum sensing against untrusted users in cognitive radio networks
@INPROCEEDINGS{10.1109/CROWNCOM.2009.5188923, author={Shaoyi Xu and Yanlei Shang and Haiming Wang}, title={Eigenvalues based spectrum sensing against untrusted users in cognitive radio networks}, proceedings={4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications}, publisher={IEEE}, proceedings_a={CROWNCOM}, year={2009}, month={8}, keywords={Cognitive Radio (CR); primary user (PU);secondary user (SU); untrusted user; maximum eigenvalue (MEV)}, doi={10.1109/CROWNCOM.2009.5188923} }- Shaoyi Xu
Yanlei Shang
Haiming Wang
Year: 2009
Eigenvalues based spectrum sensing against untrusted users in cognitive radio networks
CROWNCOM
IEEE
DOI: 10.1109/CROWNCOM.2009.5188923
Abstract
Spectrum sensing is an essential mechanism for a cognitive radio system. However, the security aspects of spectrum sensing receive little attention so far. In this paper, we identify two kinds of untrusted secondary users which are called dasiaAlways Yespsila users and dasiaAlways Nopsila users. These untrusted secondary users can degrade detection performance greatly, especially when conventional data fusion rules are applied. To counter these threats, for the correlated primary signals, an eigenvalues based detection scheme with double thresholds and revised data fusion rules is proposed. Maximum eigenvalues are proved to be very effective to detect the correlated primary signals and to find the untrusted users. By using the revised data fusion rules, simulation shows that our method has a better detection performance than the conventional method.
