Secrecy performance analysis of SIMO underlay cognitive radio systems with outdated CSI
Ansari, Imran Shafique
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/625986
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AbstractThis study investigates the secrecy outage performance of a single-input multiple-output underlay cognitive radio network (CRN) with outdated channel state information (CSI). The confidential messages are transmitted from transmitter to the destination, while a multi-antenna eavesdropper exists. The maximal ratio combining and selection combining schemes are utilised at the receivers to improve the quality of the received signal-to-noise ratio. The exact and asymptotic closed-form expressions of secrecy outage probability are derived, and simulation results are provided to verify the authors' proposed analytical results. The results reveal that imperfect CSI of main channels deteriorates the secrecy outage performance while that of eavesdropping and interfering channels has contrary effect, and only a unity diversity order can be obtained in underlay CRNs with imperfect CSI.
CitationLei H, Zhang J, Park K-H, Ansari IS, Pan G, et al. (2017) Secrecy performance analysis of SIMO underlay cognitive radio systems with outdated CSI . IET Communications 11: 1961–1969. Available: http://dx.doi.org/10.1049/iet-com.2017.0131.
SponsorsThis work was supported in part by the National Natural Science Foundation of China (NSFC) under grant nos. 61471076 and 61401372, the Program for Changjiang Scholars and Innovative Research Team in University under Grant IRT_16R72, the special fund for Key Lab of Chongqing Municipal Education Commission, the Project of Fundamental and Frontier Research Plan of Chongqing under Grant cstc2015jcyjBX0085 and cstc2017jcyjAX0204, Chinese Scholarship Council under Grant 201607845004, and the Scientific and Technological Research Program of Chongqing Municipal Education Commission under grant KJ1600413 and KJ1704088. Parts of this publication were made possible by PDRA (PostDoctoral Research Award) grant # PDRA1-1227-13029 from the Qatar National Research Fund (QNRF) (a member of Qatar Foundation (QF)).