Joint beamforming and power allocation for secure communication in cognitive radio networks. Issue 10 (1st July 2016)

• Record Type: Journal Article
• Authors: Chen, Tao; Yuan, HuaQiang; Zhao, TieZhu; Zhang, ZuSheng; Ao, Xin
• Is Part Of: IET communications. Volume 10:Issue 10(2016)
• Page Start: 1156
• Page End: 1162
• Publication Date: 2016-07-01
• Subjects: cognitive radio -- telecommunication security -- array signal processing -- cooperative communication -- concave programming -- radiofrequency interference; joint beamforming‐power allocation scheme -- secure communication -- cognitive radio networks -- cooperative jammer -- artificial noise -- eavesdropper -- available secrecy rate -- secondary user -- SU transmitter -- interference power constraint -- primary user -- global transmit power constraint -- beamforming vector -- nonconvex optimisation problem -- suboptimal algorithm -- complete orthogonal projection -- partial orthogonal projection -- transmit beamforming vector -- iteration; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2014.1243
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, secure communication in cognitive radio networks is investigated. A cooperative jammer is utilised to transmit artificial noise for interfering with the eavesdropper. The authors' objective is to maximise the available secrecy rate of the secondary user (SU) under the interference power constraint at the primary user and the global transmit power constraint at the transmitters. In that case, beamforming vectors of the SU transmitter and the cooperative jammer, and power allocation between them need to be optimised. However, the optimisation problem is non‐convex and hard to solve. In order to tackle it, two suboptimal algorithms are proposed: complete orthogonal projection and partial orthogonal projection. In these algorithms, the original optimisation problems are first decoupled into two sub‐problems, which deal with the transmit beamforming vectors and power allocation, respectively. Then, the optimal solution is obtained by iteration alternately. Finally, simulation results verify the effectiveness of the proposed algorithms.