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Power Allocation Strategy of Maximizing Secrecy Rate for Secure Directional Modulation Networks

Wan, Simin, Shu, Feng, Lu, Jinhui, Gui, Guan, Wang, Jun, Xia, Guiyang, Zhang, Yijin, Li, Jun, Wang, Jiangzhou (2018) Power Allocation Strategy of Maximizing Secrecy Rate for Secure Directional Modulation Networks. IEEE Access, . ISSN 2169-3536. (doi:10.1109/ACCESS.2018.2815779) (KAR id:66687)

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In this paper, given the beamforming vector of confidential messages and artificial noise (AN) projection matrix and total power constraint, a power allocation (PA) strategy of maximizing secrecy rate (Max-SR) is proposed for secure directional modulation (DM) networks. By the method of Lagrange multiplier, the analytic expression of the proposed PA strategy is derived. To confirm the benefit from the Max-SRbased PA strategy, we take the null-space projection (NSP) beamforming scheme as an example and derive its closed-form expression of optimal PA strategy. From simulation results, we find the following facts: in the medium and high signal-to-noiseratio (SNR) regions, compared with three typical PA parameters such ? = 0:1, 0:5, and 0:9, the optimal PA shows a substantial SR performance gain with maximum gain percent up to more than 60%. Additionally, as the PA factor increases from 0 to 1, the achievable SR increases accordingly in the low SNR region whereas it first increases and then decreases in the medium and high SNR regions, where the SR can be approximately viewed as a convex function of the PA factor. Finally, as the number of antennas increases, the optimal PA factor becomes large and tends to one in the medium and high SNR region. In other words, the contribution of AN to SR can be trivial in such a situation.

Item Type: Article
DOI/Identification number: 10.1109/ACCESS.2018.2815779
Uncontrolled keywords: power allocation, secure, directional modulation, secrecy rate, beamforming
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Jiangzhou Wang
Date Deposited: 11 Apr 2018 11:36 UTC
Last Modified: 16 Feb 2021 13:54 UTC
Resource URI: (The current URI for this page, for reference purposes)
Wang, Jiangzhou:
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