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Artificial-Noise-Aided Secure Transmission with Directional Modulation based on Random Frequency Diverse Arrays

Hu, Jinsong, Yan, Shihao, Shu, Feng, Wang, Jiangzhou, Li, Jun, Zhang, Yijun (2017) Artificial-Noise-Aided Secure Transmission with Directional Modulation based on Random Frequency Diverse Arrays. IEEE Access, . ISSN 2169-3536. (doi:10.1109/ACCESS.2017.2653182) (KAR id:59862)

Abstract

In this paper, a random frequency diverse array based directional modulation with artificial noise (RFDA-DMAN)

scheme is proposed to enhance physical layer security of wireless communications. Specifically, we first design the RFDADM-

AN scheme by randomly allocating frequencies to transmitantennas, thereby achieving two-dimensionally (i.e., angle and

range) secure transmissions, and outperforming the state-of-theart one-dimensional (i.e., angle) phase array (PA) based DM

scheme. Then we derive the closed-form expression of a lower bound on the ergodic secrecy capacity (ESC) of our RFDA-DMAN scheme. Based on the theoretical lower bound derived, we further optimize the transmission power allocation between the useful signal and artificial noise (AN) in order to improve the ESC. Simulation results show that 1) our RFDA-DM-AN scheme achieves a higher secrecy capacity than that of the PA based DM scheme, 2) the lower bound derived is shown to approach the ESC as the number of transmit antennas N increases and precisely matches the ESC when N is sufficiently large, and 3) the proposed optimum power allocation achieves the highest ESC of all power allocations schemes in the RFDA-DM-AN.

Item Type: Article
DOI/Identification number: 10.1109/ACCESS.2017.2653182
Uncontrolled keywords: Physical layer security, directional modulation, frequency diverse array, power allocation.
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Tina Thompson
Date Deposited: 16 Jan 2017 08:52 UTC
Last Modified: 09 Dec 2022 04:35 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/59862 (The current URI for this page, for reference purposes)

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