Artificial-Noise-Aided Secure Transmission for Proximal Legitimate User and Eavesdropper Based on Frequency Diverse Arrays

Abstract

In this paper, we aim to address the physical layer security problem for proximal legitimate user (LU) and eavesdropper (Eve) in the case of close-located LU and Eve, where conventional directional modulation (DM) methods may fail to provide efficient secure performance. In order to handle this problem, an optimal frequency offsets of frequency diverse array-based DM with artificial noise (AN) scheme is proposed. We maximize the secrecy capacity by optimizing the frequency offsets and designing AN projection matrix. The optimization problem of the frequency offsets is solved by a block successive upper-bound minimization method to iteratively obtain stationary convergence solutions. By elaborately calculating frequency offsets across array antennas, we can decouple the angle-range correlation and maximize recreational secrecy capacity, resulting in the improvement of the security performance of wireless communications. Numerical results show that the proposed method can provide a higher secrecy capacity than conventional DM schemes with the changes of bandwidth, power allocation factor, and power for the case of proximal LU and Eve. In addition, the proposed scheme is suitable for the case of multi-Eves.