Secure Directional Modulation to Enhance Physical Layer Security in IoT Networks

TL;DR

This paper introduces an adaptive null-space projection scheme for secure wireless transmission that improves secrecy and error rates by accurately estimating signal directions and adapting beamforming accordingly.

Contribution

It proposes a novel robust null-space projection beamforming method that enhances physical layer security in IoT networks through adaptive DOA estimation and error prediction.

Findings

Significantly reduces bit error rate at the desired user.

Achieves higher secrecy rate compared to conventional schemes.

Performance gains increase with DOA estimation error range.

Abstract

In this work, an adaptive and robust null-space projection (AR-NSP) scheme is proposed for secure transmission with artificial noise (AN)-aided directional modulation (DM) in wireless networks. The proposed scheme is carried out in three steps. Firstly, the directions of arrival (DOAs) of the signals from the desired user and eavesdropper are estimated by the Root Multiple Signal Classificaiton (Root-MUSIC) algorithm and the related signal-to-noise ratios (SNRs) are estimated based on the ratio of the corresponding eigenvalue to the minimum eigenvalue of the covariance matrix of the received signals. In the second step, the value intervals of DOA estimation errors are predicted based on the DOA and SNR estimations. Finally, a robust NSP beamforming DM system is designed according to the afore-obtained estimations and predictions. Our examination shows that the proposed scheme can significantly outperform the conventional non-adaptive robust scheme and non-robust NSP scheme in terms of achieving a much lower bit error rate (BER) at the desired user and a much higher secrecy rate (SR). In addition, the BER and SR performance gains achieved by the proposed scheme relative to other schemes increase with the value range of DOA estimation error.