1 research outputs found
Secure Directional Modulation to Enhance Physical Layer Security in IoT Networks
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.Comment: 9 pages, 12 figures, Io