4.7 Article

Directional Modulation: A Physical-Layer Security Solution to B5G and Future Wireless Networks

Journal

IEEE NETWORK
Volume 34, Issue 2, Pages 210-215

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.001.1900258

Keywords

Direction-of-arrival estimation; Transmitters; Array signal processing; Measurement errors; Measurement uncertainty; Antenna arrays; Machine learning

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Directional modulation (DM), as an efficient secure transmission method, offers security through its directive property and is suitability for LoP channels such as millimeter wave, UAV, satellite communication, and smart transportation. If the direction angle of the desired user is known, the desired channel gain vector is obtainable. Thus, in advance, the DM transmitter knows the values of the directional angles of the desired user and eavesdropper, or their DOAs because the BVCM andANPM are mainly determined by the directional angles of the desired user and eavesdropper. For a DM transceiver, working as a receiver, the first step is to measure the DOAs of the desired user and eavesdropper. Then, in the second step, using the measured DOAs, the BVCM and ANPM are designed. In this article, we describe DOA measurement methods, power allocation, and beamforming in DM networks. A machine learning-based DOA measurement method is proposed to make a substantial secrecy rate (SR) performance gain compared to single-snapshot measurement without machine learning for a given null-space projection beamforming scheme. However, for a conventional DM network, there still exists a serious security issue: the eavesdropper moves inside the main beam of the desired user and may intercept the CMs intended for the desired users because the BVCM and ANPM are only angle-dependent. To address this problem, we present a new concept of SPWT, where the transmit waveform has two-dimensional dependency by using DM, random subcarrier selection with randomization procedure, and phase alignment at the DM transmitter.

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