Artificial-Noise-Aided Power-efficient Multicast Directional Modulation Scheme of UAV Communication Networks

Abstract With the continuous progress of intelligent unmanned cluster technology, Unmanned Aerial Vehicle (UAV) have been widely used in military operations, agriculture, uran management, disater relief and other fields. However, due to the broadcast nature of wireless channels, the problem of secure transmission also needs to be urgently addressed. Since UAV are resource-constrained aerial platform, upper-layer encryption techniques can hardly play an equally effective role in UAV communication networks. In this paper, we consider the power-efficient secure beamforming scheme in multicast directional modulation (MCDM) scenario. In MCDM, all legitimate UAVs are divided into groups, and there may exist eavesdroppers (Eves) wiretapping the confidential message. We aim to address the PHY security problem for MCDM by jointly optimizing the beamforming vector and the AN projection matrix. Specifically, the power-efficient MCDM PHY secure scheme with known/unknown locations of Eves is proposed respectively. The beamforming vector per group is designed to obtain a desired standard modulation constellation at the target UAVs while distorting the received signals at other undesired receivers. Then, the power-efficient AN projection matrix optimization (PEANO) method is calculated to enhance the interference to Eves while reducing AN power consumption. Numerical results show that the proposed scheme can achieve a secure and power-efficient wireless transmission of confidential messages in MCDM.