In this paper, two regional robust secure precise wireless transmission (SPWT) schemes for multi-user unmanned aerial vehicle (UAV), (1)regional signal-to-leakage-and-noise ratio (SLNR) and artificial-noise-to-leakage-and-noise ratio (ANLNR) (R-SLNR-ANLNR) maximization and (2) point SLNR and ANLNR (P-SLNR-ANLNR) maximization, are proposed to tackle with the estimation errors of the target users’ location. In the SPWT system, the estimation error for SPWT cannot be ignored. However, the conventional robust methods in secure wireless communications optimize the beamforming vector in the desired positions only in statistical means and cannot guarantee the security for each symbol. The proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location. Specifically, with the known maximal estimation error, we define the target region and wiretap region. Then, we design an optimal beamforming vector and an artificial noise projection matrix, which achieve the confidential signal in the target area having the maximal power while only few signal power is conserved in the potential wiretap region. Instead of considering the statistical distributions of the estimated errors into optimization, we optimize the SLNR and ANLNR of the whole target area, which significantly decreases the complexity. Moreover, the proposed schemes can ensure that the desired users are located in the optimized region, which are more practical than the conventional methods. Simulation results show that our proposed regional robust SPWT design is capable of substantially improving the secrecy rate compared to the conventional non-robust method. The P-SLNR-ANLNR maximization-based method has the comparable secrecy performance with lower complexity than that of the R-SLNR-ANLNR maximization-based method.

本文针对多用户无人机（UAV）提出了两种区域鲁棒的安全精确无线传输（SPWT）方案，（1）区域信噪比（SLNR）和人为噪声比提出了泄漏噪声比（ANLNR）（R-SLNR-ANLNR）最大化和（2）点SLNR和ANNLR（P-SLNR-ANLNR）最大化来解决目标用户位置的估计误差。在SPWT系统中，不能忽略SPWT的估计误差。然而，仅在统计手段中，安全无线通信中的常规鲁棒方法仅在期望位置上优化波束形成矢量，并且不能保证每个符号的安全性。提出的区域鲁棒方案旨在优化估计位置周围整个错误区域的保密性能。特别，利用已知的最大估计误差，我们定义目标区域和窃听区域。然后，我们设计了一个最佳的波束成形矢量和一个人工噪声投影矩阵，可以在目标区域中获得具有最大功率的机密信号，而在潜在的窃听区域仅保留很少的信号功率。我们没有考虑估计误差的统计分布进行优化，而是优化了整个目标区域的SLNR和ANLNR，这大大降低了复杂度。而且，所提出的方案可以确保期望的用户位于优化区域中，这比常规方法更实用。仿真结果表明，与传统的非鲁棒方法相比，我们提出的区域鲁棒SPWT设计能够显着提高保密率。与基于R-SLNR-ANLNR最大化的方法相比，基于P-SLNR-ANLNR最大化的方法具有相当的保密性能，并且复杂度更低。