1.中国工程物理研究院 电子工程研究所;2.西南科技大学 信息工程学院;3.电子科技大学自动化工程学院
TP393
中国工程物理研究院院长基金(YZJJZL2024076, 441 YZJJZQ2023012)；国家自然科学基金资助项目(62441111)；四川省科技计划资助项目(2024NSFSC0476 and 2025YFHZ0199)。
1.Institute of Electronic Engineering,China Academy of Engineering Physics;2. College of Information Engineering,SouthWest University of Science and Technology;3. School of Automation Engineering,University of Electronic Science and Technology of China
the CAEP Foundation under Grant (YZJJZL2024076, YZJJZQ2023012), the National Natural Science Foundation of China under Grant (62441111), and the Sichuan Science and Technology Program (2024NSFSC0476 and 2025YFHZ0199)
针对无人机基站空对地通信链路易受窃听攻击的问题,本文提出了一种基于隐蔽信息映射的广义空间方向调制系统(Covert Information Mapped Generalized Spatial and Direction Modulation, CIM-GSDM),将信息隐藏于激活接收机子集的索引及其选择组合中,同时引入与合法方信道正交的人工噪声干扰窃听方。为进一步提升系统的传输安全性,本文提出了预编码矩阵和功率分配因子联合优化框架,通过有效管理多波束传输和人工噪声的功率分配,增强系统的安全速率。首先,推导了基于系统安全速率的物理层安全性指标,并以此为优化目标,联合优化预编码矩阵和人工噪声功率分配因子。为解决非凸的联合优化问题,考虑交替优化两个变量,提出了一种基于Nesterov下降的自然梯度下降,通过快速迭代更新预编码矩阵,解决了CIM-GSDM符号候选集规模较大带来的计算复杂度问题。基于合法方信噪比与窃听方干信噪比的乘积最大化准则,推导出功率分配因子的次优闭式解。仿真结果表明,所提优化算法在保证合法方可达速率的前提下,显著降低了窃听方的窃听速率,从而有效保证了CIM-GSDM系统的传输安全性。相比传统波束成形算法及固定功率分配因子的方法,本方法在安全性能上具有显著优势。
In response to the vulnerability of UAV-based air-to-ground communication links to eavesdropping attacks, this paper proposes a Covert Information Mapped Generalized Spatial and Direction Modulation (CIM-GSDM) system. The system hides information within the index of the activated receiver subset and their selection combinations, while introducing artificial noise that is orthogonal to the legitimate channel to interfere with the eavesdropper. To further enhance the transmission security of the system, a joint optimization framework for the precoding matrix and power allocation factors is proposed. This framework effectively manages multi-beam transmission and artificial noise power allocation, thereby improving the system"s secure rate. First, the physical layer security metric based on the system"s secure rate is derived, and this is used as the optimization objective for the joint optimization of the precoding matrix and artificial noise power allocation factors. To solve the non-convex joint optimization problem, alternating optimization of the two variables is considered, and a natural gradient descent algorithm based on Nesterov’s method is proposed. This method quickly iterates to update the precoding matrix and resolves the computational complexity issue caused by the large size of the CIM-GSDM symbol candidate set. Based on the criterion of maximizing the product of the legitimate receiver’s signal-to-noise ratio (SNR) and the eavesdropper’s interference-to-signal-plus-noise (ISNR), the suboptimal closed-form solution for the power allocation factor is derived. Simulation results show that the proposed optimization algorithm significantly reduces the eavesdropper’s interception rate while ensuring the legitimate receiver’s achievable rate, effectively securing the transmission in the CIM-GSDM system. Compared to traditional beamforming algorithms and methods with fixed power allocation factors, the proposed method demonstrates a significant advantage in security performance.
