基于梯度元学习的MA赋能安全ISAC系统中的天线定位与波束成形优化
Antenna Positioning and Beamforming Optimization in MA Enabled Secure ISAC Systems: A Gradient-Based Meta Learning Approach
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中文总结 AI 辅助
针对MA赋能安全ISAC系统的天线定位与波束成形优化难题，提出无需预训练的梯度元学习算法，联合优化天线定位、波束成形及人工噪声，提升系统保密速率与感知性能。
中文摘要 AI 辅助
集成感知与通信（ISAC）显著提升频谱效率，但引入了嵌入通信信号被截获的安全风险。本文提出一种可移动天线（MA）赋能的安全ISAC系统，利用MA的空间自由度缓解这些风险。随后构建优化问题，通过联合优化天线定位、发射波束成形及人工噪声，最大化系统保密速率。然而，该优化问题的非凸性及优化变量间的强耦合是主要挑战。传统优化方法存在复杂数学推导的问题，而现有深度学习方法严重依赖训练数据分布。为解决这些问题，本文引入梯度基元学习（GML）算法，该算法无需预训练即可工作，且表现出良好性能。具体而言，该算法为每个优化变量建立神经网络，以目标函数对该变量的梯度作为输入，网络输出决定变量的更新步长。通过处理约束并构造惩罚项，全局损失函数用于引导优化过程。大量数值仿真证实，所提算法在通信安全性和感知能力方面均取得令人满意的性能。
英文摘要
Integrated sensing and communications (ISAC) significantly improves spectral efficiency but introduces security risks regarding the interception of embedded communication signals. This paper proposes an movable antenna (MA)-enabled secure ISAC system that utilizes the spatial degrees of freedom of MA to mitigate these risks. Then, a problem is formulated to maximize the system secrecy rate by jointly optimizing antenna positioning, transmit beamforming, and artificial noise. However, the principal challenge arises from the non-convexity of the optimization problem and the strong coupling of the optimization variables. Generally, traditional optimization methods for this problem suffer from complex mathematical derivations, while existing deep learning approaches rely heavily on the training data distribution. To address these issues, we introduce a gradient-based meta learning (GML) algorithm, which works without pre-training and demonstrates favorable performance. Specifically, the algorithm establishes a neural network for each optimization variable, where the gradient of the objective function with respect to the variable serves as the input, and the output of the network determines the variable's update step. By handling the constraints and constructing penalty terms, the global loss function is used to guide the optimization process. Extensive numerical simulations confirm that the proposed algorithm achieves satisfactory performance in terms of both communication security and sensing capabilities.
