AI 中文总结
本文针对传统PA辅助ISAC架构未充分利用空间自由度的问题，提出可模式选择的PA辅助ISAC框架，通过联合优化多项参数并开发低复杂度算法求解，实现了感知与通信性能协同优化，优于传统基准。
AI 中文摘要
传统收缩天线（PA）辅助的集成感知与通信（ISAC）架构通常假定接收器位置固定或接收波导预先确定，从而未充分利用固有的空间自由度。本文提出一种新型的可模式选择的PA辅助ISAC框架，通过联合优化波导模式选择、发射波束成形以及发射/接收PA位置，在满足多用户服务质量约束的同时最大化合并后感知信噪比。为解决由此产生的混合整数非凸优化问题，我们开发了一种低复杂度块坐标下降算法，该算法利用基于惩罚的主元最小化方法来获得高质量的次优解。数值结果表明，所提出的设计通过协同利用空间适应性和模态可重构性，显著优于传统PA和固定天线基准。特别是，可模式选择的设计能够对发射/接收操作以及感知 - 通信资源分配进行协同优化，从而在严格的通信要求下保持感知稳健性。
英文摘要
Conventional pinching antenna (PA)-assisted integrated sensing and communication (ISAC) architectures typically assume static receiver locations or predetermined receive waveguides, thereby underutilizing the inherent spatial degrees of freedom. This paper proposes a novel mode-selectable PA-assisted ISAC framework to maximize the post-combining sensing signal-to-noise ratio while satisfying multi-user quality-of-service constraints by jointly optimizing the waveguide mode selection, transmit beamforming, and transmit/receive PA positions. To tackle the resulting mixed-integer nonconvex optimization problem, we develop a low-complexity block-coordinate descent algorithm that leverages a penalty-based majorization-minimization method to achieve high-quality suboptimal solutions. Numerical results demonstrate that the proposed design significantly outperforms both traditional PA and fixed-antenna benchmarks by synergistically harnessing spatial adaptability and modal reconfigurability. In particular, the mode-selectable design enables the coordinated optimization of transmit/receive operations and sensing-communication resource allocation, thereby maintaining sensing robustness under stringent communication requirements.
