In this paper, we propose an integrated sensing and communication (ISAC) system enabled by movable antennas (MAs), which can dynamically adjust antenna positions to enhance both sensing and communication performance for future wireless networks. To characterize the benefits of MA-enabled ISAC systems, we first derive the Cram\'er-Rao bound (CRB) for angle estimation error, which is then minimized for optimizing the antenna position vector (APV) and beamforming design, subject to a pre-defined signal-to-noise ratio (SNR) constraint to ensure the communication performance. In particular, for the case with receive MAs only, we provide a closed-form optimal antenna position solution, and show that employing MAs over conventional fixed-position antennas (FPAs) can achieve a sensing performance gain upper-bounded by 4.77 dB. On the other hand, for the case with transmit MAs only, we develop a boundary traversal breadth-first search (BT-BFS) algorithm to obtain the global optimal solution in the line-of-sight (LoS) channel scenario, along with a lower-complexity boundary traversal depth-first search (BT-DFS) algorithm to find a local optimal solution efficiently. While in the scenario with non-LoS (NLoS) channels, a majorization-minimization (MM) based Rosen's gradient projection (RGP) algorithm with an efficient initialization method is proposed to obtain stationary solutions for the considered problem, which can be extended to the general case with both transmit and receive MAs. Extensive numerical results are presented to verify the effectiveness of the proposed algorithms, and demonstrate the superiority of the considered MA-enabled ISAC system over conventional ISAC systems with FPAs in terms of sensing and communication performance trade-off.

翻译：本文提出了一种由可移动天线赋能的集成感知与通信系统，该系统可通过动态调整天线位置来增强未来无线网络的感知与通信性能。为表征MA赋能ISAC系统的优势，我们首先推导了角度估计误差的克拉美-罗界，随后在确保通信性能的预设信噪比约束下，通过优化天线位置向量与波束成形设计来最小化该界值。具体而言，针对仅接收端配备MA的情况，我们给出了闭式最优天线位置解，并证明相较于传统固定位置天线，采用MA可实现感知性能增益上界达4.77分贝。另一方面，针对仅发射端配备MA的情况，在视距信道场景中，我们提出了边界遍历广度优先搜索算法以获得全局最优解，同时设计了复杂度更低的边界遍历深度优先搜索算法来高效获取局部最优解。而在非视距信道场景中，我们提出了基于最大化-最小化框架的罗森梯度投影算法，并结合高效初始化方法获取所考虑问题的稳态解，该算法可扩展至收发两端均配备MA的通用场景。大量数值结果验证了所提算法的有效性，并证明了所研究的MA赋能ISAC系统在感知与通信性能权衡方面优于采用固定位置天线的传统ISAC系统。