发表机构
National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China; Engineering Division, New York University (NYU) Abu Dhabi; National Key Laboratory of Radar Signal Processing, Xidian University; School of Transportation and Logistics, Southwest Jiaotong University; Space Star Technology Co., Ltd.（电子科技大学; 纽约大学阿布扎比分校; 西安电子科技大学; 西南交通大学; 航天恒星科技有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对MA-ISAC系统中天线位置误差导致性能下降的问题，提出鲁棒波束成形与天线位置联合优化方案，通过联合估计误差并最小化最坏情况CRB，在满足SINR约束下提升通信可靠性并保持感知精度。
AI 中文摘要
本文研究了在可移动天线（MA）赋能的集成感知与通信（ISAC）系统中，天线位置误差下的鲁棒波束成形与天线位置设计。具体而言，由于机械精度有限，实际MA阵列中天线实际位置与标称位置之间的偏差不可避免。因此，基于标称位置的传统ISAC设计可能会遭受显著的性能下降。为解决这一问题，我们考虑一个单站下行链路MA-ISAC系统，其中每个传输帧由一个低功率导频和一个ISAC有效载荷组成。基于这两个观测值，联合估计目标角度、反射系数和天线位置误差向量，从而实现在天线位置不完全已知情况下的感知。我们推导了由此产生的角度克拉美-罗界（CRB），并制定了一个优化问题，在所有可能的位置误差下，在满足每个用户的信干噪比（SINR）要求的前提下，最小化其最坏情况值。通过利用一种公共相位响应分解，我们获得了易于处理的重新表述，并开发了一种用于波束成形向量和标称天线位置的交替优化（AO）算法。数值结果表明，与传统标称位置设计相比，所提出的鲁棒方案在实际天线位置不确定性下实现了更高的通信可靠性，同时保持了具有竞争力的感知精度。
英文摘要
This paper investigates robust beamforming and antenna position design for movable antenna (MA)-enabled integrated sensing and communication (ISAC) systems under antenna position errors. In particular, deviations between the actual and nominal antenna positions in practical MA arrays are inevitable due to limited mechanical accuracy. Therefore, the conventional ISAC design based on nominal positions may suffer from substantial performance degradation. To address this issue, we consider a monostatic downlink MA-ISAC system in which each transmission frame consists of a low-power pilot and an ISAC payload. The target angle, reflection coefficient, and antenna position-error vector are jointly estimated based on these two observations, thereby enabling sensing with imperfectly known antenna positions. We derive the resulting angle Cramer-Rao bound (CRB) and formulate a problem that minimizes its worst-case value subject to each user's signal-to-interference-plus-noise ratio (SINR) requirement under all possible position errors. By exploiting a common phase-response decomposition, we obtain tractable reformulations and develop an alternating optimization (AO) algorithm for the beamforming vectors and nominal antenna positions. Numerical results demonstrate that, compared with conventional nominal-position designs, the proposed robust scheme achieves improved communication reliability while maintaining competitive sensing accuracy under practical antenna position uncertainty.
