| 摘要: |
| 针对非完美信道状态信息（Channel State Information，CSI）条件下通信感知一体化（Integrated Sensing and Communication，ISAC）系统性能易受信道不确定性影响的问题，研究了一种可移动天线（Movable Antenna，MA）辅助的鲁棒资源优化方法。在信道估计误差存在的情况下，传统基于完美CSI的设计将导致通信与感知性能显著退化，如何在不确定信道条件下实现两者的有效权衡成为关键挑战。考虑基站发射端与通信用户均配备MA的ISAC系统，通过联合优化基站天线位置、发射波束赋形及用户天线位置，在满足通信服务质量约束及天线移动约束的前提下，最大化系统感知互信息。针对所构建问题中变量强耦合、非凸性以及CSI不确定性引入的无穷不等式约束，结合半定松弛与逐次凸逼近方法，提出了一种鲁棒交替优化算法以获得高效可行解。仿真结果表明，与固定位置天线系统相比，所提方案在信道估计误差较大时仍能保持系统稳定性，且感知互信息平均提升了38.8%。 |
| 关键词: 可移动天线 通信感知一体化（ISAC） 波束赋形 |
| DOI：10.20079/j.issn.1001-893x.260131001 |
|
| 基金项目: |
|
| Robust Optimization for Movable Antenna-assisted Integrated Sensing and Communication（ISAC） Systems |
| CHEN Shuheng,HAO Tian,HAO Qi,LI Xue,SONG Lei,LIU Yun,YANG Feng |
| (1.Unit 92728 of PLA，Shanghai 200436，China;2.School of Integrated Circuits，Shanghai Jiao Tong University，Shanghai 200240，China;3.Qingdao Branch of China Research Institute of Radiowave Propagation，Qingdao 266108，China;4.Southwest China Institute of Electronic Technology，Chengdu 610036，China) |
| Abstract: |
| To address the performance degradation of integrated sensing and communication(ISAC) systems caused by imperfect channel state information(CSI)，a robust resource optimization method is investigated for movable antenna(MA)-assisted systems.In the presence of channel estimation errors，conventional designs based on perfect CSI suffer from significant performance loss，making it challenging to achieve an effective trade-off between communication and sensing under channel uncertainty.An MA-enabled ISAC system is considered，where movable antennas are deployed at both the base station and communication users.By jointly optimizing the antenna positions at the base station，transmit beamforming，and antenna positions at the user side，the sensing mutual information is maximized while satisfying communication quality-of-service constraints and antenna movement constraints.The resulting problem is highly non-convex with strongly coupled variables，and CSI uncertainty further introduces infinitely many inequality constraints.To tackle these challenges，a robust alternating optimization algorithm is developed by integrating semidefinite relaxation and successive convex approximation to obtain efficient feasible solutions.Simulation results demonstrate that，compared with fixed-position antenna systems，the proposed scheme maintains system stability under severe channel estimation errors and achieves an average improvement of 38.8% in sensing mutual information. |
| Key words: movable antenna integrated sensing and communication（ISAC） beamforming |
《电讯技术》编辑部 