发表机构
University of Luxembourg; University of Rome Tor Vergata（卢森堡大学; 罗马托尔维加塔大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出可移动单元STAR-RIS用于通感一体化，通过几何重构改善通信感知权衡，采用双时间尺度控制，并分析实际挑战与未来研究方向。
AI 中文摘要
同时透射和反射可重构智能表面（STAR-RIS）通过实现可控的全空间传播，扩展了传统的仅反射表面。然而，一旦部署，其单元的物理位置保持固定，使得表面几何形状无法适应用户、感知目标、遮挡或近场聚焦条件。本文从系统层面探讨了用于通感一体化（ISAC）的可移动单元STAR-RIS（ME--STAR--RIS），其中表面同时重构其电磁响应和单元的物理位置。我们解释了几何重构如何重塑有效孔径、空间相关性、干扰零点以及感知照明，同时保持STAR-RIS的全空间操作。一种双时间尺度控制架构将相对较慢的单元运动与快速的波束成形及透射/反射控制分离。一项包含100次实现的说明性案例研究，在被动耦合透射/反射响应下，将ME--STAR--RIS与一个其他方面相同的固定STAR-RIS进行比较。结果表明，采样的通信-感知权衡显著改善，且重要的是，速率增益随适度的单元移动而迅速饱和。最后，我们总结了代表性用例、实现约束以及研究路线图，涵盖移动性开销、信道获取、互耦、近场操作、硬件损伤以及学习辅助的预测控制。
英文摘要
Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) extend conventional reflecting-only surfaces by enabling controllable full-space propagation. Yet, once deployed, the physical locations of their elements remain fixed, leaving the surface geometry unable to adapt to users, sensing targets, blockage, or near-field focusing conditions. This article develops a system-level perspective on movable-element STAR-RIS (ME--STAR--RIS) for integrated sensing and communication (ISAC), where the surface jointly reconfigures its electromagnetic response and the physical positions of its elements. We explain how geometric reconfiguration can reshape the effective aperture, spatial correlation, interference nulls, and sensing illumination while preserving STAR-RIS full-space operation. A two-timescale control architecture separates relatively slow element motion from fast beamforming and transmission/reflection control. A 100-realization illustrative case study compares ME--STAR--RIS with an otherwise identical fixed STAR-RIS under a passive coupled transmission/reflection response. The results show a substantially improved sampled communication--sensing tradeoff and, importantly, a rapid saturation of the rate gain with modest element travel. We conclude with representative use cases, implementation constraints, and a research roadmap covering mobility overhead, channel acquisition, mutual coupling, near-field operation, hardware impairments, and learning-assisted predictive control.
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