用于室内沉浸式通信的感知辅助抗遮挡捏合天线系统
Sensing-Assisted Anti-Blockage Pinching-Antenna Systems For Indoor Immersive Communications
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中文总结 AI 辅助
该研究提出感知辅助抗遮挡捏合天线系统PASS，通过集成感知与受控移动，实现室内毫米波通信的抗遮挡，大幅降低中断并维持所需吞吐量。
中文摘要 AI 辅助
室内沉浸式通信由毫米波（mmWave）技术赋能，是面向6G的扩展现实（XR）应用的关键支撑技术。然而，毫米波信号极易受动态障碍物（如移动的人体）影响，导致视距（LoS）链路频繁遮挡。此外，尽管大规模天线系统已在室内广泛应用，但其固定部署方式限制了在工厂、办公室等宽阔且动态的室内环境中的有效性。为应对这些挑战，本文提出一种用于室内沉浸式通信的感知辅助抗遮挡捏合天线系统（Pinching-Antenna Systems, PASS）解决方案。通过沿介质波导机械移动捏合天线（Pinching Antenna, PA），PASS可灵活扩展服务覆盖范围，并在宽阔室内场景中重新建立视距链路。此外，该方案将感知能力集成到PASS中，PA执行受控微移动以收发线性调频（chirp）雷达信号，实现对障碍物的实时感知。基于感知结果，本文设计了一种抗遮挡PA移动策略，该策略可检测波导上的遮挡区域，并主动将PA移动至安全区域。因此，整个系统执行循环的“感知-移动-通信”工作流程，每个循环在有限帧内完成，以确保感知和通信的及时性。为保证系统效率，本文在实际机械和感知约束下推导了感知参数的闭式预优化解决方案。大量实验表明，该方案将遮挡导致的中断降至接近零，同时维持室内沉浸式应用所需的有效吞吐量。
英文摘要
Indoor immersive communication, empowered by millimeter-wave (mmWave) technologies, is a key enabler for 6G-ready Extended Reality (XR) applications. However, mmWave signals are highly susceptible to dynamic obstacles (e.g., moving humans), leading to frequent line-of-sight (LoS) blockages. Moreover, although massive-antenna systems have been widely adopted indoors, their fixed-site deployment limits their effectiveness in wide and dynamic indoor environments such as factories and offices. To address these challenges, we present a sensing-assisted anti-blockage Pinching-Antenna Systems (PASS) solution for indoor immersive communications. By mechanically moving a pinching antenna (PA) along a dielectric waveguide, PASS can flexibly extend the service coverage and re-establish LoS links in wide indoor scenarios. Besides, our solution integrates sensing capabilities into PASS, where the PA executes controlled micro-movements to transmit and receive chirp radar signals, enabling real-time sensing of obstacles. Based on the sensing results, we design an anti-blockage PA movement strategy that detects blocked regions along the waveguide and proactively moves the PA to safe zones. Accordingly, the whole system performs a cycled "sensing-movement-communication" workflow with each cycle completed in a limited frame to ensure both timely sensing and communication. To ensure system efficiency, a closed-form pre-optimized solution of sensing parameters is derived under practical mechanical and sensing constraints. Extensive experiments show that our solution reduces blockage-induced outages to near-zero while sustaining the effective throughput required by indoor immersive applications.
