发表机构
Institute of Industrial Science, The University of Tokyo; Center for Spatial Information Science, The University of Tokyo（东京大学工业科学研究所; 东京大学空间信息科学中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种机械Wi-Fi天线控制系统，通过黑盒优化与环境变化检测自适应调整3D天线方向，提升动态多站点场景下的信道容量并避免不必要的重新优化。
AI 中文摘要
虽然室内物联网（IoT）和传感器网络日益依赖Wi-Fi接入点（AP）从多个设备收集高带宽数据流，但传统AP依赖静态天线部署，其固定方向在动态传播环境中往往并非最优。为克服这一局限，本文提出一种机械Wi-Fi天线控制系统，可针对动态多站点场景自适应优化其3D天线方向。该系统通过结合状态特定的黑盒优化器和基于容量的环境变化检测，根据感知到的无线电环境自主驱动其物理天线。评估结果表明，所提系统在动态站点组合下提升了信道容量，在瞬时遮挡下避免了不必要的重新优化，并在持续环境变化（如持续遮挡和设备重新定位）后触发重新优化。
英文摘要
While indoor Internet of Things (IoT) and sensor networks increasingly rely on Wi-Fi access points (APs) to collect high-bandwidth data streams from multiple devices, conventional APs rely on static antenna deployments, whose fixed orientations are often suboptimal in dynamic propagation environments. To overcome this limitation, this paper proposes a mechanical Wi-Fi antenna control system that adaptively optimizes its 3D antenna orientation for dynamic multi-station scenarios. The proposed system autonomously actuates its physical antennas in response to perceived radio environments by combining state-specific black-box optimizers and capacity-based environment change detection. The evaluation results show that the proposed system improves channel capacity under dynamic station combinations, avoids unnecessary re-optimization under transient blockages, and triggers re-optimization after sustained environmental changes such as continuous blockage and device relocation.
CommentsAccepted to IEEE GLOBECOM 2026
