LIVE-RIS：用于无人机载RIS信道测量的综合飞行数据集
LIVE-RIS: A Comprehensive In-Flight Dataset for UAV-Mounted RIS Channel Measurements
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中文总结 AI 辅助
针对无人机载RIS研究缺乏实测数据的问题，本文提出首个综合飞行数据集LIVE-RIS，包含EKF状态、真值、RIS配置及S21信道数据，以支持实际环境下的性能验证。
中文摘要 AI 辅助
可重构智能表面（RIS）对无线传播环境的动态控制能力使其成为第六代（6G）无线网络的一项有前景的技术。超越传统的固定位置部署，将RIS与无人机（UAV）集成提供了额外的空间灵活性，有助于形成有利的视距（LoS）条件，并拓宽潜在应用的范围。尽管无人机载RIS系统已引起广泛的研究兴趣，但现有研究主要依赖数值模拟，往往忽视实际约束和现实世界干扰的影响。为弥补这一空白，作者近期展示了首个无人机载RIS原型，并通过实际实验验证了其可行性。通过利用无人机的扩展卡尔曼滤波器（EKF）进行实时RIS重构，所提出的系统有效减轻了干扰效应，并保持了RIS赋能链路的性能增益。为进一步推进无人机载RIS研究并促进更广泛地获取现实世界实验见解，本工作提供了一个从多次飞行实验中收集的综合数据集。该数据集包括EKF状态估计、地面真值测量、相应的RIS配置以及S21信道数据。
英文摘要
The dynamic control of the wireless propagation environment enabled by reconfigurable intelligent surfaces (RISs) makes them a promising technology for sixth-generation (6G) wireless networks. Beyond conventional fixed-position deployments, integrating a RIS with an unmanned aerial vehicle (UAV) provides additional spatial flexibility, facilitating favorable Line-of-Sight (LoS) conditions and broadening the range of potential applications. Although UAV-mounted RIS systems have attracted significant research interest, existing studies rely predominantly on numerical simulations and often overlook the impact of practical constraints and real-world disturbances. To address this gap, the authors recently presented the first UAV-mounted RIS prototype and experimentally validated its feasibility through real-world experiments. By using the UAV's extended Kalman Filter (EKF) for real-time RIS reconfiguration, the proposed system effectively mitigates disturbance effects and preserves the performance gains of the RIS-enabled link. To further advance UAV-mounted RIS research and facilitate broader access to real-world experimental insights, this work provides a comprehensive dataset collected from multiple flight experiments. The dataset includes EKF state estimates, ground-truth measurements, corresponding RIS configurations, and S21 channel data.
发表机构
- Ruhr-Universität Bochum（波鸿鲁尔大学）
机构由 AI 辅助整理，请以论文原文为准。
