AI 中文总结
该研究针对LEO网络的高延迟波动问题，将高可靠远程控制转化为分位数预测问题，提出高分位数估计器，基于OneWeb数据集验证其可提升农场远程控制车辆运行速度138.6%。
AI 中文摘要
低轨（LEO）卫星网络因覆盖广泛，成为支撑农业4.0中农场自动化的极具吸引力的解决方案。然而，LEO网络常存在高延迟波动问题，这会限制其在远程控制等关键农场作业中的应用。本文研究基于LEO网络的高可靠远程控制，将高可靠远程控制转化为分位数预测问题，并提出一种高分位数估计器，可在给定可靠性水平下预测延迟峰值。基于在美国某主要农业枢纽收集的真实OneWeb数据集的结果表明，该估计器可满足可靠性要求，支持农场高可靠远程控制，同时使远程控制车辆的运行速度比原有方案高出138.6%。
英文摘要
LEO satellite networks are an attractive solution to support farm automation in Agriculture 4.0 because of their ubiquitous coverage. However, LEO networks often suffer from high latency volatility, which can limit their utility in mission-critical farm operations such as remote control. This paper studies highly-reliable remote control over LEO networks by (i) casting highly-reliable remote control as a quantile forecasting problem and (ii) proposing a high-quantile estimator that can predict latency spikes at a given reliability level. Our results, drawn from a real-world OneWeb dataset collected in a major agricultural hub in the US, show that the proposed estimator can support highly-reliable remote control on the farm by meeting reliability requirements while allowing the remote-controlled vehicle to operate at speeds up to 138.6% higher than what would be possible otherwise.
CommentsAccepted for presentation at IEEE Globecom 2026
