仰望天空预测地面：面向任意位置LEO网络的物理信息链路状态预测

中文摘要 AI 辅助

本文介绍了Gnomon，一个物理信息驱动的系统，用于在不同轨迹数据可用性水平下预测用户感知的低地球轨道（LEO）下行吞吐量、上行吞吐量和往返时间（RTT）。Gnomon的物理层从公开的天气、轨道、路由和许可数据中重建服务几何和四段弯管衰减。根据可用数据，Gnomon基于目标终端自身历史（模式1）、附近公开可及天线的测量（模式2）或仅物理协变量（模式3）来预测链路状态：模式1和模式2共享一个微调的时间序列基础模型，而模式3使用紧凑的梯度提升树估计器。所有三种模式都暴露了共同的输出接口，并且可以在不重新训练的情况下进行选择。我们使用在美国五个州九个地点收集的8,260分钟1 Hz测量数据评估Gnomon。我们在三个地点进行训练，并保留其余六个地点及其服务波束作为测试。在这些未见过的地点上，自身轨迹模式相对于最强已发表基线将下行吞吐量和RTT预测误差分别降低了17%和11%，并且据我们所知，提供了首个LEO上行链路预测。邻居轨迹模式不需要现场硬件，而仅协变量模式相对于唯一的先前仅协变量预测器将下行吞吐量和RTT误差分别降低了24.6%和78.8%。此外，实验表明Gnomon提供了校准的分位数带，并改善了在重放的Starlink链路上通过真实TCP流驱动的自适应比特率流媒体。

英文摘要

In this paper, we introduce Gnomon, a physics-informed system that forecasts user-perceived low-Earth-orbit (LEO) downlink throughput, uplink throughput, and round-trip time (RTT) under different levels of trace availability. Gnomon's physics layer reconstructs the serving geometry and four-leg bent-pipe attenuation from public weather, orbital, routing, and licensing data. Based on what is available, Gnomon conditions on the target terminal's own history (Mode 1), measurements from nearby publicly reachable dishes (Mode 2), or the physical covariates alone (Mode 3) to predict the link state: Modes 1 and 2 share a fine-tuned time-series foundation model, while Mode 3 uses a compact boosted-tree estimator. All three modes expose a common output interface and can be selected without retraining. We evaluate Gnomon using 8,260 minutes of 1 Hz measurements collected at nine sites across five states in the U.S. We train on three sites and hold out the remaining six sites and their serving beams. On these unseen sites, the own-trace mode reduces downlink-throughput and RTT prediction error by 17% and 11% relative to the strongest published baseline and, to our knowledge, provides the first LEO uplink forecasts. The neighbor-trace mode requires no on-site hardware, while the covariate-only mode reduces downlink-throughput and RTT error by 24.6% and 78.8% relative to the only prior covariate-only forecaster. Moreover, experiments show that Gnomon provides calibrated quantile bands and improves adaptive-bitrate streaming driven over real TCP flows on replayed Starlink links.

发表机构

• Princeton University（普林斯顿大学）
• University of Georgia（佐治亚大学）
• University of Pittsburgh（匹兹堡大学）

机构由 AI 辅助整理，请以论文原文为准。