通过LEO卫星交付的物联网数据定价

中文摘要 AI 辅助

由LEO卫星星座服务的物联网终端在离散的上行链路窗口中向过境卫星传输数据。这些数据仅在卫星到达地面站时才交付给买家。这种存储-转发结构使得可实现的价格成为交付完整性阈值的非连续函数（我们称之为“定价悬崖”现象），并产生了极地终端与赤道终端之间的地理定价不对称性，该不对称性取决于星座规模。我们提出了一个综合定价模型，该模型将已部署的Kinéis星座的完整SGP4轨道模拟与缓冲区流模型以及价值衰减框架相结合，其中衰减常数源自应用文献中的运营决策窗口时间尺度，并锚定于观测到的卫星图像市场价格。我们表明，极地和赤道终端受结构上不同的延迟组件主导，需要不同的基础设施干预措施；我们正式刻画了定价悬崖现象及其商业意义，并推导出一个与残值假设完全无关的地理定价溢价。从1颗卫星增加到25颗卫星，极地-赤道溢价降低了25倍，在n=10之后收益递减；在完整星座规模下，溢价降至峰值数据价值的1%以下，并在买家紧迫性的全部合理范围内保持在1.5%以下。

英文摘要

IoT terminals served by LEO satellite constellations transmit data to passing satellites in discrete uplink windows. That data is delivered to buyers only when the satellite reaches a ground station. This store-and-forward structure makes the achievable price a discontinuous function of the delivery completeness threshold (a phenomenon we call a pricing cliff) and creates a geographic pricing asymmetry between polar and equatorial terminals that depends on constellation size. We present an integrated pricing model combining a full SGP4 orbital simulation of the deployed Kinéis constellation with a buffer flow model and a value decay framework with decay constants derived from operational decision-window timescales in the application literature and anchored to observed satellite imagery market prices. We show that polar and equatorial terminals are dominated by structurally different latency components requiring different infrastructure interventions, formally characterize the pricing cliff phenomenon and its commercial significance, and derive a geographic pricing premium that is exactly independent of the residual value assumption. Going from 1 to 25 satellites reduces the polar--equatorial premium by 25x, with diminishing returns beyond n=10; at full constellation size the premium falls below 1% of peak data value and remains below 1.5% across the full plausible range of buyer urgency.

发表机构

• University of Wisconsin–Madison（威斯康星大学麦迪逊分校）

机构由 AI 辅助整理，请以论文原文为准。