A Stochastic Geometry Approach for Analyzing Uplink Performance for IoT-over-Satellite

Recent satellite constellations are being deployed to serve massive numbers of wireless devices, especially targeting those located in rural and offshore settings. Accordingly, business models relying on data reported via wireless Internet-of-Things (IoT) networks can now easily utilize satellite constellations to expand their offerings. In this paper, we present an analytic framework for modeling the uplink performance of massive IoT-over-Satellite networks. The framework utilizes tools from stochastic geometry to model the satellites and the users as two random point processes enabling the development of a tractable analytic model for the uplink outage probability. Furthermore, the paper derives the expected normalized throughput and compares the results to Monte-Carlo simulations for intractable constellations such as the Walker models adopted by current satellite deployments. Comparisons show that random constellations provide a tractable lower bound to the performance and average throughput compared to Walker constellations. The analytic model can provide the fast estimation of the uplink performance aiding in designing the IoT-over-Satellite system.