Modeling and Analysis for Multiple-Layer LEO Satellite Internet of Things Constellations
2026-07-10 • Information Theory
Information Theory
AI summaryⓘ
The authors studied how multiple layers of low Earth orbit (LEO) satellites can provide global Internet of Things (IoT) coverage, especially when the satellite signals experience realistic Rician fading. They created a new mathematical model using stochastic geometry and a unique channel approximation to simplify complex signal behavior. This allowed them to derive exact formulas for important factors like connectivity, coverage, and data rates for short IoT messages. Their simulations confirmed the model works well and can help design better satellite IoT networks.
Low Earth Orbit (LEO)Internet of Things (IoT)Rician fadingStochastic geometryCox point processesConnectivity probabilityCoverage probabilityTransmission rateShort-packet transmissionSatellite communication
Authors
Ming Ying, Xiaoming Chen, Qiao Qi, Yichao Xu
Abstract
To provide multiple-satellite coverage for global Internet of Things (IoT), a low Earth orbit (LEO) satellite IoT constellation usually contains multiple-layer orbits with different altitudes. However, the performance of multiple-layer LEO satellite IoT constellations under practical Rician fading satellite channels remains unknown due to complex theoretical modeling and intractable mathematical analysis. To address these challenges, this paper proposes a stochastic geometry-based modeling and analysis framework for multiple-layer LEO satellite IoT constellations, integrating Rician channel modeling and Cox point processes. Specifically, we introduce a novel channel approximation method to overcome the intractable expressions caused by the Rician fading. Building on this method, we derive exact closed-form expressions for key performance metrics, including connectivity probability, coverage probability, and transmission rate, especially in the case of IoT short-packet transmission. Extensive simulation results validate the accuracy and effectiveness of the proposed model and reveal significant design insights. The results not only provide new theoretical perspectives for modeling and analysis of LEO satellite IoT constellations but also offer practical guidance for system deployment and optimization.