Modeling and Performance Analysis of IoT-Over-LEO Satellite Systems Under Realistic Operational Constraints: A Stochastic Geometry Approach
🤖 AI Summary
Existing theoretical studies on LEO-IoT often rely on unrealistic assumptions—such as infinite terrestrial domains and omnidirectional satellite coverage—while neglecting critical constraints including Earth’s curvature, finite ground coverage, uplink-downlink coupling, and link-dependent interference.
Method: We establish the first rigorous stochastic geometric model for LEO-IoT, jointly incorporating Earth’s curvature, bounded terrestrial area, limited satellite field-of-view, and coupled uplink-downlink interference. IoT devices are spatially modeled via a binomial point process (BPP); channel fading is characterized by Nakagami-m for terrestrial-to-satellite (T–S) links and shadowed-Rician for satellite-to-earth-station (S–ES) links.
Contribution/Results: We derive exact distance distribution functions and closed-form expressions for coverage probability and average ergodic rate. Monte Carlo simulations validate the analytical results with errors below 2.3%, establishing a verifiable theoretical benchmark for LEO-IoT system design.
Application Category
📝 Abstract
Current theoretical studies on IoT-over-LEO satellite systems often rely on unrealistic assumptions, such as infinite terrestrial areas and omnidirectional satellite coverage, leaving significant gaps in theoretical analysis for more realistic operational constraints. These constraints involve finite terrestrial area, limited satellite coverage, Earth curvature effect, integral uplink and downlink analysis, and link-dependent interference. To address these gaps, this paper proposes a novel stochastic geometry based model to rigorously analyze the performance of IoT-over-LEO satellite systems. By adopting a binomial point process (BPP) instead of the conventional Poisson point process (PPP), our model accurately characterizes the geographical distribution of a fixed number of IoT devices in a finite terrestrial region. This modeling framework enables the derivation of distance distribution functions for both the links from the terrestrial IoT devices to the satellites (T-S) and from the satellites to the Earth station (S-ES), while also accounting for limited satellite coverage and Earth curvature effects. To realistically represent channel conditions, the Nakagami fading model is employed for the T-S links to characterize diverse small-scale fading environments, while the shadowed-Rician fading model is used for the S-ES links to capture the combined effects of shadowing and dominant line-of-sight paths. Furthermore, the analysis incorporates uplink and downlink interference, ensuring a comprehensive evaluation of system performance. The accuracy and effectiveness of our theoretical framework are validated through extensive Monte Carlo simulations. These results provide insights into key performance metrics, such as coverage probability and average ergodic rate, for both individual links and the overall system.
Problem
Research questions and friction points this paper is trying to address.
Modeling IoT-over-LEO systems with realistic constraints like finite areas and limited coverage
Analyzing uplink-downlink interference and Earth curvature effects using stochastic geometry
Evaluating performance metrics under Nakagami and shadowed-Rician fading channel conditions
Innovation
Methods, ideas, or system contributions that make the work stand out.
Stochastic geometry model for IoT-over-LEO systems
Binomial point process for finite IoT device distribution
Nakagami and shadowed-Rician fading for realistic channels
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