Orchestrating Heterogeneous NTNs: From Stochastic Geometry to Resource Allocation

Terrestrial networks face limitations, such as restricted rural broadband coverage and service outages during disasters. To address these challenges, nonterrestrial networks (NTNs) are a promising alternative, utilizing aerial vehicles and satellites to enhance coverage and support diverse user applications. However, existing works lack comprehensive consideration of transmitter availability, resource allocation, and cost constraints, leading to suboptimal network performance and design. This work explores the potential of heterogeneous NTNs, including unmanned aerial vehicles, high-altitude platforms, and satellites. Using stochastic geometry, we analyze downlink performance while considering interruptions in communication service for both low-altitude transmitters (due to recharging needs) and high-altitude transmitters (due to fluctuating solar energy harvesting). Our analysis derives connection probabilities, representing the likelihood of transmitters establishing downlink connections with ground users. We propose a resource allocation framework using convex optimization techniques to maximize the downlink connection probability while considering economic costs and communication quality-of-service requirements. Numerical evaluations highlight the significance of incorporating low-Earth orbit satellites and demonstrate the influence of economic cost and signal-to-interference-plus-noise ratio (SINR)-related constraints. Results indicate that allocating resources to higher-altitude layers is favorable under stringent cost constraints while lower-altitude layers are preferred under strict SINR constraints due to improved propagation conditions.