Stochastic modeling and performance analysis of multi-altitude LEO satellite networks using cox point processes

Abstract

The research focuses on the stochastic modeling and performance analysis of multi-altitude Low Earth Orbit (LEO) satellite networks using Cox point processes. LEO satellite networks have emerged as a promising solution for global connectivity, offering high data rates and low latency. To optimize their performance and resource allocation, accurate modeling and analysis techniques are crucial. This research employs Cox point processes to model the spatial distribution and behavior of satellites at different altitudes within the network. The intensity functions capture the expected number of satellites per unit area at each altitude. Realizations of the Cox point process are generated using Monte Carlo simulations, enabling performance analysis in terms of network connectivity, coverage probability, signal quality, and interference levels. The results provide insights into network behavior and inform network design decisions, including the optimal number of satellites, their altitudes, and their spatial distribution. The research contributes to the advancement of multi-altitude LEO satellite networks, enabling efficient global connectivity and addressing communication needs in various industries and applications