Modeling and optimization of multi-altitude leo satellite networks using cox point processes

Abstract

This research focuses on the modeling and optimization of multi-altitude Low Earth Orbit (LEO) satellite networks using Cox point processes to achieve efficient coverage and performance analysis. LEO satellite networks have gained attention for their potential to provide global connectivity with reduced latency and increased network capacity. Accurately modeling the spatial distribution of satellites at different altitudes and optimizing their deployment pose significant challenges. This research proposes a mathematical framework based on Cox point processes to capture the randomness and irregularity of satellite deployments. Optimization algorithms, such as genetic algorithms, are employed to determine the optimal satellite locations, altitude allocation, and network parameters. Performance analysis considers metrics such as coverage probability, signal strength, interference levels, capacity, and quality of service. The research contributes to the development of advanced modeling techniques, optimization algorithms, and performance analysis frameworks, enabling efficient coverage and performance optimization in multi-altitude LEO satellite networks. The numerical examples and discussions illustrate the effectiveness and potential of the proposed approach in enhancing the design and operation of satellite communication systems