An Analysis of Resource Allocation and User Association Strategies in Space-Air-Ground Integrated Networks

Space-Air-Ground-Integrated Networks (SAGIN) enable seamless data connectivity for applications such as smart transport, healthcare, smart cities, and disaster response through the coordinated use of low-earth orbit (LEO) satellites, base stations mounted with uncrewed aerial vehicles (UAV), and terrestrial infrastructure. This paper provides a detailed analysis of resource management frameworks, reviews the literature, and evaluates key methods such as alternating optimization (AO), damped iterative water filling (DIWF), and genetic algorithms (GA) for resource allocation. MATLAB simulation results benchmark these algorithms across 10,000 trials, demonstrating robust, fair, and low-latency resource allocation. In addition, this paper also analyzes strategies for user association with terrestrial and aerial base stations during emergencies and network overloads. The main contributions include a comparative assessment of resource allocation strategies in SAGIN and an in-depth analysis of user association policies for emergency scenarios. The study provides guidance for designing resilient and efficient next-generation networks. Potential future research directions include investigating satellite handover and multi-domain orchestration for SAGIN deployments.