Optimizing Resource Allocation for Multi-Beam Satellites Using Genetic Algorithm Variations

The increasing demand for satellite communication capacity poses challenges in efficiently managing the limited frequency spectrum. This study explores dynamic resource allocation strategies for multi-beam satellite communication systems, focusing on optimizing communication delay, packet loss, and power consumption. We conduct a detailed comparative analysis of various Genetic Algorithm (GA) variants, such as NSGA-II and SPEA2, to address the multi-objective optimization problem inherent in resource allocation. Experiments demonstrate NSGA-II's superior ability to reduce delay and packet loss. In contrast, SPEA2 shows greater power efficiency, which is critical for satellite lifespan. This research advances multi-beam satellite resource management, offering an adaptable optimization technique balancing key performance factors like latency, loss, and power usage.