Efficient Power Control for Satellite-Borne Batteries Using Q-Learning in Low-Earth-Orbit Satellite Constellations

Recently, changes in the relationship between satellite communication networks and ground communication networks have led to an increase in the demands imposed on satellite communication networks. In this category of networks, the low earth orbit (LEO) satellite constellations, which cover the entire surface of Earth through cooperation among many small satellites in low orbit, are currently attracting attention. LEO satellites consume power when communicating with terrestrial terminals. However, in the absence of solar light, these satellites must operate using battery energy only. The power consumption during these periods places a heavy load on the satellite battery and can shorten their lifetimes. This entails a significant cost for satellite communication networks. In this letter, we apply Q-learning to the power allocation problem in satellite-to-ground communication using LEO satellites. Using this method, we can extend the lifetime of the LEO satellite battery by sharing the workload of overworked satellites with adjacent satellites with a lower load. The effects of the proposed method on the battery lifetime of the LEO satellites are verified.