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Abstract

Low Earth Orbit (LEO) CubeSat constellations are becoming increasingly important for Earth observation, environmental monitoring, scientific missions, disaster management, and global connectivity. However, CubeSats operate under severe constraints in terms of power availability, onboard processing capability, communication bandwidth, and contact opportunities with ground stations. Traditional CubeSat communication systems rely on fixed communication parameters and static protocol configurations. Such systems are unable to adapt efficiently to changing channel conditions, fluctuating energy levels, intermittent connectivity, and varying mission priorities. Modern satellite missions generate heterogeneous data streams, including telemetry, control commands, scientific measurements, and payload data. These data types do not have the same importance, urgency, or reliability requirements. Therefore, an intelligent mechanism is required to prioritize information and dynamically select the most appropriate communication strategy according to mission requirements and available resources. In nutshell, the work focuses on ""developing the decision-making layer that will enable future adaptive communication protocols to make autonomous and mission-aware transmission decisions.