AI-Driven Cooperative Mechanisms for Edge-Intelligent Communication Systems

As edge-intelligent communication systems are increasingly deployed in complex scenarios (e.g. unmanned aerial vehicles, UAVs) there is a growing demand for more efficient, secure operations and greater flexible cooperative capabilities. This research aims to meet these important needs. In such systems, diverse devices must collaborate using cooperative mechanisms to handle data processing and task execution collectively, while also satisfying strict latency and privacy constraints. In the aerospace environment, satellite constellations need to coordinate data exchange across vast orbital distances. The Space-Air-Ground Integrated Networks (SAGIN) must achieve seamless connectivity among aircraft, UAVs, and ground stations. Consequently, the aerospace environment presents unprecedented challenges for communication systems. The aerospace environment features unique limitations that differ from those of ground networks. High mobility causes rapid signal loss and frequent switching. The sparse placement of space and air nodes worsens connection instability. Energy shortages exacerbate this problem, as the limited power supply restricts satellites and drones from operating fully. At the same time, the aerospace system demands an extremely high level of reliability and safety, functioning under conditions with nearly zero failure tolerance. In this context, this study conducted a systematic review of the collaborative mechanisms driven by artificial intelligence (AI) and constructed a classification system covering five categories: data collaboration, model collaboration, reasoning collaboration, decision collaboration, and resource collaboration. By clarifying their roles, performance benefits, and application relevance, we aim to create a clear framework that applies not only to general 5G/6G edge intelligent communication but also suits the aerospace network.