On an MADDPG-based Task Scheduling Strategy in Heterogeneous Low Earth Orbit Satellite Networks

With the rise of sixth-generation (6 G) and the development of non-terrestrial networks (NTNs), low Earth orbit (LEO) satellites play a key role in global connectivity, especially in remote areas. However, due to the limited communication and computing resources of satellites, efficiently utilizing these capabilities has become an urgent problem. To address this, we propose a multi-satellite collaborative computation offloading framework for LEO satellite networks. We divide the satellites into communication satellites and computation satellites according to their resource status, and construct a cooperative processing model that supports cross-satellite task offloading and distributed execution. Meanwhile, we introduce the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to achieve the access selection of ground terminals and the scheduling of computing tasks. Simulation results show that the method can effectively shorten the task completion time, improve the task success rate, and significantly enhance the resource utilization efficiency.