2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), Oral Presentation
Date:
Presentation Topic: Heterogeneous Mean-Field Multi-Agent Reinforcement Learning for Communication Routing Selection in SAGI-Net
In this presentation, I introduce the concepts of the space-air-ground integrated network (SAGI-Net) and the challanges it faces nowadays. Then, a novel communication routing selection model for the SAGI-Net system is proposed according to the relevent communication standards. Furthurmore, a heterogeneous multi-agent reinforcement learning (HMF-MARL) framework enhanced with mean-field theory is ultilized to optimize the system.