Federated deep reinforcement learning for prediction-based network slice mobility in 6g mobile networks

HIGHLIGHTS

• What: To cope with these challenges, in this paper, the authors design a general network architecture for NSM in 6G networks, which considers the decentralized core network to be realized by the VNFs deployed at edge servers (ESs) and the RAN built by the VNFs under the Open-RAN paradigm. The problem is formulated to maximize the long-term system profit of MNOs, and the authors propose a prediction-based federated DRL (FDRL) framework that learns users` requests and position information to solve this problem. The authors aim to explore prediction-based NSM that utilizes system information . . .
  

   

  

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