Low-Latency Federated Reinforcement Learning-Based Resource Allocation in Converged Access Networks

We propose a federated reinforcement learning (FedRL) solution to innovate resource allocation in converged access networks. FedRL lowers network latency with reinforcement-learnt bandwidth decision and achieves fast learning with federated learning efforts.