Joint Communication and Computing Resource Allocation over Cell-Free Massive MIMO-enabled Mobile Edge Network: A Deep Reinforcement Learning-based Approach

Abstract

We present a cell-free massive MIMO-enabled mo-edge network with the aim of meeting the stringent rements of the newly introduced multimedia services. For considered framework, we propose a distributed deep-orcement learning (DRL)-based joint communication and uting resource allocation wherein each user is implemented n independent agent to make joint resource allocation ion relying on local observation only. The simulation results nstrate that the agents learn robust policies that reduce gy consumption while attaining the ultra-low delay requires of the advanced services.