Delay-aware Joint Resource Allocation in Cell-Free Mobile Edge Computing

This paper investigates a joint resource allocation problem in cell-free mobile edge computing system which intends to minimize the number of users subjected to outage, due to failure to meet user-specific delay constraints. Accordingly, the number of APs serving each user, i.e., dynamic cluster size, uplink transmit power and computing resources at the edge server are jointly optimized based on deep reinforcement learning (DRL) algorithm.