Mobile Edge Computing Tasking Offloading Strategy in Cell-Free Massive MIMO with Graph Neural Network

Abstract

Combining cell-free massive multiple-input multiple-output (CF-mMIMO) and mobile edge computing (MEC) facilitates the processing of compute-intensive and latency-sensitive tasks in the distributed IoT. For MEC-enabled CF-mMIMO system, this paper designs a task offloading strategy for local computing and multi-access points (APs) collaboration. Under energy constraints, we aim to minimize the latency of computing offloading. According to the different data size of each user and the service of APs, the graph neural network method is adopted to deal with the link prediction between the user and APs.