Latency Fairness for MEC-Enabled Cell-Free Massive MIMO: ICA- and AI-Based Approaches

This letter investigates the latency minimization at the network edge in mobile edge computing (MEC)-enabled Cell-Free massive MIMO systems. We introduce a new edge computing model that integrates both task offloading and local execution. To minimize overall system latency while considering power allocation constraints, we formulate an optimization problem aimed at reducing maximum computing time. This mixed-integer non-convex problem is then reformulated into a more tractable form, which is solved using an iterative convex approximation method to achieve locally-optimal solutions. Additionally, we propose a convolutional neural network-based algorithm as an alternative solution to further improve system efficiency. Numerical results are provided to validate the theoretical framework and demonstrate the effectiveness of the proposed approaches in accelerating the data processing in MEC-enabled cell-free networks.