Joint Optimization of Uplink Power and Computational Resources in Mobile Edge Computing-Enabled Cell-Free Massive MIMO

The coupling of cell-free massive MIMO (CF-mMIMO) with Mobile Edge Computing (MEC) is investigated in this paper. A MEC-enabled CF-mMIMO architecture implementing a distributed user-centric approach both from the radio and the computational resource allocation perspective is proposed. An optimization problem for the joint allocation of uplink powers and remote computational resources is formulated, aimed at minimizing the total uplink power consumption under power budget and latency constraints, while simultaneously maximizing the minimum SE throughout the network. In order to efficiently solve such a challenging non-convex problem, an iterative algorithm based on sequential convex programming is proposed, along with two approaches to priory assess the problem feasibility. Finally, a detailed performance comparison between the proposed MEC-enabled CF-mMIMO architecture and its cellular counterpart is provided. Numerical results reveal the effectiveness of the proposed joint optimization problem, and the natural suitability of CF-mMIMO in supporting computation-offloading applications with benefits over users' transmit power and energy consumption, the offloading latency experienced, and the total amount of allocated remote computational resources.