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 striking an optimal balance between the total uplink power consumption and the sum SE throughout the network, under power budget and latency constraints. 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 user-centric CF-mMIMO architecture and its network-centric (both centralized and distributed) counterpart, is provided. Numerical results reveal the effectiveness of the proposed joint optimization problem, under different AP selection strategies, 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.