  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. A multi-objective
optimization problem (MOOP) for the joint allocation of radio and remote
computational resources is formulated, aimed at striking an optimal balance
between total uplink power minimization and sum spectral efficiency
maximization, under resource budget and latency constraints. In order to solve
such a challenging non-convex problem, we convert the MOOP to an equivalent
single-objective optimization problem (SOOP) through the weighted sum method
and propose an iterative algorithm based on alternating optimization and
sequential convex programming, along with an alternative heuristic resource
allocation for distributed networks. Finally, we provide a detailed performance
comparison between the proposed MEC-enabled CF-mMIMO architecture with its
co-located counterpart, and its small-cell implementation. Numerical results
reveal the effectiveness of the proposed resource allocation scheme, under
different access point selection strategies, and the natural suitability of
CF-mMIMO in supporting computation-offloading applications with benefits over
users' transmit power and energy consumption, the effective latency
experienced, and the computation offloading efficiency.
