  This paper considers a mobile edge computing-enabled cell-free massive MIMO
wireless network. 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 latency constraints, while
simultaneously also maximizing the minimum SE throughout the network. Since the
considered problem is non-convex, an iterative algorithm based on sequential
convex programming is devised. A detailed performance comparison between the
proposed distributed architecture and its co-located counterpart, based on a
multi-cell massive MIMO deployment, is provided. Numerical results reveal the
natural suitability of cell-free massive MIMO 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.
