The Promising Marriage of Mobile Edge Computing and Cell-Free Massive MIMO

TL;DR

This paper explores integrating mobile edge computing with cell-free massive MIMO to optimize resource allocation, reduce power consumption, and improve latency in wireless networks, demonstrating significant performance benefits over traditional setups.

Contribution

It introduces an optimization framework for joint uplink power and computational resource allocation in cell-free massive MIMO networks, employing a novel iterative algorithm for non-convex problems.

Findings

Reduced user transmit power and energy consumption.

Lower offloading latency.

Enhanced resource utilization in cell-free massive MIMO.

Abstract

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.