A Time- and Energy-Efficient Massive MIMO-NOMA MEC Offloading Technique: A Distributed ADMM Approach

Mobile edge computing (MEC) is an emerging platform that enables mobile devices to offload computation intensive tasks to the edge servers co-located with base stations (BSs) at the network edge for enhanced computation capabilities and low latency. This paper investigates the computation offloading problem in next-generation massive multiple-input multiple-output (M-MIMO) non-orthogonal multiple access (NOMA) MEC networks using a distributed alternating direction method of multipliers (ADMM) approach. Specifically, we develop a novel ADMM-based offloading algorithm to optimize latency and increase energy efficiency over next-generation mobile networks in a multiuser M-MIMO NOMA configuration. Simulation results demonstrate that the proposed offloading scheme significantly improves the system performance.