A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access

TL;DR

This paper proposes a max-min task offloading algorithm for mobile edge computing using NOMA, improving performance over OMA in delay-sensitive scenarios by maximizing the minimum offloaded bits.

Contribution

It introduces a novel algorithm for non-convex optimization in NOMA-based MEC, enhancing task offloading efficiency and fairness.

Findings

NOMA outperforms OMA in MEC delay scenarios.

The proposed algorithm converges efficiently.

NOMA-based MEC benefits delay-sensitive applications.

Abstract

To mitigate computational power gap between the network core and edges, mobile edge computing (MEC) is poised to play a fundamental role in future generations of wireless networks. In this letter, we consider a non-orthogonal multiple access (NOMA) transmission model to maximize the worst task to be offloaded among all users to the network edge server. A provably convergent and efficient algorithm is developed to solve the considered non-convex optimization problem for maximizing the minimum number of offloaded bits in a multi-user NOMAMEC system. Compared to the approach of optimized orthogonal multiple access (OMA), for given MEC delay, power and energy limits, the NOMA-based system considerably outperforms its OMA-based counterpart in MEC settings. Numerical results demonstrate that the proposed algorithm for NOMA-based MEC is particularly useful for delay sensitive applications.