Computation Efficiency Maximization in OFDMA-Based Mobile Edge Computing Networks

TL;DR

This paper proposes a novel resource allocation scheme for OFDMA-based mobile edge computing networks that maximizes computation efficiency, providing closed-form solutions and an iterative algorithm, outperforming benchmark schemes.

Contribution

It introduces a new optimization framework for computation efficiency maximization in MEC networks considering partial and binary offloading modes.

Findings

Proposed resource allocation scheme outperforms benchmarks in simulations.

Closed-form expressions for optimal subchannel and power allocation are derived.

An efficient iterative algorithm effectively solves the non-convex optimization problem.

Abstract

Computation-efficient resource allocation strategies are of crucial importance in mobile edge computing networks. However, few works have focused on this issue. In this letter, weighted sum computation efficiency (CE) maximization problems are formulated in a mobile edge computing (MEC) network with orthogonal frequency division multiple access (OFDMA). Both partial offloading mode and binary offloading mode are considered. The closed-form expressions for the optimal subchannel and power allocation schemes are derived. In order to address the intractable non-convex weighted sum-of ratio problems, an efficiently iterative algorithm is proposed. Simulation results demonstrate that the CE achieved by our proposed resource allocation scheme is better than that obtained by the benchmark schemes.