Transmission Delay Minimization for NOMA-Based F-RANs

TL;DR

This paper introduces a NOMA-based low-delay framework for fog radio access networks, optimizing user association, cache placement, and power allocation to minimize transmission delay, outperforming traditional OMA systems.

Contribution

It proposes a novel NOMA-based F-RAN framework with an AO algorithm for joint optimization, addressing a complex delay minimization problem.

Findings

AO algorithm balances performance and efficiency

NOMA-based F-RANs reduce average transmission delay

Framework outperforms OMA-based systems in simulations

Abstract

A novel non-orthogonal multiple access (NOMA) based low-delay service framework is proposed for fog radio access networks (F-RANs). Fog access points (FAPs) leverage NOMA for local delivery of cached content, while the cloud access point employs NOMA to simultaneously push content to FAPs and directly serve users. Based on this model, a delay minimization problem is formulated by jointly optimizing user association, cache placement, and power allocation. To address this non-convex mixed-integer nonlinear programming problem, an alternating optimization (AO) algorithm is developed, which decomposes the original problem into two subproblems, namely joint user association and cache placement, and power allocation. In particular, a low-complexity algorithm is designed to optimizing the user association and cache placement strategy using the McCormick envelope theory and Lagrangian partial relaxation. The power allocation is optimized by invoking the successive convex approximation. Simulation results reveal that: 1) the proposed AO-based algorithm effectively balances between the achieved performance and computational efficiency, and 2) the proposed NOMA-based F-RANs framework significantly outperforms orthogonal multiple access-based F-RANs systems in terms of average transmission delay in different scenarios.