Low-Complexity Dynamic Resource Scheduling for Downlink MC-NOMA Over Fading Channels

TL;DR

This paper proposes a low-complexity, online resource scheduling algorithm for downlink MC-NOMA systems over fading channels, optimizing sum rate with QoS constraints, suitable for practical implementation.

Contribution

It introduces a novel low-complexity heuristic joint subchannel and power allocation algorithm, Joint-SAPA-LCC, integrated into an opportunistic scheduling framework for real-time systems.

Findings

Joint-SAPA-LCC achieves performance comparable to existing algorithms.

The proposed algorithm significantly reduces computational complexity.

The scheduling method effectively satisfies QoS constraints in simulations.

Abstract

In this paper, we investigate dynamic resource scheduling (i.e., joint user, subchannel, and power scheduling) for downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems over time-varying fading channels. Specifically, we address the weighted average sum rate maximization problem with quality-of-service (QoS) constraints. In particular, to facilitate fast resource scheduling, we focus on developing a very low-complexity algorithm. To this end, by leveraging Lagrangian duality and the stochastic optimization theory, we first develop an opportunistic MC-NOMA scheduling algorithm whereby the original problem is decomposed into a series of subproblems, one for each time slot. Accordingly, resource scheduling works in an online manner by solving one subproblem per time slot, making it more applicable to practical systems. Then, we further develop a heuristic joint subchannel assignment and power allocation (Joint-SAPA) algorithm with very low computational complexity, called Joint-SAPA-LCC, that solves each subproblem. Finally, through simulation, we show that our Joint-SAPA-LCC algorithm provides good performance comparable to the existing Joint-SAPA algorithms despite requiring much lower computational complexity. We also demonstrate that our opportunistic MC-NOMA scheduling algorithm in which the Joint-SAPA-LCC algorithm is embedded works well while satisfying given QoS requirements.