Performance of Proportional Fair Scheduling for Downlink Non-Orthogonal Multiple Access Systems

TL;DR

This paper provides the first analytical performance analysis of proportional fair scheduling in downlink NOMA systems, deriving optimal power allocation and validating results through simulations.

Contribution

It introduces a closed-form solution for PFS in NOMA, along with a low-complexity algorithm and an analytical model for throughput estimation.

Findings

Analytical upper bound for PFS performance in NOMA

High accuracy of data rate estimation using the analytical model

Impact of imperfect channel information on estimation accuracy

Abstract

In this paper, we present the first analytical solution for performance analysis of proportional fair scheduling (PFS) in downlink non-orthogonal multiple access (NOMA) systems. Assuming an ideal NOMA system with an arbitrary number of multiplexed users, we derive a closed-form solution of the optimal power allocation for PFS and design a low-complexity algorithm for joint power allocation and user set selection. We develop an analytical model to analyze the throughput performance of this optimal solution based on stochastic channel modeling. Our analytical performance is proved to be the upper bound for PFS and is used to estimate user data rates and overall throughput in practical NOMA systems. We conduct system-level simulations to evaluate the accuracy of our data rate estimation. The simulation results verify our analysis on the upper bound of PFS performance in NOMA and confirm that using the analytical performance for data rate estimation guarantees high accuracy. The impact of partial and imperfect channel information on the estimation performance is investigated as well.