Optimal User Pairing for Achieving Rate Fairness in Downlink NOMA Networks

TL;DR

This paper proposes an optimization method for user pairing and beamforming in downlink NOMA networks to enhance rate fairness, using a relaxed convex approximation approach that converges to a local optimum.

Contribution

It introduces a novel joint optimization framework for user pairing and beamforming in NOMA, improving fairness over traditional methods.

Findings

Achieves higher rate fairness compared to traditional solutions.

Uses sequential convex approximation for solving a complex nonconvex problem.

Converges to a locally optimal solution.

Abstract

In this paper, a downlink non-orthogonal multiple access (NOMA) network is studied. We investigate the problem of jointly optimizing user pairing and beamforming design to maximize the minimum rate among all users. The considered problem belongs to a difficult class of mixed-integer nonconvex optimization programming. We first relax the binary constraints and adopt sequential convex approximation method to solve the relaxed problem, which is guaranteed to converge at least to a locally optimal solution. Numerical results show that the proposed method attains higher rate fairness among users, compared with traditional beamforming solutions, i.e., random pairing NOMA and beamforming systems.