Analysis and Optimization for Weighted Sum Rate in Energy Harvesting Cooperative NOMA Systems

TL;DR

This paper optimizes the weighted sum rate in a cooperative NOMA system with RF energy harvesting by proposing a low-complexity algorithm and analyzing high SNR approximations, demonstrating improved system performance.

Contribution

It introduces a novel low-complexity optimization algorithm for power and energy splitting coefficients in cooperative NOMA systems with energy harvesting.

Findings

Optimal power allocation and splitting coefficients improve weighted sum rate.

High SNR analysis reveals the scaling behavior of ergodic rates.

Numerical results confirm the effectiveness of the proposed scheme.

Abstract

We consider a cooperative non-orthogonal multiple access system with radio frequency energy harvesting, in which a user with good channel harvests energy from its received signal and serves as a decode-and-forward relay for enhancing the performance of a user with poor channel. We here aim at maximizing the weighted sum rate of the system by optimizing the power allocation coefficient used at the source and the power splitting coefficient used at the user with good channel. By exploiting the specific structure of the considered problem, we propose a low-complexity one-dimensional search algorithm which can provide optimal solution to the problem. As a benchmark comparison, we derive analytic expressions and simple high signal-to-noise ratio (SNR) approximations of the ergodic rates achieved at two users and their weighted sum with fixed values of the power allocation and the power splitting coefficients, from which the scaling of the weighted sum in the high SNR region is revealed. Finally, we provided numerical results to demonstrate the validity of the optimized scheme. Index Terms-Cooperative NOMA, RF-energy harvesting, weighted sum rate analysis and optimization.