Power Allocation for IRS-aided Two-way Decode-and-Forward Relay Wireless Network

TL;DR

This paper proposes three power allocation strategies for IRS-aided two-way relay networks, significantly improving sum rate performance over equal power allocation, with gains up to 45.2%.

Contribution

It introduces three novel power allocation schemes tailored for IRS-assisted two-way relay networks, optimizing sum rate and fairness.

Findings

Max-SR method optimizes joint power factors for higher sum rate.

Max-Min-SR enhances fairness by maximizing minimum sum rate.

Max-SR-RC achieves up to 45.2% gain over equal power allocation.

Abstract

In this paper, an intelligent reflecting surface (IRS)-aided two-way decode-and-forward (DF) relay wireless network is considered, where two users exchange information via IRS and DF relay. To enhance the sum rate performance, three power allocation (PA) strategies are proposed. Firstly, a method of maximizing sum rate (Max-SR) is proposed to jointly optimize the PA factors of user U1, user U2 and relay station (RS). To further improve the sum rate performance, two high-performance schemes, namely maximizing minimum sum rate (Max-Min-SR) and maximizing sum rate with rate constraint (Max-SR-RC), are presented. Simulation results show that the proposed three methods outperform the equal power allocation (EPA) method in terms of sum rate performance. In particular, the highest performance gain achieved by Max-SR-RC method is up to 45.2% over EPA. Furthermore, it is verified that the total power and random shadow variable X{\sigma} have a substantial impact on the sum rate performance.