Al-Obiedollah, H., Salameh, H.B., Hayajneh, A.M. et al. (1 more author) (2025) Throughput-Fairness Trade-off Optimization for IRS NOMA Systems. IEEE Access. ISSN 2169-3536
Abstract
Improving the overall throughput (i.e., sum rate) of a communication system while maintaining fairness between users has recently been identified as a crucial requirement for beyond fifth-generation communication systems. However, these performance metrics, i.e., sum rate and fairness, are conflicting. Specifically, maximizing the overall sum rate is achieved at the cost of per-user throughput degradation and vice versa. Such a conflicting nature has an undesirable impact on fairness between users, especially those with weaker channel conditions. To deal with such an issue, this paper proposes a multi-objective optimization (MOO) resource allocation technique for intelligent reflecting surfaces (IRS)-assisted multicarrier non-orthogonal multiple access (NOMA) systems. The proposed MOO framework aims to balance overall throughput and fairness between users, where the fairness index (FI) is selected as a quantitative measure of fairness. Unlike single-objective optimization (SOO) problems, traditional approaches cannot solve the formulated MOO framework. Consequently, the weighted max-min (WMM) method is deployed to transform the MOO problem into a conventional SOO one, showing that the WMM method can achieve a set of Pareto-optimal solutions (i.e., dominant solutions). Consequently, we use the sequential convex approximation to evaluate the optimization parameters, namely the allocated power levels and the phase-reflecting coefficients of the IRS units. A set of simulation results is carried out to demonstrate the superiority of the proposed fairness-throughput resource allocation technique. In addition, the performance of the proposed WMM method is compared with a benchmark method, namely the weighted sum method (WSM).
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Keywords: | IRS, Multi-carrier NOMA, dominant solutions, multi-objective, weighted max-min (WMM) method |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 Mar 2025 09:35 |
Last Modified: | 12 Mar 2025 09:49 |
Published Version: | https://ieeexplore.ieee.org/document/10856097 |
Status: | Published online |
Publisher: | IEEE |
Identification Number: | 10.1109/access.2025.3535839 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224306 |