- The paper introduces an SDR-based joint optimization method for user power control and IRS passive beamforming to maximize sum rate in uplink NOMA.
- It demonstrates that IRS-assisted NOMA significantly outperforms traditional OMA by enhancing spectral efficiency and scalability with more reflecting elements.
- The study outlines practical implications for next-generation wireless networks and identifies future research directions in robust IRS-assisted system designs.
Sum Rate Maximization for IRS-assisted Uplink NOMA
This paper addresses the optimization of sum rate maximization in an IRS-assisted uplink non-orthogonal multiple access (NOMA) system. The proposed work investigates the integration of intelligent reflecting surfaces (IRS) with NOMA, which has emerged as a promising technique to enhance the capacity and efficiency of wireless communications.
Study Objectives and Methodology
The primary objective of this paper is to maximize the sum rate of all users under individual power constraints in an uplink NOMA system aided by IRS. The IRS, composed of a large number of passive reflecting elements, manages the reflection patterns of incident electromagnetic waves, thereby optimizing signal propagation directions and improving communication links.
The authors formulate the considered problem as a non-convex optimization task, involving joint power control at the users and passive beamforming at the IRS. The core challenge lies in the constant modulus constraint that each reflecting element must satisfy. To tackle this, the authors utilize semidefinite relaxation (SDR) to transform the optimization problem into a more tractable form. The SDR-based approach is shown to provide a near-optimal solution to this non-convex problem.
Numerical Results and Analysis
Numerical results presented in the paper indicate that the proposed NOMA-based system significantly outperforms the traditional orthogonal multiple access (OMA)-based system in terms of sum rate. These results underscore the potential of using IRS and NOMA together in a synergistic fashion, leading to enhanced spectral efficiency and better utilization of available communication resources.
Furthermore, the paper elucidates that the sum rate grows with the number of reflecting elements, demonstrating the scalability benefits of employing IRS in wireless networks. The analysis also reveals that, unlike conventional systems, the order of decoding in uplink NOMA does not influence the sum rate, as user power always gets allocated at maximum for optimal performance.
Implications and Future Directions
The implications of this research are twofold. Practically, the integration of IRS and NOMA can be instrumental in developing next-generation wireless networks, as it enables more effective use of the wireless spectrum and enhances system capacity without incurring additional energy cost. Theoretically, the work contributes a valuable framework for future explorations into advanced resource allocation strategies for IRS-assisted systems.
Looking forward, further research could address the robustness of IRS-assisted NOMA under various real-world scenarios such as imperfect channel state information, dynamic user environments, and hardware impairments. Moreover, extending the paper to consider multi-antenna configurations and asynchronous system setups might unveil additional performance gains.
In conclusion, this work is a significant step toward understanding and exploiting the potential of IRS-assisted NOMA systems in wireless communications, offering promising pathways for enhancing network performance in upcoming 5G and beyond networks.