Edge User Performance Improvement by Intelligent Reflecting Surface-Assisted NOMA System

kground and Objectives: This research addresses the performance drop of edge users in downlink non-orthogonal multiple access (NOMA) systems. The challenging issue is paring the users, which becomes more critical in the case of edge users due to poor signal quality as well as the similarity of users' channel gains.Methods: To study this issue, the capabilities of intelligent reflecting surface (IRS) technology are investigated to enhance system performance by modifying the propagation environment through intelligent adjusting of the IRS components. In doing so, an optimization problem is formulated to determine the optimal user powers and phase shifts of IRS elements. The objective is to maximize the system sum rate by considering the channel gain difference constraint. Additionally, the study addresses the effect of the IRS location in the cell on system performance.Results: The proposed approach is evaluated for various scenarios and compared with benchmarks in terms of average bit error rate (BER) and sum rate. The numerical results show that IRS-assisted NOMA improves the performance of edge users and distributes resources more fairly compared to conventional NOMA.Conclusion: Simulation results demonstrate that using IRS-assisted NOMA can effectively address the issue of edge users. By modifying the channel between the BS and the edge users using IRS, the channel gain difference of the users is increased, thereby enhancing the overall system performance. Particularly, the proposed IRS-NOMA system offers a gain of about ۴ dB at a BER of ۰.۰۱ and ۳ dB at the sum rate of ۰.۱ bps/Hz compared to conventional NOMA. In addition, it was observed that the location of the IRS in the cell affects the system's performance.

کلیدواژه ها:

Non-orthogonal Multiple Access ، Intelligent Reflecting Surface ، Edge Users ، Channel Gain Difference ، Optimization Problem