| Autor: |
Qiang Sun, Hai Yang, Hongwu Liu, Kyung Sup Kwak |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
ICT Express, Vol 9, Iss 6, Pp 1040-1046 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2405-9595 |
| DOI: |
10.1016/j.icte.2023.10.004 |
| Popis: |
Intelligent reflecting surfaces (IRS) can effectively improve the system performance of non-orthogonal multiple access (NOMA) systems. In this paper, we propose a Levenberg–Marquardt algorithm-based supervised learning network (LMA-SLN) to maximize the sum-rate of an IRS-assisted NOMA system. By decoupling the sum-rate maximization problem into the active and passive beamforming optimization sub-problems, we design an alternating optimization scheme to optimize the active and passive beamformings. Then, the LMA-SLN is trained with ideal channel state information (CSI) to obtain the optimized network parameters. Finally, the trained LMA-SLN is applied to optimize the active and passive beamformings without requiring CSI. The experimental results show that the proposed LMA-SLN scheme achieves the superior performance on improving the sum-rate. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
