| Autor: |
Jia Guo, Giovanni Crupi, Jialin Cai |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 10, Pp 89823-89834 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2022.3201348 |
| Popis: |
In this paper, a new multi-objective Bayesian optimization (BO) algorithm is applied to design a broadband gallium nitride (GaN) based Doherty power amplifier (DPA). The optimization process can be automatically implemented by combing the proposed methodology with a commercial simulation software. The performance of the DPA optimized by the proposed method is compared with those obtained with the initial designed DPA, the DPA optimized by existing BO method, and DPA optimized by the optimizers built-in using the commercial software advanced design system (ADS). The comparison results reveal that the DPA designed with the proposed method can achieve better performance with less optimization time than other optimization methods. The measured results show that the optimized DPA with the proposed method achieves a 9-dB back-off efficiency of 44.6%-65% and a saturated efficiency of 60.5%-78% from 2.0 GHz to 2.6 GHz, with saturated output power varying from 43.8 dBm to 45.2 dBm. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
