Design of a High-Efficiency Sequential Load Modulated Balanced Amplifier Based on Multiple Multiobjective Bayesian Optimization

作者：Jiajun Huang, Zhiming Fan, Jialin Cai · 发表于：IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 年份：2024 · DOI：10.1109/tcad.2024.3415012 · 被引用次数：9 · 研究领域：Diverse Interdisciplinary Research Innovations

In this article, an overall optimization strategy of power amplifier (PA) based on Bayesian algorithm is proposed to perform multiple multiobjective optimization design of sequential load modulated balanced amplifier (SLMBA). Specifically, by combining the programming language in MATLAB with commercial electronic design automation (EDA) software, such as advanced design system (ADS), the joint optimization process can be achieved. Then, the complex load modulation can be achieved and high-drain efficiency (DE) at various output power back-off (OBO) levels can be obtained by using the proposed overall optimization strategy, which proves the superiority of the combined optimization strategy in optimizing SLMBA compared with the optimization algorithms embedded in ADS. To verify the proposed optimization strategy, a prototype operating at 1.8–2.1 GHz was demonstrated and implemented using Gallium Nitride (GaN) transistors. A high-back-off efficiency SLMBA is simulated and measured, which the measured saturated total output power reaches 42.7–43.5 dBm with 75.8%–81.2% DE and 55%–62.5% DE at 10-dB power back-off. After that, digital pre-distortion (DPD) is implemented to further improve the linearity of the designed SLMBA with 20-MHz 5G NR signal, and good performance is achieved.