This work presents a new artificial neural network (ANN) model formulation for RF high-power transistors which includes the S-parameters of the active device. This improves the small-signal extrapolation capability, and the OFF-state impedance approximation, making it suitable for Doherty power amplifier (DPA) design. This extrapolation capability plays a key role in the correct Doherty load modulation prediction, since, at low power levels, the peaking PA is subjected to active loads that cannot be synthetized with a passive load-pull system, forcing the model to extrapolate. Thus, the proposed model formulation is able to solve the issues that are normally observed when ANN-based models are used in complex PA architectures as the Doherty PA. To validate the proposed behavioral model, a 700-W asymmetrical LDMOS DPA, centered at 1.84 GHz, was simulated and measured.

中文翻译：

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适用于Doherty PA设计的新型晶体管行为模型公式

这项工作为RF大功率晶体管提出了一种新的人工神经网络（ANN）模型公式，其中包括有源器件的S参数。这提高了小信号外推能力和OFF状态下的阻抗近似值，使其适用于Doherty功率放大器（DPA）设计。这种外推功能在正确的Doherty负载调制预测中起着关键作用，因为在低功率水平下，峰值PA承受的有源负载无法与无源负载牵引系统进行合成，从而迫使模型进行外推。因此，当在复杂的PA体系结构中使用基于ANN的模型作为Doherty PA时，所提出的模型公式能够解决通常观察到的问题。为了验证建议的行为模型，以1.84 GHz为中心的700W非对称LDMOS DPA，