John Wood

TL;DR: The derived model is valid for both small and large amplitude drive signals, correctly predicts even and odd harmonics through cascaded chains of functional blocks, simulates accurately load-pull behavior away from 50 /spl Omega/, and predicts adjacent channel power ratio and constellation diagrams in remarkably close agreement to the circuit model from which the behavioral model was derived.

TL;DR: This work has described neural networks for microwave modeling and design and demonstrated that neural networks are helpful in developing parametric or scalable models for passive and active microwave devices.

TL;DR: In this paper, the authors investigated the effect of increasing the size of the peaking amplifier's transistor and its conduction angle on the Doherty PA's RF performance, and the impact of the extended current profile of the peak amplifier and reduced turn-on effects on the soft-turn characteristic was deduced.

TL;DR: A new technique, called statistical neuro-space mapping, is proposed for large-signal statistical modeling of nonlinear microwave devices, which uses nonlinear mapping to overcome the accuracy limitations of the linear mapping in modeling large statistical variations among different devices.

TL;DR: This paper has generated a model of a 200-W Doherty amplifier from measured IQ data taken using a wideband code-division multiple-access excitation; the amplifier was driven from the linear regime into saturation.