Gaussian processes regression for optimizing harmonic impedance trajectories in continuous class-F power amplifier design

This paper proposes an advanced optimization-oriented strategy to design a continuous Class-F power amplifier (PA) using Gaussian processes regression (GPR). Optimal harmonic impedance trajectories for achieving high efficiency are obtained at a Cree CHG40010 package plane. GPR is exploited to optimize matching networks for fitting the desired trajectories of harmonic impedances. By combining GPR with Agilent´s Advanced Design System (ADS), the optimization procedure runs automatically and predicts optimal design parameters which match well with the expected harmonic impedance trajectories. Measured results show that greater than 60% efficiency is attained over a 50% bandwidth from 1.5 to 2.5 GHz. The output power is larger than 40.2 dBm with gain varying from 13.2 to 15.4 dB across the band.