6 papers · 1 filter
An Efficient W-/D-Band Power Amplifier in a 130 nm SiGe BiCMOS Process
Han Zhou, Yu Yan, Haojie Chang +1
This paper presents a wideband power amplifier (PA) designed and implemented in Infineon Technologies' 130-nm SiGe BiCMOS process for upper W-band and lower D-band applications. A…
An Ultra-Compact Differential V-Band Power Amplifier Using EDMOS Transistors With 18.1 dBm P1dB and 21% PAE in 22nm FD-SOI CMOS
Han Zhou, Torgil Kjellberg, Haojie Chang +1
This paper presents a compact, fully differential, two-stage millimeter-wave (mm-wave) cascode power amplifier (PA) designed and implemented in a 22nm FD-SOI CMOS process (22FDX+).…
Inverse Design of Compact and Wideband Inverted Doherty Power Amplifiers Using Deep Learning
Han Zhou, Haojie Chang, David Widen +1
This paper presents a deep learning-assisted methodology for the inverse synthesis of a compact, wideband inverted Doherty power amplifier (PA). Convolutional neural networks (CNNs…
Deep-Learning-Based Pixelated Microwave Filter Design and Characterization using Electro-Optical Electric-Field Measurements
Han Zhou, Richard Bannister, Caspar Pierce +9
Traditional microwave filter design typically relies on iterative parameter tuning and predefined topologies, which limits design space and increases development time. This study u…
Deep Learning-Driven Inverse Design of Doherty Power Amplifiers Using Pixelated Combiners and Dual-State Impedance Synthesis
Han Zhou, Haojie Chang, David Widen +1
The output combiner of a Doherty power amplifier (PA) integrates load modulation, impedance matching, and phase compensation within a single network, making its design and synthesi…
Deep Learning-Driven Black-Box Doherty Power Amplifier with Pixelated Output Combiner and Extended Efficiency Range
Han Zhou, Haojie Chang, David Widen
This article presents a deep learning-driven inverse design methodology for Doherty power amplifiers (PA) with multi-port pixelated output combiner networks. A deep convolutional n…