A 5G FR1 43.5 dBm GaN Hybrid Doherty Power Amplifier with Dynamic Auxiliary Gate Voltage for Enhanced Gain at Saturation

This paper presents a dynamic gate bias (DGB) approach to improve the linearity of a Doherty Power Amplifier (DPA) designed for 5G FR1 applications, utilizing Gallium Nitride (GaN) transistors. The amplifier adopts a hybrid implementation on a printed circuit board (PCB), integrating transmission lines (TLs) and lumped discrete elements to optimize performance. Although the Doherty architecture is known for its efficiency advantages under back-off conditions, it encounters challenges such as gain compression at saturation of the main amplifier. To address this limitation, a dynamic gate biasing is used, enhancing the linearity and mitigating gain compression. The DPA fabricated on a Taconic RF-35 substrate with a dielectric constant of 3.5. The amplifier’s performance is evaluated through both simulations and measurements. Key metrics, including gain, efficiency, and output power, are assessed for both DPA with standard gate bias and DPA with DGB for auxiliary amplifier, with measurement results demonstrating a peak drain efficiency of 55%, an output power of 43.5 dBm, average gain of 13 dB and a 2 dB improvement in gain compression in case of DGB approach. These outcomes confirm the DPA’s suitability for high-linearity, high-efficiency applications within the 5G FR1.

Authors

Institutions

Publication Details

Published
2025-03-17
DOI
https://doi.org/10.23919/gemic64734.2025.10979016
Primary Topic
Advanced Power Amplifier Design
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A 5G FR1 43.5 dBm GaN Hybrid Doherty Power Amplifier with Dynamic Auxiliary Gate Voltage for Enhanced Gain at Saturation

Christian Fager, Jorge Julián Moreno Rubio, Gregor Lasser, Abdolhamid Noori
Advanced Power Amplifier Design
article

A 5G FR1 43.5 dBm GaN Hybrid Doherty Power Amplifier with Dynamic Auxiliary Gate Voltage for Enhanced Gain at Saturation

Christian Fager, Jorge Julián Moreno Rubio, Gregor Lasser, Abdolhamid Noori
article en

Abstract

This paper presents a dynamic gate bias (DGB) approach to improve the linearity of a Doherty Power Amplifier (DPA) designed for 5G FR1 applications, utilizing Gallium Nitride (GaN) transistors. The amplifier adopts a hybrid implementation on a printed circuit board (PCB), integrating transmission lines (TLs) and lumped discrete elements to optimize performance. Although the Doherty architecture is known for its efficiency advantages under back-off conditions, it encounters challenges such as gain compression at saturation of the main amplifier. To address this limitation, a dynamic gate biasing is used, enhancing the linearity and mitigating gain compression. The DPA fabricated on a Taconic RF-35 substrate with a dielectric constant of 3.5. The amplifier’s performance is evaluated through both simulations and measurements. Key metrics, including gain, efficiency, and output power, are assessed for both DPA with standard gate bias and DPA with DGB for auxiliary amplifier, with measurement results demonstrating a peak drain efficiency of 55%, an output power of 43.5 dBm, average gain of 13 dB and a 2 dB improvement in gain compression in case of DGB approach. These outcomes confirm the DPA’s suitability for high-linearity, high-efficiency applications within the 5G FR1.

Silicon Austria Labs (Austria) (AT), Chalmers University of Technology (SE)
Affordable and clean energy
Openalex Percentile: Top 92%
Advanced Power Amplifier Design
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.