An Artificial-Intelligence (AI) Assisted Mm-Wave Doherty Power Amplifier with Rapid Mixed-Mode In-Field Performance Optimization
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Date
2019Type
- Conference Paper
ETH Bibliography
no
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Abstract
This paper presents an artificial-intelligence (AI) assisted “intelligent” millimeter-wave (mm-wave) Doherty power amplifier (PA) architecture that achieves robust adaptive operation over antenna VSWR. A built-in machine-learning core utilizes online function estimation and reinforcement learning algorithms for dynamic Doherty performance optimization. As a proof of concept, a 3-bit mixed-signal Doherty PA (MSDPA) at 28GHz is used as a hardware platform to demonstrate the performance improvement with the AI core. Over 2:1 antenna VSWR variation, simulations using extracted Doherty PA schematic show up-to 4.9 dBm P 1dB improvement and up-to 7% PAE improvement at P 1dB . Show more
Publication status
publishedExternal links
Book title
2019 IEEE MTT-S International Microwave Conference on Hardware and Systems for 5G and Beyond (IMC-5G)Pages / Article No.
Publisher
IEEEEvent
Subject
Artificial intelligence (AI); Doherty; Efficiency; Linearity; Machine learning (ML); Mixed-signal; Power amplifier (PA); Power back-off (PBO); Reinforcement learningOrganisational unit
09757 - Wang, Hua / Wang, Hua
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ETH Bibliography
no
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