DEVELOPMENT AND OPTIMIZATION OF ML BASED COMPREHENSIVE MODELLING FRAMEWORK FOR GAN HEMTS
Loading...
Date
2024-04-24
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
Radio Frequency (RF) Power Amplifier (PA) is one of the most pivotal constituents of any wireless transceivers. However, continual advancements and ever-increasing complexity in the wireless communication technologies demand frequent innovations in the design of RFPAs. The quality of the designed RFPAs are generally evaluated based around two basic figures of merits namely efficiency and linearity. Thus, the RFPAs should provide maximum power and efficiency while maintaining highly linear operation. In literature, two primary PA design mechanisms, namely measurement- and modeling-based techniques have been extensively utilized. Each class of technique has pronounced merits, limitations and applications. However, owing to the seamless integration ability of the modeling-based techniques with Computer-Aided Design (CAD) tools, they are increasingly becoming more popular. The design and innovation in RFPAs are excessively contingent on the measurement facilities and the Large Signal Models (LSMs) of transistor devices. At present, Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) technology is regarded as an optimal microwave transistor technology for the design of RFPAs in advanced RF/microwave and high power switching applications. This is due to their attributes namely high energy bandgap, high saturation velocity, high electron mobility, exceptional thermal behavior and high breakdown field. Furthermore, GaN HEMTs manifest high power density, thus a smaller size device can be used to sustain a high power demand.
Description
Keywords
GaN HEMTs, ML, Behavioral modelling, Small-Signal Modelling, Large-Signal Modelling, Joint EC-BM, GaN based class-F PA, Type of access: Restricted
Citation
Husain, S. (2024) Development and Optimization of ML Based Comprehensive Modelling Framework for GaN HEMTs. Nazarbayev University School of Engineering and Digital Sciences.