A Comprehensive Overview of the Temperature-Dependent Modeling of the High-Power GaN HEMT Technology Using mm-Wave Scattering Parameter Measurements

Abstract

The gallium-nitride (GaN) high electron-mobility transistor (HEMT) technology has emerged as an attractive candidate for high-frequency, high-power, and high-temperature applications due to the unique physical characteristics of the GaN material. Over the years, much effort has been spent on measurement-based modeling since accurate models are essential for allowing the use of this advanced transistor technology at its best. The present analysis is focused on the modeling of the scattering (S-) parameter measurements for a 0.25 μm GaN HEMT on silicon carbide (SiC) substrate at extreme operating conditions: a large gate width (i.e., the transistor is based on an interdigitated layout consisting of ten fingers, each with a length of 150 μm, resulting in a total gate periphery of 1.5 mm), a high ambient temperature (i.e., from 35 °C up to 200 °C with a step of 55 °C), a high dissipated power (i.e., 5.1 W at 35 °C), and a high frequency in the millimeter-wave range (i.e., from 200 MHz up to 65 GHz with a step of 200 MHz). Three different modeling approaches are investigated: the equivalent-circuit model, artificial neural networks (ANNs), and gated recurrent units (GRUs). As is shown, each modeling approach has its pros and cons that need to be considered, depending on the target performance and their specifications. This implies that an appropriate selection of the transistor modeling approach should be based on discerning and prioritizing the key features that are indeed the most important for a given application.

Incorporating DC bias voltage in poly‐harmonic distortion modeling for RF power GaN transistors

“…In particular, GaN-based power transistors have received a widespread attention for developing RFPAs due to their ability to generate high power densities. [4][5][6][7][8][9][10][11][12][13] Several transistor models are available for power transistors, including physics-based models, [14][15][16] equivalent circuit models, [17][18][19][20][21][22][23] and behavioral models. [24][25][26][27][28][29][30][31] Typically, the first two models are used for nonlinear circuit designs, as they provide acceptable results when devices are subjected to extreme operating conditions.…”

Beamsteering-Aware Power Allocation for Cache-Assisted NOMA mmWave Vehicular Networks

“…As another pivotal technology in the communication domain, millimeter-wave (mmWave) communication is expected to meet the high data rate requirements of 5G networks and beyond [4][5][6]. Despite its potential to accommodate multigigabit data rates through the vast available bandwidth in the mmWave frequency band [7], challenges persist due to severe path loss and sensitivity to blockage characteristics of mmWave signals. These issues underscore the necessity for sophisticated beamforming techniques and multiantenna systems to ensure reliable communication [8].…”