High-Efficiency Moderate-Power Amplifier Using Packaged GaN Transistor With Improved Average PAE and Gain for Batteryless IoT Applications
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Bibliographic record
Abstract
One of the fundamental problems in power amplifier (PA) design is the mismatch between the optimum loads for maximum output power and maximum efficiency. This work demonstrates that a GaN transistor of choice can reduce such mismatch when operating at the minimum input RF power required ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\text {in}}$ </tex-math></inline-formula> ) to obtain its maximum output power. Furthermore, this work investigates the average power-added efficiency (PAE) degradation caused by the baseband terminations for high-efficient switch-mode class-E PAs. Our results show that the average PAE degradation mechanism of class-E PAs is similar to that of class-B ones, but some class-E solutions are more susceptible to the driving signal’s bandwidth. To clarify that, two class-E PAs were implemented using commercial package GaN transistors based on two different modes from the continuum of class-E solutions. Despite being driven by half of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\text {in}}$ </tex-math></inline-formula> typically employed by designers, the PAs have achieved a gain almost 3 dB higher than the state-of-the-art and excellent efficiency controlling only the second harmonic. Based on the obtained results, the proposed design strategy is believed to have a promising potential for developing high-efficiency simultaneous wireless information and power transmission (SWIPT) base stations for batteryless Internet of Things (IoT).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it