Efficiency enhancement of a WiMAX switching mode GaN power amplifier through layout optimization of distributed harmonic matching networks
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Bibliographic record
Abstract
This work proposes a method to enhance the efficiency of a WiMAX switching mode GaN power amplifier through the layout optimization of harmonic matching networks. In the first step, the optimal termination conditions for the inverse class F power amplifier are extracted through load-pull measurement. Afterward, the loss in the multi-harmonic output matching network is minimized through layout optimization in order to improve the efficiency of the PA. The fabrication of an inverse class F for WiMAX applications following the optimization procedure demonstrates that the power added efficiency is improved by 5% when minimizing the loss in the output matching network compared to a non-optimized circuit. The fabricated PA power added efficiency reaches 71.2% after loss minimization.
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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 | 0.000 | 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