First-pass design of high efficiency power amplifiers using accurate large signal models
Why this work is in the frame
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Bibliographic record
Abstract
A systematic, first-pass methodology for designing high efficiency power amplifier (PA) using only large signal CAD models is presented. Detailed analysis using the model reveals significant insights into PA operation as well as the required impedance environment for high efficiency mode of operation. In particular, waveform engineering and empirical loadpull are used to determine the optimal class of operation and impedance terminations. Combined with the use of precise electromagnetic simulator in synthesizing the matching network, first pass design of a 10W, 3.3 GHz GaN inverse class F PA as well as a 2.5 GHz push-pull inverse class F PA was realized with very good agreement between simulation and measurement results. Specifically, the 3.3 GHz PA achieved 74% power added efficiency (PAE) at 3.27 GHz with 38.27 dBm output power, while the push-pull PA achieved 75% drain efficiency with 42.7 dBm output power. The linearizability of the 3.3 GHz PA is demonstrated using predistorted WiMAX modulated signals. When combined with DPD, the PA showed acceptable EVM for use in next generation wireless base stations.
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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) | 0.001 | 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