High efficiency digitally linearized GaN based power amplifier for 3G applications
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Bibliographic record
Abstract
In this paper, a high efficiency GaN based power amplifier is designed using multi-harmonics load pull measurements. A load matching network that independently controls the load impedance at the fundamental, second and third harmonic frequencies is used for straightforward implementation. The continuously driven single-ended deep class AB biased power amplifier achieves a peak power added efficiency of 68% at saturation. It is found that the designed power amplifier exhibit highly non linear characteristics with 7 dB gain compression at saturation. Digital predistortion based linearizer is used to improve the linearity performance of the power amplifier under a WCDMA excitation (PAPR=9.8 dB). At a 10 dB output power back-off, 21% power added efficiency was measured along with 53 dBc adjacent channel leakage ratio.
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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