Efficiency vs. linearity trade-offs in outphasing power amplifiers
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Bibliographic record
Abstract
This paper presents an investigation of the trade-offs between efficiency improvement and linearity of the outphasing power amplifier. Simulations and experimental measurements are carried out to validate the theoretical analysis. Two types of digital modulation signals are used, namely 16-QAM and 64-QAM. The impact of the stub length on the efficiency and linearity is studied for both signals. Different Chireix combiners having stubs of varying electrical lengths combiners are fabricated for experimental validation of the theoretical results. The work shows that a trade-off can be made between efficiency and linearity, as measured by the error vector magnitude (EVM), for a given signal by proper choice of the outphasing combinerpsilas reactances. The resulting combiner ensures signal transmission with the maximum efficiency that meets the established linearity requirement.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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