Class-iF<sup>−1</sup>: Linearity Enhanced High Efficiency Power Amplifier
Bibliographic record
Abstract
This paper presents a new class of power amplifier (PA) - Class-iF-1- resolving the highly nonlinear double inflection characteristics in the conventional Class-F-1PA. It is illustrated that, by properly terminating the second harmonic source impedance Z2Sfrom conventional short-circuit to open-circuit, the double inflection nonlinear gain profile can be mitigated in the proposed Class-iF-1PA, wherein the same saturation output power is achieved with less gain compression without drain efficiency trade-off. The idea was validated with source/load-pull and a broadband prototype operating from 2.0 to 2.6 GHz was designed using a commercial 10-W Gallium Nitride (GaN) transistor. Under continuous wave (CW) signal test, the proposed Class-iF-1PA can achieve 40.1-40.8-dBm output power, 71.2%-77.3% drain efficiency (DE) and 67.4%-74.1 % power added efficiency (PAE) at 3-dB gain compression level over 2.0-2.6 GHz.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".