EFFECT OF SECOND AND THIRD HARMONIC INPUT IMPEDANCES IN A CLASS-F AMPLIFIER
Bibliographic record
Abstract
In this paper, the design of a class-F radio frequency power amplifler with a multiharmonic input transmission line network is presented. Harmonic signal components at the gate come from several sources including nonlinear device capacitances and imperfect output harmonic terminations that create harmonic components that are fed back to the gate through the gate-drain capacitance. The efiect of these harmonic generation mechanisms and the potential to shape the gate waveform to improve power e-ciency are investigated. The study shows that a second harmonic short is most beneflcial and the efiect of a third harmonic termination is less signiflcant. The concepts are applied to the design of a 10W GaN class-F amplifler and the design is supported by theoretical, simulation and experimental results. The fabricated design has a measured drain e-ciency of 78.8% at an output power of 40.5dBm for a frequency of 990MHz. The amplifler was also tested with a 8.8dB peak-to-average power ratio 5MHz WCDMA signal. With the modulated signal, the adjacent channel power ratio was i33:1dBc at a drain e-ciency of 46.1% without predistortion correction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".