Efficient output power configuration in a <i>K</i> -band power amplifier using a split-gate layout
Bibliographic record
Abstract
Abstract A multi-finger radio frequency (RF) transistor has been divided into multiple gate sections which can be biased independently. This provides a system designer the ability to dynamically reconfigure the output power and power gain of the device while maintaining good power efficiency and without changing the input drive power. By selectively switching the gate biases below pinch-off to effectively reduce the device’s active periphery, the maximum current of the device can be tuned to “follow” a reduced drain bias voltage, so that the optimum impedance at lower power remains similar to the one at full power, and a fixed matching network can be used to accommodate all power modes. The concept has been tested in a large signal load–pull characterization campaign on a test cell and implemented in a K -band power amplifier (PA) prototype. Measurements on the PA confirm the effectiveness of the method, achieving 30% efficiency at around 4.8–4.9 dB of output power tunability when maintaining a constant input power.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".