A novel Doherty power amplifier with self‐adaptive biasing network for efficiency improvement
Bibliographic record
Abstract
Abstract A Doherty power amplifier (DPA) with a self‐adaptive biasing circuit is presented in this letter. The proposed structure is integrated into the gate biasing network of the peaking power amplifier (PA), and then the gate voltage can be adaptively adjusted with the input power. Due to the presence of this simple but effective circuit, the peaking PA can approach the ideal power transfer characteristic which results in better efficiency than the conventional design with constant biasing. The proposed circuit is implemented and compared with both the conventional DPA and a single Class‐AB PA. 12% and 34% power added efficiency improvements are achieved at 6 dB backoff, respectively. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2586‐2589, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26301
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".