An optimized Doherty power amplifier using an unequal quadrature input splitter
Bibliographic record
Abstract
Abstract In this article, we present an optimized Doherty power amplifier using an unequal quadrature input splitter and bias control for the peaking amplifier. The linearity and efficiency performances of the Doherty power amplifier were experimentally optimized by means of unequal quadrature input power splitters, which drive unbalanced input power between the carrier and peaking amplifiers. The bias points of the peaking amplifier were also adjusted for each input splitter. A high power‐added efficiency of 33.68% and an output power of 33.95 dBm were achieved for a down‐link wide‐band code division multiple access signal excitation at a given adjacent channel leakage‐power ratio of −30 dBc. This was a significant improvement by 2.75% and 8.22% points from the conventional Doherty and class‐AB amplifiers, respectively. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 1536–1539, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23420
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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) | 0.001 | 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 | 0.000 |
| 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".