An Extended-Bandwidth Three-Way Doherty Power Amplifier
Bibliographic record
Abstract
This paper expounds a three-way Doherty power amplifier (3W-DPA) as a solution to the need for high-efficiency wideband power amplifiers when driven by multi-standard signals. The paper begins with a theoretical analysis of 3W-DPA architecture from which the governing equations are derived. This analysis enables the identification of circuit parameters for maximizing bandwidth. A comprehensive methodology was devised to address the practical design challenges resulting from the transistor nonidealities: nonlinear input capacitance, transistor package, and output capacitance. Based on this methodology, a fully analog 30-W 3W-DPA was designed and implemented using GaN packaged transistors. The 3W-DPA prototype maintained an average drain efficiency of 55% at an output back-off of up to 9 dB, over the frequency range of 0.73-0.98 GHz. The 3W-DPA was successfully linearized when driven with 20-MHz four-carrier wideband code division multiple access (WCMDA) signals. 830- and 900-MHz power-added efficiencies of 47% and 53% was achieved at 32- and 35-dBm average output power, corresponding to a peak-to-average power ratio of 11.7 and 7.14 dB, respectively.
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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 | 0.001 |
| 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".