Octave Bandwidth Doherty Power Amplifier Using Multiple Resonance Circuit for the Peaking Amplifier
Bibliographic record
Abstract
This paper presents a broadband Doherty power amplifier (DPA) design with an octave bandwidth based on a new load network consisting of a quasi-lumped impedance transformer for the carrier amplifier, a multiple resonance circuit for the peaking amplifier, and a broadband post-matching network. The quasi-lumped impedance transformer and the multiple resonance circuit were designed based on accurate equivalent circuits for internal components inside the packaged transistor. Based on power bandwidth analysis, optimum susceptance provided by the multiple resonance circuit at the peaking amplifier, was obtained. The proposed broadband DPA was designed using 45 W gallium-nitride high electron mobility transistor for both carrier and peaking amplifiers. For continuous-wave signals in frequency range of 0.9 to 1.8 GHz, the implemented broadband DPA exhibited a drain efficiency of 54.2% to 73.4% at peak output power of 49.7 to 51.4 dBm and a drain efficiency of 41.7% to 58.0% at output back-off of 6 dB. For the down-link long-term evolution signal with a channel bandwidth of 10 MHz and a peak-to-average power ratio of 6.5 dB, a drain efficiency of 41.3% to 57.4% and an adjacent channel leakage power ratio of -22.5 to -30.2 dBc at an average output power of 43.2 to 449 dBm were achieved at an octave bandwidth.
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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 | 0.001 |
| 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".