Novel dual-band matching network topology and its application for the design of dual-band Class J power amplifiers
Bibliographic record
Abstract
In this paper, a systematic design of a dual-band power amplifier (PA) is presented. Using the inherent impedance matching flexibility of a Class J operating mode, we can start by relaxing the performance sensitivity and design requirements of the matching networks. Then, a novel dual-band matching network topology is devised to simultaneously present adequate source and load impedances at the fundamental and harmonic components of both targeted operating frequencies. The dual-band matching network is designed in two stages. First, a complex-to-real impedance transformation network, with harmonic control capability, is used to transform the complex impedance for class J operation to real impedance that is common to both operation frequencies. Then, a real-to-real trans-impedance transformer is synthesized using dual-band filter theory. This technique was successfully applied to design a dual-band 45W GaN Class J PA operating at 0.8GHz and 1.9GHz. The measurement results of the fabricated PA shows peak efficiencies of 74.4% at the lower band and 57.6% at the upper band.
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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".