Dual-band GaN HEMT power amplifier using resonators in matching networks
Bibliographic record
Abstract
In this paper, we employ a novel method by using resonators with microstrip lines to design a dual-band GaN HEMT power amplifier. At both input and output matching networks, we add parallel resonators between series microstrip lines and open-circuited stubs to realize the dual-band operation. With our proposed structure, we can use the conventional L-type structure to design matching network for each operation frequency so that the design is easier. By using just one transistor without any tunable electronic element or switch, a novel dual-band class AB power amplifier working at 1.5 GHz and 2.4 GHz is designed and fabricated to demonstrate our proposed simple method. With dual-band matching networks using resonators, the experimental results show the output power 40.3 dBm and 39.05 dBm with power added efficiency (PAE) 55.63% and 40.25% at 1.5 GHz and 2.4 GHz, 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".