6–18 GHz GaAs pHEMT Broadband Power Amplifier Based on Dual-Frequency Selective Impedance Matching Technique
Bibliographic record
Abstract
This paper presents a broadband gallium-arsenide pseudomorphic high-electron-mobilitytransistor (GaAs pHEMT) power amplifier integrated circuit (PAIC) based on a dual-frequency selective impedance matching technique for warfare applications. For a broadband PA design, lower and upper-frequency corners where serious performance degradation is likely to occur should be carefully considered. Feedback and resistive biasing circuits were adopted for driver and main stages to making their frequency responses as flat as possible. Optimum impedances of not only extended lower and upper-frequency corners but also center frequency, were then extracted. Such dual-frequency selective impedance matching technique was applied for extended lower and upper-frequency corners while checking the mismatch level for the center frequency. The proposed broadband PAIC for frequency band from 6 to 18 GHz was designed using a 0.15 μm GaAs enhanced-mode pHEMT (E-pHEMT) process. The implemented broadband PAIC with a simple two-stage structure had a very small chip size of 1.19×0.82 mm2. It exhibited a power gain of more than 16.4 dB and output power of 19.2 dBm. Very flat characteristics in power gain and an output power within ±1.0 dB through the whole band were achieved.
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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".