A 1.7-dB Minimum NF, 22–32-GHz Low-Noise Feedback Amplifier With Multistage Noise Matching in 22-nm FD-SOI CMOS
Bibliographic record
Abstract
A low-noise feedback amplifier (LNA) with interstage noise matching is implemented in 22-nm fully depleted silicon-on-insulator (SOI)-CMOS technology. Minimum noise figure (NF) is 1.7 dB centered at 28 GHz, and NF remains below 1.98±0.25 dB across a 10-GHz range. Peak gain of the two-stage LNA is 21.5 dB at 22 GHz, and the bandwidth (BW) for |S21| is 19-36 GHz. Input and output return losses are better than 10 dB across an effective LNA BW of 22-32 GHz. The third-order input intercept is -13.4 dBm at peak gain when dissipating 17.3 mW. Continuous dc power control on the fly is implemented using modulation of FET backgates. When dc power consumption is reduced 5.6 mW, NF increases by less than 0.5 dB, peak gain decreases by 3.6 dB, and input return loss remains better than 10 dB with no change in effective BW.
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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 | 0.001 |
| 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 | 0.001 | 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".