An Area-Efficient Multistage 3.0- to 8.5-GHz CMOS UWB LNA Using Tunable Active Inductors
Bibliographic record
Abstract
An area-efficient multistage 3.0- to 8.5-GHz ultrawideband low-noise amplifier (LNA) utilizing tunable active inductors (AIs) is presented. The AI includes a negative impedance circuit (NIC) consisting of a pair of cross-coupled NMOS transistors and is tuned to vary the gain and bandwidth (BW) of the amplifier. Fabricated in a 90-nm digital CMOS process, the proposed fully on-chip LNA occupies a core chip area of only 0.022 mm2. The measurement results show a power gain S21of 16.0 dB, a noise figure of 3.1-4.4 dB, and an input return loss S11 of less than -10.5 dB over the 3-dB BW of 3.0-8.5 GHz. Tuning the AIs allows one to increase the gain above 18.0 dB and to extend the BW over 9.4 GHz. The LNA consumes 16.0 mW from a power supply of 1.2 V.
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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".