Noise figure optimization of wide-band inductively-degenerated CMOS LNAs
Bibliographic record
Abstract
This paper presents the design and measurement results of a wide-band inductively-degenerated 0.18-mum CMOS LNA targeted for the square kilometer array (SKA) radio telescope. A noise figure optimization procedure is discussed that allows selection of an optimum power consumption resulting in the lowest noise figure given the required bandwidth. The noise optimization procedure accounts for the parasitic resistances of both the transistor's gate fingers and the gate inductor. Measured results of a single-stage 700 MHz-1400 MHz LNA are discussed. The LNA, designed in 0.18-mum CMOS, achieves noise figures better than 0.57 dB, gain (S21) of at least 15 dB, input return loss of greater than 16 dB, output P1dB of 6 dBm, and output IP3 of 14.5 dBm while consuming 50 mW of power from a 1.5-V supply.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
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".