High frequency low cost CMOS LNA design procedure for the wireless industry
Bibliographic record
Abstract
This paper presents a design procedure used in industry for designing low-power narrowband high-gain CMOS LNAs for wireless applications for frequencies greater than 6 GHz, with considerations for process variations. This paper does not give detailed derivations of equations. Rather, it gives the simulation procedure and methodology that converges quickly to a practical optimized solution for LNA designs mostly used in mobile communication industry for mass-production, requiring minimal time and resources from the designer. It takes a wholistic design approach where all factors, including manufacturing costs, technology choice and applications are considered. It explains how to design the appropriate topology from the ldquogrounds uprdquo approach, and then giving the designer the option to match the ports or not, depending on if it is appropriate. This method yields these LNA parameters at 6.5 GHz: S21=18 dB, NFmin=3.22 dB, NF=6.1 dB and S22,<-15 dB with only 6.4 mW (plus 2.5 mW for narrowband output match) power consumption over 1.2 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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".