Distortion in RF CMOS short-channel low-noise amplifiers
Bibliographic record
Abstract
An approach to estimate the distortion in CMOS short-channel (e.g. 0.18-/spl mu/m gate length) RF low-noise amplifiers (LNAs), based on Volterra's series, is presented. Compact and accurate frequency-dependent closed-form expressions describing the effects of the different transistor parameters on harmonic distortion are derived. For the first time, the second-order distortion (HD2), in CMOS short-channel based LNAs, is studied. This is crucial for systems such as homodyne receivers. Equations describing third-order intermodulation distortion in RF LNAs are reported. The analytical analysis is verified through simulations and measured results of an 0.18-/spl mu/m CMOS 5.8-GHz folded-cascode LNA prototype chip geared toward sub-1-V operation. It is shown that the distortion is independent of the gate-source capacitance C/sub gs/ of the MOS transistors, allowing an extra degree of freedom in the design of LNA circuits. Distortion-aware design guidelines for RF CMOS LNAs are provided throughout the paper.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 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".