24 GHz Low-Noise Amplifiers using High Q Series-Stub Transmission Lines in 0.18μm CMOS
Bibliographic record
Abstract
Single-ended and differential low-noise amplifiers (LNAs), designed in 0.18 μm CMOS for operation at 24 GHz, are introduced in this paper. Novel, high-Q series-stub transmission lines (SSTLs) are used in the matching networks of both LNAs. This SSTL structure shows a notable Q factor improvement over the commonly used spiral inductor, which helps to minimize the losses and noise produced in the LNA matching networks, making these topologies suitable for sensitive receiver front ends. The single-ended amplifier uses two cascade stages to help improve gain and reverse isolation when compared to common source stages. Results show that the cascade LNA is able to produce an excellent compromise between ease of design, gain and noise. After optimizing transistor sizes to produce minimum noise, the single-ended amplifier produces a simulated noise figure of only 4.9 dB and a gain of 17.4 dB. The differential LNA uses two capacitive neutralized stages to improve reverse isolation. Chip production has been delayed by the foundry, but simulated results of the differential LNA show an excellent noise figure of 4.2 and a gain of 12.3 dB
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".