A 0.18μm CMOS 2.1GHz Sub-sampling Receiver Front End with Fully Integrated Second- and Fourth-Order Q-Enhanced Filters
Bibliographic record
Abstract
The implementation of a 0.18μm CMOS 2.1GHz sub-sampling receiver front end with fully integrated fourth-and second- order Q-enhanced LC filters is described. The use of an integrated fourth-order filter allows the amount of noise aliasing due to sub-sampling to be reduced and the bandwidth and roll-off factor to be independently controlled. When tuned to a high effective quality factor of 210, the front end has a measured bandwidth of 14MHz, a passband flatness of +/-0.4dB, a gain of 34dB and an input IP3 of -31.7dBm. The simulated noise figure of the front end is 7.12dB, which is lower than that of previously published sub-sampling front ends using off-chip inductors. The total power consumption of the front end is 28.5mA from a 1.8V 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".