A 0.01mm<sup>2</sup> 4.6-to-5.6GHz sub-sampling type-I frequency synthesizer with −254dB FOM
Bibliographic record
Abstract
Power consumption, Performance in terms of phase noise and integrated jitter, and Area (PPA) are three design metrics that have driven countless research efforts in CMOS frequency-synthesizer design. Design limitations and system-level tradeoffs have made simultaneous optimizations of PPA metrics in PLLs challenging. In traditional Type-II charge-pump (CP) based PLLs, power is consumed in the VCO, divider (N), and CP to improve noise performance, and area is consumed in large loop-filter (LF) capacitors. ADPLLs are attractive due to compact LF, but are limited in noise performance. Sub-sampling (SS) PLLs eliminate divider noise, and remove the N2amplification of the phase detector (PD), CP, and LF noise, thereby improving the overall phase-noise performance [1]. However, their area is large due to the LF capacitors [1]. The performance of CPs and ring-VCOs in traditional or SS Type-II PLLs are also encumbered by reduced VDDin scaled CMOS processes. Overall, PLLs with ring-VCOs have higher noise [2,3], and PLLs with LC-VCOs have larger area [1]. Figure 15.6.1 highlights the PPA tradeoffs in prior art.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.015 | 0.006 |
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".