Comparative Robustness of CML Phase Detectors for Clock and Data Recovery Circuits
Bibliographic record
Abstract
In this paper the robustness of CML based phase detectors is analyzed with respect to the scaling of CMOS processes. Phase detectors are an important part of CDR circuits, which enable high-speed serial data links. As CDR circuits are integrated into monolithic CMOS ICs, their robustness becomes critically important. Three phase detectors are analyzed over corners in three standard CMOS processes: 180nm, 130nm and 90nm. The results of the simulations show that the total variation of the static phase offset increases with scaling for all phase detectors. The presence of a static phase offset is mathematically shown to negatively affect the BER of a CDR circuit. The analysis shows that the DFF binary phase detector has an advantage in terms of robustness however it has performance limitations. Both the Alexander and Hogge phase detector experience significant and increasing variations in static phase offset as the technology scales
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".