A 14-GHz Bang-Bang Digital PLL With Sub-150-fs Integrated Jitter for Wireline Applications in 7-nm FinFET CMOS
Bibliographic record
Abstract
Demands for increased wireline data throughput necessitate multi-gigahertz clock sources of ever-greater fidelity. This article demonstrates a 14-GHz bang-bang digital phase-locked loop (BBPLL) with 143-fs rms jitter (integrated from 1 kHz to 100 MHz) to clock a 56-Gb/s PAM-4 transceiver. The low jitter is achieved with an LC-based digitally controlled oscillator (DCO) having a tuning range of 2 GHz, a frequency resolution of 1.2 MHz/LSB, and a low phase noise of -104 dBc/Hz at 1-MHz offset. All PLL digital functions are consolidated in a single, fully synthesized digital signal processing unit operating at 3.5 GHz or 10× the reference clock frequency. Limit cycles are minimized without the aid of a time-to-digital converter through substantial reduction of loop latency using a look-ahead digital loop filter. Various design techniques exploiting the advanced 7-nm FinFET technology are discussed, including noise reduction and tank Q enhancement. Closed-loop phase noise performance is accurately predicted using an industry-standard digital event-driven simulator with dramatically reduced computation effort compared to analog or mixed-mode simulators. Here, the accuracy and computational burden of calculating 1/fαnoise is overcome by pre-calculating the DCO and reference phase noise profiles. The results obtained from these simulation techniques show very close agreement with experimental measurements. This 7-nm FinFET PLL occupies a competitive 0.06 mm2and consumes 40 mW.
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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 | 0.000 |
| 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) | 0.001 | 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 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".