A Reconfigurable DLL-Based Digital-to-Time Converter Using Charge Pump Current Interpolation and Digital Predistortion Linearization
Bibliographic record
Abstract
This brief presents a digital-to-time converter (DTC) based on a reconfigurable delay-locked loop that employs dual feedback taps and interpolation at the output of two charge pumps biased with programmable complementary currents from a current digital-to-analog converter (I-DAC) to achieve fine delay tuning. Through selection of the feedback and output delay line taps, the 65-nm CMOS prototype can be configured to achieve different specs, such as a 24.5 ps delay span with a 0.46 ps maximum delay step and 1.33 ps maximum RMS jitter or a span of 244 ps with a 3.30 ps maximum step and 2.63 ps maximum RMS jitter when a 7-bit I-DAC and a 2 GHz input are used. A simple digital predistortion method to compensate for the inherent nonlinearity of the architecture is presented and experimentally shown to improve the worst-case integral nonlinearity from -14.3 LSB (-27.6 ps) to +1.79 LSB (+3.43 ps) for the 244 ps delay span case, and by 67%-88% at all taps for the same loop configuration. Excluding the I-DAC, which would require an estimated 0.2 mW, the DTC consumes 0.665 mW from a 1.25-V supply at 2 GHz and occupies an area of 46 μm × 28 μm.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".