A 28-GHz Quadrature Fractional-N Frequency Synthesizer for 5G Transceivers With Less Than 100-fs Jitter Based on Cascaded PLL Architecture
Bibliographic record
Abstract
This paper introduces a quadrature fractional-N cascaded frequency synthesizer and its phase noise analysis, optimization, and design for future 5G wireless transceivers. The performance improvement of the cascaded phase-locked loop (PLL) over single-stage PLL in terms of jitter and power consumption is theoretically presented and verified with measured results. The cascaded PLL is implemented using a first-stage fractional-N charge-pump PLL followed by a second-stage quadrature dividerless subsampling PLL. The fractional division in the first-stage PLL is implemented using a high-resolution phase mixer for lower quantization noise. Two prototypes of the single-stage PLL and the cascaded PLL were implemented in the 65-nm bulk CMOS process. The 26-32 GHz quadrature cascaded PLL consumes a total of 26.9 mW from 1-V supply and achieves less than 100-fs integrated jitter with -116.2 and -112.6-dBc/Hz phase noise at 1-MHz offset for the integer-N and the fractional-N modes, respectively. The fractional-N single-stage and cascaded PLLs achieve figure-of-merits of -230.58 and -248.75 dB, respectively.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".