A Highly Integrated 1.8 GHz Frequency Synthesizer Based on a MEMS Resonator
Bibliographic record
Abstract
A highly integrated 1.7-2.0 GHz digitally programmable frequency synthesizer using a MEMS resonator as its reference is presented. Due to the dimensions of the MEMS device (e.g., 25 mum by 114 mum), the entire system with a total area of 6.25 mm2can be housed in a small standard chip package. This considerably reduces the form factor and cost of the system, compared to using an external crystal as a reference. The MEMS resonators are clamped-clamped beams fabricated using a CMOS-compatible process. The main structural layer is made of silicon carbide, which provides the resonators with higher power handling capabilities and higher operating frequencies, compared to silicon. The resonators are electrostatically and thermally tunable - an 8.4% frequency tuning is demonstrated for a 9 MHz resonator. The 100 nm vertical transducer gaps of the resonators allow the use of electrostatic actuation voltages as low as 2 V. An integrated high gain-bandwidth trans-impedance amplifier (TIA) is combined with a resonator to generate the synthesizer's input reference signal. The TIA employs automatic gain control to mitigate the inherent low power handling capabilities and the non-linearities of the MEMS device, thus minimizing their effect on phase noise. The fractional- N synthesizer employs a 3rd-order 20-bit delta-sigma modulator to deliver a theoretical output resolution of ~ 11 Hz, in order to allow for high output frequency stability when used with an appropriate feedback loop. A fully integrated on-chip dual path loop filter is used to maintain a high level of system integration. With a supply voltage of 2 V, the phase noise for a 1.8 GHz output frequency and a ~12 MHz reference signal is -122 dBc/Hz at a 600 kHz offset, and -137 dBc/Hz at a 3 MHz offset.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".