A 10-MHz BW 77.3-dB SNDR 640-MS/s GRO-Based CT MASH ΔΣ Modulator
Bibliographic record
Abstract
We present in this brief a novel multi-stage noise-shaping (MASH) 3–1 continuous-time (CT) delta-sigma modulator ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula> ) with gated ring oscillator based quantizers (GROQs) in both stages of the cascade. The use of GROQs increases the linearity performance with respect to the conventional voltage controlled oscillator based quantizers (VCOQs) and allows a more robust extraction of the front-end stage quantization error in the time domain, thus making the proposed architecture more suitable to implement high-order expandable scaling-friendly MASH <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> Ms, in which the back-end stages are implemented by mostly-digital GRO-based time-to-digital converters (TDCs). The circuit has been fabricated in a 65-nm CMOS technology with 1-V supply voltage, and it operates at 640-MHz sampling frequency to digitize 10-MHz signals. To the best of the authors’ knowledge, this is the first reported experimental validation of a GRO-based CT MASH <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \Sigma \text{M}$ </tex-math></inline-formula> , featuring a 79.8-dB signal to noise ratio (SNR) at −2.2-dBFS, a 77.3-dB signal to (noise + distortion) ratio (SNDR) at −4-dBFS and a dynamic range (DR) of 81.7 dB, with a power consumption of 12-mW. These metrics demonstrate state-of-the-art performance with a DR-based Schreier FOM of 170.9 dB.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".