A 1-V 13-mW Single-Path Frequency-Translating $\Delta \Sigma $ Modulator With 55-dB SNDR and 4-MHz Bandwidth at 225 MHz
Bibliographic record
Abstract
This paper presents a frequency-translating bandpass ΔΣ modulator that uses single-path mixing within the ΔΣ feedback loop to downconvert a 4-MHz signal band from IF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> = 225 MHz at the input to IF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> = 25 MHz at the output. The proposed ΔΣ modulator is designed with a sixth-order continuous-time loop filter and a 3-bit quantizer. The quantizer operates at a sampling frequency of 100 MHz, which is lower than IF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and, therefore, reduces both the power consumption and the sensitivity to timing errors relative to a conventional bandpass ΔΣ modulator. Furthermore, the loop filter implements noise shaping primarily at IF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , which reduces the sensitivity to coefficient variations. The prototype chip was fabricated in 65-nm CMOS with an active area of 0.55 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . It achieves an SNDR of 55 dB over a 4-MHz signal bandwidth, and consumes 13 mW from a 1-V power supply.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".