An Improved Comparator Based on Current Reuse and a New Frequency Compensation Technique used in an OTA for Pipeline ADCs
Bibliographic record
Abstract
In this paper, a comparator and an operational amplifier considered as essential components, constituting a 10-bit 50-MHz pipeline Analog-to-Digital Converter for Wireless Local Area Network (WLAN) applications, are described and designed. All post-layout and Monte-Carlo simulations, using a 0.35[Formula: see text][Formula: see text]m CMOS AMS process technology with [Formula: see text][Formula: see text]V supply voltage and an input common-mode range of [Formula: see text][Formula: see text]V, are achieved. An improved clocked comparator with a dynamic latch, based on a switched capacitor network, using the current reuse technique for slew rate enhancement and positive feedback for offset voltage compensation, is presented. The operational amplifier, consisting of a fully differential folded cascode operational transconductance amplifier, providing high-gain and good stability, is exhibited. A new frequency compensation technique, based on active resistors, is used to improve amplifier phase-margin. The Monte-Carlo performance results of the designed clocked comparator provide an offset voltage of [Formula: see text][Formula: see text]mV with [Formula: see text][Formula: see text]mV 3[Formula: see text] deviation, a slew rate of [Formula: see text]V/ns with [Formula: see text]V/ns 3[Formula: see text] deviation, and a propagation delay of [Formula: see text][Formula: see text]ns with [Formula: see text][Formula: see text]ns 3[Formula: see text] deviation. Monte-Carlo performance results of the designed operational amplifier provide a phase-margin of [Formula: see text], and a high-gain of [Formula: see text]dB with [Formula: see text] and [Formula: see text]dB 3[Formula: see text], respectively, by using [Formula: see text] load capacitance.
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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 | 0.001 |
| 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 | 0.001 | 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".