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Record W2122860598 · doi:10.1109/ccece.2006.277635

Bandwidth Expansion in Sigma-Delta PLLs Using Multiphase VCOs

2006· article· en· W2122860598 on OpenAlexaff
Igor Miletić, R. Mason

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsVoltage-controlled oscillatorDelta-sigma modulationPhase noiseElectronic engineeringNoise shapingClock generatorCMOSBandwidth (computing)Phase-locked loopChipQuantization (signal processing)EngineeringFrequency synthesizerElectrical engineeringVoltageComputer scienceTelecommunicationsClock signalJitter

Abstract

fetched live from OpenAlex

A 120MHz fractional-N frequency synthesizer was implemented in a standard 0.18mum CMOS process with an on-chip multiphase voltage-controlled oscillator (VCO). The proposed architecture uses multiphase outputs of the VCO to decrease quantization noise from the sigma-delta (SigmaDelta) modulator. Results show 6dB decrease in quantization noise for every two fold increase in the number of phases, which allows increase in loop bandwidth. The VCO phase noise was measured to be -104dBc/Hz at 200kHz offset. The loop bandwidth can be increased to 700kHz and still maintain in-band quantization noise below -100dBc/Hz. The power consumption of the synthesizer is 5.4mW with a 1.8V supply and it occupies an active area of 750mum times 550mum. The intended application is subharmonic injection higher frequency VCO and as a clock generator in a subsampling analog-to-digital converter (ADC)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.240
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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Same topicAdvancements in PLL and VCO TechnologiesFrench-language works237,207