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Record W2899996489 · doi:10.1109/jssc.2018.2874013

A Type-I Sub-Sampling PLL With a <inline-formula> <tex-math notation="LaTeX">$100\times100\,\,\mu\text{m}^{2}$ </tex-math> </inline-formula> Footprint and −255-dB FOM

2018· article· en· W2899996489 on OpenAlexafffund
Ahmad Sharkia, Shahriar Mirabbasi, Sudip Shekhar

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaIndian Institute of Technology MadrasCMC MicrosystemsIntel Corporation
KeywordsVoltage-controlled oscillatorPhase-locked loopFigure of meritPhase noiseCMOSJitterdBcPhysicsElectrical engineeringLoop (graph theory)Electronic engineeringVoltageMathematicsEngineeringOptoelectronics

Abstract

fetched live from OpenAlex

A dual-loop LC-voltage-controlled oscillator (VCO)based frequency synthesizer, composed of an all-digital frequency-locked loop (ADFLL) and a voltage-mode, type-I, subsampling phase-locked loop (SS-PLL), is presented. A compact SS phase detector is described which also acts as a loop filter (LF). Fabricated in a 65-nm CMOS process, the synthesizer occupies a small footprint of 100 × 100 μm2, thanks to its compact LF and full integration underneath the VCO inductor. The synthesizer achieves the sub-200 fs of rms integrated jitter across its tuning range of 4.6-5.6 GHz while consuming no more than 1.1 mW of power. A peak figure-of-merit (FOM) of -255 dB at 5 GHz and an FOM of -254 dB across the tuning range are achieved. A reference spur of -64.1 dBc is measured with the PLL operating at 5 GHz.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.005

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 head0.024
GPT teacher head0.270
Teacher spread0.247 · 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 designBench or experimental
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

Citations52
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Journal of Solid-State CircuitsSame topicAdvancements in PLL and VCO TechnologiesFrench-language works237,207