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Record W2885350572 · doi:10.1109/tcsi.2018.2858197

A Compact, Voltage-Mode Type-I PLL With Gain-Boosted Saturated PFD and Synchronous Peak Tracking Loop Filter

2018· article· en· W2885350572 on OpenAlexafffund
Ahmad Sharkia, Sankaran Aniruddhan, Shahriar Mirabbasi, Sudip Shekhar

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCMC MicrosystemsIntel Corporation
KeywordsPhase-locked loopVoltage-controlled oscillatorCMOSControl theory (sociology)dBcCharge pumpElectronic engineeringPhase noisePhase detectorPhase frequency detectorTopology (electrical circuits)PLL multibitEngineeringVoltagePhysicsComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Despite their inherent stability, area-efficient loop filters, and insensitivity to phase-frequency detector nonlinearity and dead-zone, type-I phase-locked loops (PLLs) are used infrequently because of two major limitations-limited lock-range and large reference spurs. This paper introduces a type-I PLL that takes advantage of the inherent benefits of the architecture, while tackling its limitations by means of gain boosting in the forward path for lock-range improvement and synchronous peak tracking of the voltage-controlled oscillator control voltage for reference spur reduction. Sampling in the loop filter changes the loop dynamics, and methods to accurately predict the closed-loop response, starting from state-space equations, are provided. A digital-friendly, voltage-mode topology is proposed that does not need charge pumps or opamps. A prototype 2.2-2.8-GHz PLL occupies a core area of 0.12 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in 0.13-μm CMOS and achieves -103.4 dBc/Hz in-band phase noise, -65-dBc reference spur, and 2.5-μs worst-case lock-time while consuming 6.8 mW from a 1.2-V supply.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.231
Teacher spread0.215 · 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 teacher head, 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

Citations23
Published2018
Admission routes2
Has abstractyes

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