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Record W2126391376 · doi:10.1109/cicc.2006.320973

An Anti-Harmonic Locking, DLL Frequency Multiplier with Low Phase Noise and Reduced Spur

2006· article· en· W2126391376 on OpenAlexafffund
Qinglei Du, Jingcheng Zhuang, T. Kwaśniewski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsdBcFrequency multiplierJitterPhase noiseCMOSVoltage-controlled oscillatorPhase-locked loopFrequency offsetElectrical engineeringElectronic engineeringLow-power electronicsSignal generatorComputer sciencePhysicsEngineeringChipPower (physics)VoltagePower consumptionOrthogonal frequency-division multiplexing

Abstract

fetched live from OpenAlex

This paper presents a new programmable delay-locked loop based frequency multiplier with a period error compensation loop (PECL) designed to reduce the output spurious power level. The low bandwidth auxiliary PECL compensates the output period error caused by the in-lock errors from various noise sources. By employing a novel switching control scheme, the circuit is capable of locking to frequencies either above or below the start up frequency without initialization. Programmable multiplication ratios from 13 to 20 are achieved with an output frequency range of 900 MHz to 2.9 GHz. The circuit is implemented in TSMC 0.18mum CMOS technology and measured with the reference signal from an RF signal generator. A 23 dB spur reduction from -23dB to -46.5dB at 1.216GHz is observed from the measurement results. The measured cycle-to-cycle timing jitter at 2.16GHz is 1.6ps (rms) and 12.9 ps (pk-pk), and the measured phase noise is -110 dBc/Hz at 100 kHz offset with a power consumption of 19.8 mW at a 1.8 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 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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

Citations4
Published2006
Admission routes2
Has abstractyes

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