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Record W2792673958 · doi:10.1109/jssc.2017.2776307

On-Chip Jitter Measurement Using Jitter Injection in a 28 Gb/s PI-Based CDR

2018· article· en· W2792673958 on OpenAlexafffund
Joshua Liang, Ali Sheikholeslami, Hirotaka Tamura, Hisakatsu Yamaguchi

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsHuawei Technologies (Canada)University of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TokyoCMC Microsystems
KeywordsJitterChipAutocorrelationPhysicsDetectorCMOSElectronic engineeringComputer scienceOpticsOptoelectronicsTelecommunicationsMathematicsEngineering

Abstract

fetched live from OpenAlex

We present a technique to measure random jitter in a phase interpolator (PI)-based clock and data recovery (CDR) circuit by injecting a controlled amount of square-wave jitter into its edge clock and monitoring its effect on the autocorrelation function of the CDR's bang-bang phase detector output. Jitter is injected by adjusting the code of the edge PI while the autocorrelation function is measured by on-chip counters. Since the injected jitter only affects the edge clock, the CDR remains operational during jitter injection. Using this technique, the rms relative jitter between the clock and data at the CDR input can be estimated with sub-picosecond accuracy as demonstrated in measurements of a 28 Gb/s half-rate digital CDR fabricated in 28 nm CMOS.

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)0.001
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 score0.506
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.051
GPT teacher head0.283
Teacher spread0.232 · 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

Citations18
Published2018
Admission routes2
Has abstractyes

Explore more

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