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Record W4246330818 · doi:10.32920/ryerson.14653047.v1

Subthreshold Frequency Synthesis For Implantable Medical Devices

2021· preprint· en· W4246330818 on OpenAlexaff
Tarek Khan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSubthreshold conductionElectrical engineeringElectronic engineeringComputer scienceMaterials scienceOptoelectronicsEngineeringTransistorVoltage

Abstract

fetched live from OpenAlex

<p>In this thesis, several novel circuits for use in an ultra-low power integer-n frequency synthesizer operating in the 402 MHz to 405 MHz Medical Implant Communication Service spectrum have been proposed. The proposed designs include a current-reuse quadrature voltage-controlled oscillator, a novel subthreshold source-coupled logic D-latch with clear and preset functionality, a programmable frequency divider and phase/frequency detector based on the aforementioned D-latch, and a modified current-steering charge pump. A design methodology for low-power CMOS oscillators was proposed based on the MOS EKV model and g<sub>m</sub>/i<sub>d</sub> design methodology. The proposed designs were implemented using IBM CMRF8SF130 nm CMOS technology and simulated using Cadence Spectre. Simulation results for the proposed current-reuse quadrature voltage-controlled oscillator and programmable frequency divider consume 420µW and 200µW respectively from a 0.7 V supply, a significant improvement compared to existing designs. The simulated phase noise of the proposed oscillator is -127.2 dBc/Hz at a 1 MHz offset. Measurement results from a fabricated prototype of the current-reuse quadrature verify the simulation results and serve as a proof-of-concept for the proposed design. The proposed designs were used to implement an integer-n frequency synthesizer and were submitted for fabrication. Simulation results show that the synthesizer consumes 635µW from a 0.7 V supply and has a locking time of 250µs.</p>

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.237
Teacher spread0.221 · 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.

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
Published2021
Admission routes1
Has abstractyes

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