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Record W2612556938

Adaptive receivers for high-speed wireline links

2013· dissertation· en· W2612556938 on OpenAlexaff
Anthony Chan Carusone, Dustin Dunwell

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWirelineAutomatic gain controlPreamplifierElectronic engineeringEngineeringElectrical engineeringComputer scienceWirelessAmplifierTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines the design of high-speed wireline receivers that can be adapted to a variety of operating conditions. In particular, the ability to adapt to varying received signal strengths, channel losses and operating frequencies is explored. In order to achieve this flexibility, this thesis examines several key components of such a receiver. First, a 15 Gb/s preamplifier with 10-dB gain control for the input stage of an analog front end (AFE) is presented that automatically adjusts its power consumption to suit the gain and linearity requirements of the AFE for various received signal strengths. The gain of this preamplifier, along with the amount of peaking delivered by a linear equalizer in the AFE are controlled using a new adaptation technique, which adds only a small amount of overhead to the receiver. This adaptation scheme is able to sense changes in the received signal conditions and automatically adjust the equalization and gain of the AFE in order to optimize the vertical opening of the received eye. In addition, this thesis presents the first clock multiplier with both a wide operating frequency range and the ability to transition between completely off and fully operational modes in under 10 cycles of the reference clock. This multiplier relies on the careful use of several injection-locked oscillators (ILOs) with an aggregate lock range of 55.7% of the 3.16-GHz centre frequency. The design of these ILOs was facilitated by the use of a new method for modeling the injection locking behaviour of oscillators. This model differs from existing techniques in the way that it relies on the simulated response of an oscillator to injected stimuli, instead of complex equations using quasi-physical parameters, to predict the behaviour of an ILO.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
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 head0.014
GPT teacher head0.245
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

Citations0
Published2013
Admission routes1
Has abstractyes

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