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Record W2144628794 · doi:10.1109/jproc.2008.2008787

Low-Power Impulse UWB Architectures and Circuits

2009· article· en· W2144628794 on OpenAlexfundno aff
Anantha P. Chandrakasan, Fred S. Lee, David D. Wentzloff, Vivienne Sze, Brian Ginsburg, Patrick P. Mercier, Denis C. Daly, R. Blázquez

Bibliographic record

VenueProceedings of the IEEE · 2009
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyNational Defense Science and Engineering GraduateSemiconductor Research CorporationNational Science Foundation
KeywordsTransmitterComputer scienceRangingFrequency scalingElectronic circuitChipsetDuty cycleElectronic engineeringElectrical engineeringRadio frequencyUSBWirelessEmbedded systemChipVoltageEngineeringTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Ultra-wide-band (UWB) communication has a variety of applications ranging from wireless USB to radio frequency (RF) identification tags. For many of these applications, energy is critical due to the fact that the radios are situated on battery-operated or even batteryless devices. Two custom low-power impulse UWB systems are presented in this paper that address high- and low-data-rate applications. Both systems utilize energy-efficient architectures and circuits. The high-rate system leverages parallelism to enable the use of energy-efficient architectures and aggressive voltage scaling down to 0.4 V while maintaining a rate of 100 Mb/s. The low-rate system has an all digital transmitter architecture, 0.65 and 0.5 V radio-frequency (RF) and analog circuits in the receiver, and no RF local oscillators, allowing the chipset to power on in 2 ns for highly duty-cycled operation.

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 score0.008
Threshold uncertainty score0.026

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Citations84
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the IEEESame topicRadio Frequency Integrated Circuit DesignFrench-language works237,207