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Record W2121504822 · doi:10.1109/jlt.2007.916586

Generation of Power-Efficient FCC-Compliant UWB Waveforms Using FBGs: Analysis and Experiment

2008· article· en· W2121504822 on OpenAlexaff
Mohammad Abtahi, Julien Magné, Mehrdad Mirshafiei, Leslie A. Rusch, Sophie LaRochelle

Bibliographic record

VenueJournal of Lightwave Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWaveformFiber Bragg gratingOpticsTime domainFrequency domainOptical fiberNoise (video)PhotodetectionElectronic engineeringMaterials scienceEngineeringComputer sciencePhysicsElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

In this paper, we design, analyze, and demonstrate experimentally U.S. Federal Communications Commission (FCC)- compliant power-efficient ultrawideband (UWB) waveforms generated by optical pulse shaping. The time-domain pulse shape is written in the frequency domain, and a single-mode fiber performs the frequency-to-time conversion. The waveform is inscribed in the frequency domain by the fiber Bragg grating (FBG). A significant challenge for this approach is elimination of an unwanted, positive rectangular pulse superimposed on the desired waveform. Our innovative use of balanced photodetection eliminates this pedestal, assuring compliance with the FCC mask at low frequency. Three UWB pulses with duration of 0.3,0.6, and 1.2 ns are designed and tested experimentally. Whereas an excellent match between the optimized and measured pulses is achieved for the simpler, shorter duration waveforms, the noise in the fabrication process of FBGs limits the generation of the more complex, longer duration waveforms.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.259
Teacher spread0.222 · 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

Citations76
Published2008
Admission routes1
Has abstractyes

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