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Record W2083421305 · doi:10.1117/12.472897

Dispersion-induced signal distortion in cascaded OADMs

2003· article· en· W2083421305 on OpenAlexaff
Haiqing Wei, Hwan J. Jeong, Aly F. Elrefaie, David V. Plant

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsOptical add-drop multiplexerDispersion (optics)Wavelength-division multiplexingOffset (computer science)Optical filterMultiplexerOptical performance monitoringChannel spacingOpticsComputer scienceModal dispersionBandwidth (computing)Electronic engineeringMultiplexingTelecommunicationsOptical fiberDispersion-shifted fiberPhysicsEngineeringWavelengthFiber optic sensor

Abstract

fetched live from OpenAlex

The optical add/drop multiplexer (OADM) is an important device in modern optical networks. Optical filters in OADMs often introduce group-velocity dispersion (GVD) and/or slope of GVD, the accumulation of which could distort the signals significantly. A computer model is built for commercial filters, accounting for the filtering gain and dispersion characteristics. When the model is incorporated into a network simulator, the filter dispersion is found to severely limit the number of OADMs that may be cascaded when transmitting 40Gb/s WDM signals with a channel spacing of 100GHz. As such high spectral efficiency difficult to achieve, the next considerations would be to transmit 40Gb/s over 200GHz channel spacing, or 10Gb/s over 50GHz channel spacing. The dispersion problem is mitigated, but still an un-negligible factor of limitation. For a large OADM network size, low-dispersion filters should be used, or a proper dispersion compensator is needed to offset the filter dispersion.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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 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

Citations1
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOptical Network TechnologiesFrench-language works237,207