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Record W2005260555 · doi:10.1364/oe.22.000001

Experimental demonstration of a 10 Gb/s RSOA-based 16-QAM subcarrier multiplexed WDM PON

2013· article· en· W2005260555 on OpenAlexaff
Jonathan M. Buset, Ziad A. El-Sahn, David V. Plant

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPassive optical networkBit error rateWavelength-division multiplexingSubcarrier multiplexingSubcarrierTransmission (telecommunications)OpticsMultiplexingQuadrature amplitude modulationComputer scienceOptical amplifierElectronic engineeringPhysicsTelecommunicationsChannel (broadcasting)WavelengthOrthogonal frequency-division multiplexingLaserEngineering

Abstract

fetched live from OpenAlex

We experimentally demonstrate the performance of a 10 Gb/s subcarrier multiplexed (SCM) wavelength-division multiplexed (WDM) passive optical network (PON) using 2.5 Gbaud 16-QAM transmission signals. Digital signal processing (DSP) and square-root raised cosine (SRRC) pulse shaping enable both the uplink and downlink channels to achieve net spectral efficiencies up to 2.8 bit/s/Hz per channel using reflective semiconductor optical amplifier (RSOA)-based optical network units (ONUs) and economical 10 GHz intensity modulation and direct detection transceivers. We characterize the system's bit error rate (BER) performance over a 20 km single feeder PON with both remote continuous-wave (CW) seeding and full-duplex transmission scenarios, assuming standard forward error correction (FEC) codes.

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 score0.002
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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

Citations36
Published2013
Admission routes1
Has abstractyes

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