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Record W2071392974 · doi:10.1364/oe.20.014428

Bandwidth efficient bidirectional 5 Gb/s overlapped-SCM WDM PON with electronic equalization and forward-error correction

2012· article· en· W2071392974 on OpenAlexaff
Jonathan M. Buset, Ziad A. El-Sahn, David V. Plant

Bibliographic record

VenueOptics Express · 2012
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceSubcarrier multiplexingSpectral efficiencyWavelength-division multiplexingTransceiverElectronic engineeringBandwidth (computing)TransmitterForward error correctionSubcarrierBit error rateOrthogonal frequency-division multiplexingTelecommunicationsOpticsWirelessEngineeringPhysicsChannel (broadcasting)Decoding methods

Abstract

fetched live from OpenAlex

We demonstrate an improved overlapped-subcarrier multiplexed (O-SCM) WDM PON architecture transmitting over a single feeder using cost sensitive intensity modulation/direct detection transceivers, data re-modulation and simple electronics. Incorporating electronic equalization and Reed-Solomon forward-error correction codes helps to overcome the bandwidth limitation of a remotely seeded reflective semiconductor optical amplifier (RSOA)-based ONU transmitter. The O-SCM architecture yields greater spectral efficiency and higher bit rates than many other SCM techniques while maintaining resilience to upstream impairments. We demonstrate full-duplex 5 Gb/s transmission over 20 km and analyze BER performance as a function of transmitted and received power. The architecture provides flexibility to network operators by relaxing common design constraints and enabling full-duplex operation at BER ∼ 10(-10) over a wide range of OLT launch powers from 3.5 to 8 dBm.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2012
Admission routes1
Has abstractyes

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