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Record W1587280308 · doi:10.1109/icc.2015.7249118

Full-duplex analog WiFi transport over RSOA-based wavelength-reused digital passive optical networks

2015· article· en· W1587280308 on OpenAlexaff
Zhihui Cao, An Nguyen, Leslie A. Rusch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhase-shift keyingComputer scienceTelecommunications linkElectronic engineeringWavelength-division multiplexingDuplex (building)Bit error rateTransmission (telecommunications)Quadrature amplitude modulationPassive optical networkOptical amplifierMultiplexingPhysicsWavelengthTelecommunicationsOpticsChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

We experimentally demonstrated the transparent convergence of distributed antenna system in a digital wavelength division multiplexed passive optical network system employing reflective semiconductor optical amplifier (RSOA) at the remote antenna unit (RAU). The spurious free dynamic range and frequency response of the RSOA is measured to meet WiFi's requirements. RSOA's electrical-to-optical conversion efficiency improves significantly by down converting the WiFi signal to intermediate frequency band. By incorporating the up/down mixer in Central Office and RAU, we experimentally achieve full-duplex WiFi transmission along with 1 Gb/s downlink digital on-off-keying signal in single mode fiber up to 15 km (64QAM), 40 km (16QAM), and 60 km (QPSK) with 1 meter wireless path working in half-duplex mode. The bit-error-rate below the forward error correction threshold (2 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ) is observed in all cases whereas the 1 Gb/s digital downlink signal is error-free up to 20 km of fiber.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.749
Threshold uncertainty score1.000

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 head0.019
GPT teacher head0.233
Teacher spread0.213 · 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 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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