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Record W2096394498 · doi:10.1364/oe.20.019990

High phase noise tolerant pilot-tone-aided DP-QPSK optical communication systems

2012· article· en· W2096394498 on OpenAlexaff
Xu Zhang, Xiaodan Pang, Lei Deng, Darko Zibar, Idelfonso Tafur Monroy, Richard Younce

Bibliographic record

VenueOptics Express · 2012
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsPhase-shift keyingPhase noiseBit error rateOpticsLaser linewidthKeyingComputer scienceOptical communicationFree-space optical communicationElectronic engineeringPhysicsLaserTelecommunicationsDecoding methodsEngineering

Abstract

fetched live from OpenAlex

In this paper we experimentally demonstrate a novel, high phase-noise tolerant, optical dual polarization (DP) quadrature phase-shift keying (QPSK) communication system based on pilot-tone-aided phase noise cancellation (PNC) algorithm. Vertical cavity surface emitting lasers (VCSELs) with approximate 300 MHz linewidth are used as transmitters and local oscillators for coherent detection of optical DP-QPSK signals. The proposed system, with central wavelength at 1540.68 nm, operates at 40 Gb/s over 80 km single mode fiber (SMF) as part of a passive optical network (PON). The deployment of pilot-tone-aided PNC algorithm guarantees a bit error rate (BER) performance below the forward error correction (FEC) threshold. Moreover, we also evaluate a novel digital signal processing (DSP) algorithm for adaptive pilot tone detection.

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 science0.0010.000
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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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

Citations17
Published2012
Admission routes1
Has abstractyes

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