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Record W2017201505 · doi:10.1109/jlt.2014.2364987

A Silicon Photonic Integrated Packaged Coherent Receiver Front-End For Soft-Decision Decoding

2014· article· en· W2017201505 on OpenAlexafffund
Meer Sakib, Mohammed Shafiqul Hai, Odile Liboiron-Ladouceur

Bibliographic record

VenueJournal of Lightwave Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill UniversityCiena (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase-shift keyingFront and back endsDecoding methodsSilicon photonicsKeyingPhotonicsElectronic engineeringPhotonic integrated circuitBit error rateCMOSComputer scienceForward error correctionOptoelectronicsEngineeringPhysicsTelecommunications

Abstract

fetched live from OpenAlex

In this paper, a packaged integrated coherent receiver and optical front-end for soft decision based on 25 Gbaud/s quadrature phase-shift keying (QPSK) is investigated for on-chip applications. The front-end consists of a 90° hybrid, balanced photodetectors, and unbalanced couplers monolithically integrated in a CMOS compatible silicon-on-insulator technology. The silicon photonic device is packaged onto a ceramic substrate with RF and dc connectors. The proposed front-end is an example of integration of system on chip. The integrated solution is able to provide 6.2 dB performance improvements over uncoded system without error correction. The front-end outperforms optical system with hard-decision forward error correction by 2.2 dB at the BER of 10-7.

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)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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