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Record W2884498739 · doi:10.1049/iet-opt.2018.5041

Extensive simulation of fibre non‐linearity mitigation in a CO‐OFDM‐WDM long‐haul communication system

2018· article· en· W2884498739 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Optoelectronics · 2018
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEqualiserOrthogonal frequency-division multiplexingWavelength-division multiplexingBit error rateElectronic engineeringComputer scienceTransmission (telecommunications)Context (archaeology)TelecommunicationsEngineeringWavelengthOpticsChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

In this study, a performance comparison of fibre non‐linearity mitigation is performed in the context of 10 and 20 Gb/s coherent optical orthogonal frequency‐division multiplexing and wavelength division multiplexing (CO‐OFDM‐WDM). The authors compare two regression methods based on the third‐order Volterra series and least mean square algorithm in terms of the bit error rate (BER) for different transmission distances and modulation formats. They also evaluate the BER as a function of the number of OFDM subcarriers for the Volterra‐based non‐linear equaliser (VNLE). In addition, by increasing the order of the VNLE from third‐order to fifth‐order series, a significant increase of performance is obtained for 100 Gb/s CO‐OFDM‐WDM system. Likewise, a comparison study of 16‐QAM 40 Gb/s CO‐OFDM system is performed as a function of Q‐factor for support vector machine, Volterra equaliser and linear equaliser, respectively.

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.

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 score0.028
Threshold uncertainty score0.687

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 head0.253
Teacher spread0.246 · 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