MétaCan
Menu
Back to cohort
Record W4226434157 · doi:10.1109/jlt.2022.3169704

Outage Probability Due to PDL Using Threshold Exceedances: Implications of DD-LMS Equalization and Inter-Channel Fiber Nonlinearities

2022· article· en· W4226434157 on OpenAlexafffund
John C. Cartledge, Ahmed I. Abd El-Rahman

Bibliographic record

VenueJournal of Lightwave Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMathematicsBit error rateQuadrature amplitude modulationRoot mean squarePhase-shift keyingOpticsPhysicsElectronic engineeringStatisticsEngineeringDecoding methods

Abstract

fetched live from OpenAlex

The outage probability due to polarization dependent loss (PDL) is estimated using the method of threshold exceedances for a multi-channel transmission model that includes i) decision-directed least-mean-square equalization to partially compensate PDL, ii) the dominant fiber nonlinear effects of cross-phase modulation and cross-polarization modulation, and iii) transceiver noise. The outage probability is defined in terms of the bit-wise achievable information rate (BW-AIR) being less than a threshold value for the generalized mutual information determined by the forward error correcting code rate. The root mean square error between the mean excess function and a theoretical fit to it is used for the critical step of determining the threshold below which the BW-AIR data is represented by the generalized Pareto distribution. The applicability of the method of threshold exceedances is demonstrated for 32 Gbaud, dual-polarization 64-ary quadrature amplitude modulation with a uniform constellation.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.261
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Lightwave TechnologySame topicOptical Network TechnologiesFrench-language works237,207