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Record W3011661351 · doi:10.1109/jlt.2020.2982378

Experimental Demonstration of 600 Gb/s Net Rate PAM4 Transmissions over 2 km and 10 km with a 4-λ CWDM TOSA

2020· article· en· W3011661351 on OpenAlex
Zhenping Xing, Meng Xiang, Eslam El‐Fiky, Xueyang Li, Md. Ghulam Saber, Luhua Xu, Ping-Chiek Koh, David V. Plant

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

VenueJournal of Lightwave Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsBit error rateTransmitterSymbol rateWavelength-division multiplexingElectronic engineeringIntersymbol interferencePulse-amplitude modulationModulation (music)Equalization (audio)Transmission (telecommunications)Forward error correctionPhysicsComputer scienceOpticsTelecommunicationsWavelengthEngineeringPulse (music)DetectorChannel (broadcasting)

Abstract

fetched live from OpenAlex

We propose to introduce a controlled amount of inter-symbol interference (ISI) during pulse shaping in a high symbol rate intensity modulation direct detection (IM/DD) system to increase the alternating current (AC) power of the received electrical signal after photo-detection and transimpedance amplification. We experimentally demonstrate high-speed 4-level pulse amplitude modulation (PAM4) transmissions with a 4-λ coarse wavelength division multiplexing (CWDM) transmitter optical sub-assembly (TOSA) using the proposed scheme. The intentionally introduced ISI is mitigated using either transmitter-side Tomlinson Harashima precoding (THP) or receiver-side feed forward equalization (FFE) aided with a 2-tap post filter and maximum likelihood sequence estimation (MLSE). Both methods enable 4 × 81 Gbaud PAM4 transmission over 2 km of single mode fiber (SMF), with a bit error rate (BER) below the 7% overhead hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> , which corresponds to a net rate of >600 Gb/s. We also explore the limit of our system at 10 km. The result shows that an aggregated net rate of 600 Gb/s excluding the HD-FEC overhead can still be achieved by loading different symbol rates onto different wavelength channels.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.545

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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