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Record W4312403979 · doi:10.1109/jlt.2022.3211466

Digital Subcarrier Multiplexing: Enabling Software-Configurable Optical Networks

2022· article· en· W4312403979 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

VenueJournal of Lightwave Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsTransceiverScalabilitySubcarrierComputer scienceMultiplexingElectronic engineeringSubcarrier multiplexingNetwork topologyMultiwavelength optical networkingComputer networkSoftware deploymentFlexibility (engineering)Wavelength-division multiplexingEngineeringOrthogonal frequency-division multiplexingTelecommunicationsOptical fiberWirelessFiber optic splitterChannel (broadcasting)

Abstract

fetched live from OpenAlex

The various topologies, traffic patterns and cost targets of optical networks have prevented the deployment of end-to-end solutions across multi-domains, and the optimization of the network as a whole. The consequent limitations in flexibility, scalability, and adaptability of optical networks will become increasingly important with new applications, such as 5G/6G. Coherent transceivers based on digital subcarrier multiplexing (DSCM) are proposed to address these current constraints. In particular, DSCM allows (i) the design of high-capacity point-to-point (P2P) and -multipoint (P2MP) optical networks; (ii) simplified aggregation with passive optics; and (iii) connections between low- and high-speed transceivers. Furthermore, DSCM-based networks reduce the number of opto-electro-opto stages, halve the number of bookended transceivers, and provide a better match for existing hub-and-spoke (H&S) traffic patterns in fast-growing and dynamic access/metro segments. A DSCM-based transceiver will pave the way for the deployment of next-generation flexible, adaptable, and scalable software-configurable optical networks. Key steps and elements to realize this solution are laid out, and promising applications outlined. The first real-time experimental results of coherent P2MP transceivers are presented.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.193
Teacher spread0.186 · 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