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Record W2096779480 · doi:10.1109/ccece.2008.4564700

Transmission strategies for high-speed access over Category-7A copper wiring

2008· article· en· W2096779480 on OpenAlexvenueno aff
Ali Enteshari, M. Kavehrad

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsnot available
Fundersnot available
KeywordsTransmission (telecommunications)Computer scienceData transmissionReliability engineeringEngineeringTelecommunicationsComputer network

Abstract

fetched live from OpenAlex

This paper focuses on conceptual designs and demonstration of beyond 10G transmission systems for distribution of digital signals over standard Category-7A copper cable, which is an enhanced version of Category 7 cable. Although the actual implementation might not be feasible at the time of writing of this paper due to technology limitations and high production costs, we have been trying to address the technical feasibility, limitations and design of a system in a framework leading to a practical implementation in a not too distant future with the ever increasing speed of technology advances. We have demonstrated that a data rate up to 40Gbps over 100m of CAT-7A is feasible with reasonable complexity. Developing 100Gb/s over 100m balanced cabling is going to be very challenging. To optimize costs, while ensuring robust and reliable performance over 100 meters and through four connections, Category 8 cabling is the most likely choice to support the emerging IEEE 100GBASE-T application. The results of our investigations indicate that 100Gbps transmission is possible over 50m of such a cable.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.228
Teacher spread0.201 · 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 designNot applicable
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

Citations9
Published2008
Admission routes1
Has abstractyes

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