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Increasing Reliability of Terahertz Communication Links Using Onboard Fiber Connectivity

2020· article· en· W3011685994 on OpenAlexaff
Kathirvel Nallappan, Yang Cao, Guofu Xu, Hichem Guerboukha, Chahé Nerguizian, Maksim Skorobogatiy

Bibliographic record

Venue2020 10th Annual Computing and Communication Workshop and Conference (CCWC) · 2020
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTerahertz radiationMaterials scienceWirelessOptoelectronicsFiberCommunications systemTransmission (telecommunications)Electronic engineeringComputer scienceReliability (semiconductor)Optical communicationTelecommunicationsPower (physics)EngineeringPhysics

Abstract

fetched live from OpenAlex

Terahertz (THz) band is the next frontier for the ultra-high-speed communication systems. Currently, most of communications research in this spectral range is focused on wireless systems, while waveguide/fiber-based links have been less explored. Although free space communications have several advantages, the fiber-based communications provide superior performance in certain short-range communication applications. In this work, we study the use of subwavelength dielectric THz fibers for information transmission. Particularly, we use polypropylene-based rod-in-air subwavelength dielectric THz fibers of various diameters (0.57-1.75 mm) to study link performance as a function of the link length of up to ~10 m, and data bitrates of up to 6 Gbps at the carrier frequency of 128 GHz. Furthermore, we compared the power budget of the rod-in-air subwavelength THz fiber-based links to that of free space communication links and we demonstrate that fiber links offer an excellent solution for various short-range applications.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.032
GPT teacher head0.258
Teacher spread0.226 · 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 designSimulation or modeling
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

Citations2
Published2020
Admission routes1
Has abstractyes

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