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Spectral Efficiency of Carbon Nanotube Antenna Based MIMO Systems in the Terahertz Band

2013· article· en· W2169216872 on OpenAlexafffund
Xu Zheng, Xiaodai Dong, Jens Børnemann

Bibliographic record

VenueIEEE Wireless Communications Letters · 2013
Typearticle
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsUniversity of Victoria
FundersUniversity of Victoria
KeywordsAntenna (radio)MIMOTerahertz radiationCarbon nanotubeSpectral efficiencyDipole antennaMaterials scienceElectronic engineeringOptoelectronicsComputer scienceTelecommunicationsNanotechnologyEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

Based on the models of single walled carbon nanotubes (SWCNTs) and bundled SWCNTs antennas, we analyse the spectral efficiency of an SWCNT bundled dipole antenna based MIMO system in the Terahertz band. Two scenarios are considered: the large scale MIMO and the conventional scale MIMO. It is found that, in order to get the maximum spectral efficiency, the CNT bundle size should be optimized to obtain a tradeoff between antenna efficiency and the number of antennas for a given area. This work also takes into account the random fluctuation in the bundle size during the CNT bundled antenna fabrication which reduces the system spectral efficiency.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

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