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Sub-THz Compact On-Chip Dipole Antennas for 6G Application

2024· article· en· W4402980155 on OpenAlexaff
V. Aparna, Samiyalu Usurupati, Immanuel Raja, Chinmoy Saha, Yahia M. M. Antar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsDipole antennaTerahertz radiationChipDirectional antennaDipoleOptoelectronicsElectrical engineeringComputer scienceElectronic engineeringMaterials sciencePhysicsAntenna (radio)Engineering

Abstract

fetched live from OpenAlex

Two separate designs of a meandered sub-THz dipole antenna having potential for 6G application on a commercial 65 nm CMOS are presented in this article. Meandering of the antenna reduces the length of the antenna and hence the chip area. Widening the dipole arms without violating the design rule checks (DRC) of the CMOS foundry increases the impedance bandwidth. A 1-strip meandered on-chip dipole antenna occupies an area of$554 \mu \mathrm{m} \times 60 \mu \mathrm{m}$resulting in 32.4 % of fractional$S_{11}$bandwidth ranging from 83.5-115.8 GHz with a gain of -2.9 dBi at 100 GHz. A 2-strip meandered on-chip dipole results in 38.2 % of fractional$S_{11}$bandwidth ranging from 78.2-115.2 GHz with a gain of -2.5 dBi at 100 GHz while occupying a silicon area of$582 \mu \mathrm{m} \times 58 \mu \mathrm{m}$. The proposed on-chip dipole antennas are good candidates for 6G sub-THz communication 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.241
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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