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A Wideband Dual-Polarized 1-bit Unit Cell for Reconfigurable Intelligent Surface Applications

2024· article· en· W4395662378 on OpenAlexaff
Jalaledin Tayebpour, Raafat R. Mansour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDiodeWidebandPhysicsBandwidth (computing)Polarization (electrochemistry)PIN diodeTopology (electrical circuits)OptoelectronicsComputer scienceOpticsElectrical engineeringEngineeringTelecommunicationsChemistry

Abstract

fetched live from OpenAlex

In this paper, a wideband 1-bit dual-polarized unit cell has been presented at Ku-band. It comprises three substrates and four metallic layers. The proposed structure uses polarization conversion technique, and out of phase characteristic of electric field in patch dominant mode to get two phase states. Using this characteristic provides the proposed structure with considerable bandwidth and accurate phase difference between two states. Two PIN diodes are used as switches for two phase states. Activating one diode for each state results in the conversion of x-polarized to y-polarized (and vice versa) incident wave with a 180°phase difference between the two states. Notably, only one control voltage suffices for both diodes, simplifying the design of the control system. The proposed structure has been simulated using CST software. Numerical results show good matching and 180°±2°phase difference between two states from 11.2 GHz -14.2 GHz with 25 % relative bandwidth. The proposed structure can be used for different beamforming, beam steering and RIS 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.265
Teacher spread0.240 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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