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New Design Technique for mm-Wave Reflecting Electromagnetic Surfaces With Varying Phase Shifts

2021· article· en· W4212851749 on OpenAlexaff
Bilel Mnasri, Halim Boutayeb, Larbi Talbi

Bibliographic record

Venue2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI) · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsReflection coefficientExtremely high frequencyVaricapReflection (computer programming)WirelessComputer scienceAntenna (radio)Printed circuit boardElectronic engineeringRelayPhase (matter)Surface waveElectrical engineeringEngineeringTelecommunicationsPower (physics)Physics

Abstract

fetched live from OpenAlex

Reconfigurable intelligent surfaces (RIS) represent a disruptive and promising relay technology for future wireless communications systems. These surfaces are expected to be implemented in scenarios having the undesired presences of obstacles or strong shadowing between the communicating systems. In these scenarios, RIS can help create favorable propagation paths, which are crucial, especially at millimeter wave frequencies. In this paper, we present the analysis and design of a new reflecting surface which is based on a periodic structure, a three-layer printed circuit board and one varactor per unit cell. Results in terms of phase and magnitude of the reflection coefficient are presented and discussed, for a structure operating around 28GHz

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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.034
GPT teacher head0.297
Teacher spread0.263 · 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
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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Same venue2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI)Same topicAdvanced Wireless Communication TechnologiesFrench-language works237,207