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Compact Spoof Surface Plasmon Polaritons Antenna Array with Rotated Elements for 5G/6G Networks

2025· article· W4417132293 on OpenAlexafffund
Behnam Mazdouri, Rashid Mirzavand

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsBeamwidthSurface plasmon polaritonAntenna arrayAntenna (radio)Compact spaceCollinear antenna arrayDipole antennaFan-beam antenna

Abstract

fetched live from OpenAlex

This paper introduces a compact antenna array leveraging spoof surface plasmon polaritons (SPP) with rotated elements on a single-layer conducting structure. The use of highly localized electromagnetic surface waves in the proposed design enables the placement of antenna elements much closer together compared to conventional antennas. This unique feature not only addresses spatial constraints but also enhances the array's compactness and efficiency, making it highly suitable for next-generation communication systems. The design achieves a maximum realized gain of 6.3 dB for a single element and 10.88 dB for a four-element array at 28 GHz. The 3 dB half-power beamwidth is reduced from 60° to 32°, demonstrating the array precise beam-steering capability. This design overcomes spatial constraints, simplifies feeding networks, enables closer antenna placement, and ensures compactness and precise beam-steering for 5G/6G and SatCom systems.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.001
Open science0.0000.000
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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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