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Record W2313116979 · doi:10.1109/tap.2014.2323410

Dual-Layer EBG-Based Miniaturized Multi-Element Antenna for MIMO Systems

2014· article· en· W2313116979 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2014
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnechoic chamberMIMOElectromagnetic reverberation chamberAntenna (radio)MiniaturizationMicrostrip antennaAcousticsElectronic engineeringComputer sciencePhysicsChannel (broadcasting)TelecommunicationsEngineeringElectrical engineeringReverberation

Abstract

fetched live from OpenAlex

A dual-layer electromagnetic band-gap (EBG) mushroom structure is proposed in this paper. Based on the concept of slow-wave propagation, this structure can reduce the size of multi-element microstrip patch antennas (MPAs) by 61%. While the mushroom inner layer aids in the antenna miniaturization, the more compact upper layer acts as a band-stop filter further reducing the mutual coupling between the miniaturized patch antenna elements, which is otherwise not possible for a single-layer EBG structure. Various 2- and 4-element miniaturized MPAs are proposed for 2.5-GHz band applications, with antenna elements closely spaced at 0.5λ and low mutual coupling levels in the range of -28 dB to -50 dB. Furthermore, the achievable multiple-input-multiple-output (MIMO) channel capacities of these miniaturized multi-antennas are analyzed using the Kronecker channel model and tested in various propagation scenarios like the anechoic chamber, reverberation chamber and indoor. It is observed that the miniaturized MPAs can provide significant gains in MIMO capacity in all the signal scattering environments and are close to the theoretical limit of i.i.d. Rayleigh fading.

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.

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: none
Teacher disagreement score0.988
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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