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Record W3131994289 · doi:10.1109/lawp.2021.3061281

Array of Arrays: Optimizing Phased Array Tiles

2021· article· en· W3131994289 on OpenAlexaff
Ahmed Shehata Abdellatif, Wenyao Zhai, Hari Krishna Pothula, Morris Repeta

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsHuawei Technologies (Canada)
Fundersnot available
KeywordsPhased arrayArray data structurePhased-array opticsComputer scienceBeamformingScalabilityMultiplication (music)Electronic engineeringReflective array antennaSensor arrayRadiation patternMaterials scienceEngineeringOptoelectronicsAcousticsPhysicsTelecommunicationsAntenna (radio)Slot antenna

Abstract

fetched live from OpenAlex

This letter discusses some of the challenges for realizing large millimeter-wave phased array antennas using multiple scalable arrays (tiles). The letter uses the radiation pattern multiplication and the array of arrays concepts to analyze the effect of the tiling gap on the large array radiation pattern. Different techniques to mitigate the performance deterioration due to the tiling gap are proposed and analyzed. The proposed methods use either the elements’ spacing, or the amplitude excitation to minimize the tiling impact on the array performance.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.701

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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 teacher head, 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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

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