MétaCan
Menu
Back to cohort
Record W2963241698

Multi-port Slot Array Antenna for Millimeter-wave Direction Finding and Beam-forming Applications

2019· article· en· W2963241698 on OpenAlexaff
Mohamed K. Emara, Daniel J. King, Hoang‐Vu Nguyen, Samer Abielmona, Shulabh Gupta

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsCarleton University
Fundersnot available
KeywordsBeam waveguide antennaAntenna (radio)Antenna arrayPeriscope antennaAntenna measurementExtremely high frequencyCoaxial antennaSlot antennaPort (circuit theory)Antenna apertureElectronic engineeringOpticsEngineeringElectrical engineeringComputer scienceDipole antennaPhysics
DOInot available

Abstract

fetched live from OpenAlex

A simple multi-port antenna structure is proposed which can be used for direction finding (DF) and beam-forming applications in the receive and transmit modes, respectively. The proposed antenna offers unique functionalities in both receive and transmit modes. For DF applications in the receive mode, the beam-scanning laws of each antenna array is engineered to cover a given sector of space and the back-end of the system will feature a power sensing mechanism to monitor the power received at all ports. In the transmit mode, the proposed antenna can be used for beam-forming applications by engineering the individual port excitation and the antenna sub-arrays. The proposed antenna structure characteristics are demonstrated using full-wave simulations at 58-61 GHz based on circularly polarized slot arrays using substrate integrated waveguide (SIW) technology. Initial results show the antenna features high angle of arrival (AoA) resolution and a wide sector coverage, making it a good candidate for 5G wireless 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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.232
Teacher spread0.197 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Conference on Antennas and PropagationSame topicMicrowave Engineering and WaveguidesFrench-language works237,207