MétaCan
Menu
Back to cohort

Dual-Polarized High-Isolation Dielectric Resonator Antenna for Full-Duplex mMIMO

2024· article· en· W4402834313 on OpenAlexaff
Yuanzhe Gong, Tho Le‐Ngoc

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsMcGill University
Fundersnot available
KeywordsDual (grammatical number)DielectricDielectric resonator antennaIsolation (microbiology)Duplex (building)Materials scienceCoaxial antennaAntenna (radio)ResonatorComputer scienceDipole antennaOptoelectronicsElectronic engineeringTelecommunicationsEngineeringChemistryBioinformatics

Abstract

fetched live from OpenAlex

A dual-polarized high-isolation dielectric resonator antenna for full-duplex massive multiple-input and multiple output is proposed. The design integrates cross-polarized dual ports, utilizing two distinct mechanisms, probe feeding and aperture feeding, to enhance isolation performance. The beamforming capability and Tx-to-Rx port and beam-level isolation with monostatic and bistatic array configurations are studied. The proposed antenna element demonstrates a realized gain of 8.6 dB and a remarkable radiation efficiency of 97.7% at 3.5 GHz. In sample 1×8 array configurations, the design delivers an effective beam steering range from -60 to +60 degrees, with an average directivity and 3dB-beamwidth of 14.9 dB and 16.2 degrees, respectively. When deployed in a monostatic full-duplex array, the proposed structure achieves an average Tx-Rx port isolation of 53.8 dB. Moreover, adopting a bistatic array configuration can further enhance the average beam-level isolation to 73.4 dB, with peak beam-level isolation reaching up to 94.4 dB.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.002

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicFull-Duplex Wireless CommunicationsFrench-language works237,207