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Record W2516564827 · doi:10.1109/antem.2016.7550213

Design of compact millimeter wave massive MIMO dual-band (28/38 GHz) antenna array for future 5G communication systems

2016· article· en· W2516564827 on OpenAlexaff
Mohamed Mamdouh M. Ali, Abdel-Razik Sebak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsMIMOExtremely high frequencyBandwidth (computing)Antenna arrayAntenna (radio)Multi-band devicePhysicsAzimuthComputer scienceTelecommunicationsElectronic engineeringElectrical engineeringEngineeringOpticsBeamforming

Abstract

fetched live from OpenAlex

In this article, a compact millimeter wave massive MIMO dual-band (28/38 GHz) antenna array for future 5G communication systems is proposed. A compact high gain dual-band (28/38) series fed antenna array with size of (13× 20 mm2) is nominated to design the massive MIMO antenna system. The simulated results shows that the impedance bandwidth (S11<; -10 dB) is achieved around 28 GHz and 38 GHz with a high gain of 12.07 and 13.46 dB, respectively. The proposed six-sector base station will have 6 sub-sectors (array antennas) each covering a range of 40° and 30° at 28 and 38 GHz, respectively, in azimuth plane (θ).

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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
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 science0.0000.000
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 head0.026
GPT teacher head0.222
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 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
GenreMethods

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

Citations59
Published2016
Admission routes1
Has abstractyes

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