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Record W2510014190 · doi:10.1109/mwsym.2016.7540293

Dual-band millimeter-wave interleaved antenna array exploiting low-cost PCB technology for high speed 5G communication

2016· article· en· W2510014190 on OpenAlexaff
Wenyao Zhai, V. Miraftab, Morris Repeta, David Wessel, Wen Tong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsHuawei Technologies (Canada)
Fundersnot available
KeywordsStriplineMulti-band deviceLocal Multipoint Distribution ServiceBandwidth (computing)Extremely high frequencyAntenna arrayElectronic engineeringComputer scienceElectrical engineeringEngineeringAntenna (radio)TelecommunicationsWireless

Abstract

fetched live from OpenAlex

In this paper, a novel dual-band co-aperture antenna array with high bandwidth is presented. The proposed frequency bands of interest are E-band and LMDS which can work simultaneously in a dual-band mm-wave radio to achieve high throughput. The distribution network is based on the combination of Substrate-Integrated-Waveguide (SIW) and stripline technologies. These feed networks co-exist in a low-cost PCB with 4 metal layers with minimal interference. The SIW distribution network feeds slot apertures with a special offset from the center axis of the waveguides, while the stripline lines excite U-shaped patch antennas by vertical vias. A 4×4 dual-band E-band/LMDS array prototype is presented to validate the concept. The dual-band antenna array is approximately 12mm×12mm in size realized on a Rogers 4350 substrate. Measured results versus simulations have been presented and discussed. This dual-band technique can be a great candidate for the multi-Giga-bit/s (Gbps) cellular applications for 5G communication and is compatible with low cost multilayer technologies.

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 score0.682
Threshold uncertainty score0.777

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 head0.019
GPT teacher head0.213
Teacher spread0.195 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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