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Record W3047312875 · doi:10.1109/tap.2021.3060138

Integrated Multiport Leaky-Wave Antenna Multiplexer/Demultiplexer System for Millimeter-Wave Communication

2021· article· en· W3047312875 on OpenAlexafffund

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMultiplexingWidebandTransmission (telecommunications)Center frequencyAntenna (radio)Matching (statistics)Bandwidth (computing)Transmission lineFrequency response

Abstract

fetched live from OpenAlex

A novel application of leaky-wave antennas (LWAs) as multiplexers/demultiplexers is proposed and experimentally demonstrated in the millimeter-waveband at 60 GHz. The first application is demultiplexing of an oblique-incident free-space wideband plane wave into 2N channels using N LWAs with different beam-scanning laws. The second application is N-channel multiplexing and demultiplexing using N pairs of identical LWAs in each other's far-field, where each LWA pair is designed such that the broadside frequency is the center frequency of its respective channel. The Friis transmission equation is first used to analytically demonstrate the two applications. The LWAs are then implemented using reflection-canceling slot pairs using substrate integrated waveguide technology. The two applications are demonstrated in full-wave simulations and experimentally by conducting horn-to-LWA and LWA-to-LWA transmission measurements. The proposed LWAs provide a simple, compact, and high-efficiency multiplexing/demultiplexing solution with high-integration capability with other circuitry. Compared with conventional multiplexers, LWAs do not require matching networks and can be directly scaled to higher frequencies using the same architecture.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score1.000

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 head0.028
GPT teacher head0.220
Teacher spread0.192 · 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.

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

Citations11
Published2021
Admission routes2
Has abstractyes

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