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Record W3160405861 · doi:10.1109/tap.2021.3076674

Nonreciprocal-Beam Phased-Array Antennas Based on Transistor-Loaded Phase Shifters

2021· article· en· W3160405861 on OpenAlexaff
Reza Karimian, Sajjad Taravati, Mansoor Dashti Ardakani, Shahrokh Ahmadi, Mona Zaghloul

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversité du Québec à MontréalInstitut National de la Recherche ScientifiqueUniversity of Toronto
Fundersnot available
KeywordsPhased arrayAntenna (radio)Antenna arrayReflective array antennaDirectional antennaPhased-array opticsBeam (structure)OpticsPhase shift moduleElectrical engineeringPhysicsEngineeringSlot antennaInsertion loss

Abstract

fetched live from OpenAlex

This study presents a nonreciprocal-beam phased-array antenna constituted of phase-gradient patch radiators integrated with transistor-based nonreciprocal phase shifters. Such an antenna exhibits different beams for transmission and reception states. The proposed phased-array antenna provides power amplification for both transmission and reception states, which is of paramount importance in most practical applications. In addition, in contrast to the recently proposed time-modulated antennas, the proposed nonreciprocal-beam phased-array antenna introduces no undesired time harmonics and unwanted frequency conversion, which requires no radio frequency bias signal. Furthermore, the nonreciprocal phased-array antenna is lightweight and is amenable to integrated circuit fabrication. The transmission and reception beam angles, the beam shapes, and the power amplification level may be easily tuned by changing the direct current (dc) bias of the transistors and phase of the passive phase shifters. Such a nonreciprocal-beam phased-array antenna is expected to find military and commercial applications.

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 score0.005

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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

Citations31
Published2021
Admission routes1
Has abstractyes

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