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Record W3088883636 · doi:10.1002/mop.32668

Frequency agile multiple‐input‐multiple‐output antenna design for <scp>5G</scp> dynamic spectrum sharing in cognitive radio networks

2020· article· en· W3088883636 on OpenAlex
Rifaqat Hussain, Muhammad U. Khan, Naveed Iqbal, Eqab Almajali, Saqer S. Alja’afreh, U. M. Johar, Atif Shamim, Mohammad S. Sharawi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCognitive radioFrequency agilityVaricapAntenna (radio)MIMOElectronic engineeringComputer scienceGround planeReconfigurable antennaElectrical engineeringEngineeringTelecommunicationsOmnidirectional antennaPhysicsAntenna efficiencyWirelessCapacitanceChannel (broadcasting)

Abstract

fetched live from OpenAlex

Abstract In this work, 2‐element slot‐based frequency reconfigurable (FR) multiple‐input‐multiple‐output (MIMO) antenna design antenna with a very wide‐sweep is proposed for dynamic spectrum sharing (DSS) in 5G technologies. FR is achieved using varactor diode with frequency tuning range from 1655 to 2605 MHz. The design is a low profile with planar structure having a single element footprint of 19.5 × 20 mm 2 . The two slot antenna elements of the MIMO configuration are etched out from a ground (GND) plane of dimensions of 60 × 120 mm 2 . The proposed antenna is narrow‐band and hence it is suitable for RF front‐end in the 5G‐enabled DSS in cognitive radio (CR) 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.

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 score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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