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Record W4416859494 · doi:10.1049/icp.2025.3342

Design of an UWB antenna with WLAN band notch characteristic

2025· article· en· W4416859494 on OpenAlexaff
Shenxu Wang, Qingsheng Zeng, Yuan He, Jiahao Sun, Jiarui Chen, Zhaohui Yang, Zhuo Li

Bibliographic record

VenueIET conference proceedings. · 2025
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsCommunications satelliteAntenna (radio)Electromagnetic compatibilityElectromagnetic interferenceImpedance matchingBroadbandFrequency bandRadarAvionicsUltra-wideband

Abstract

fetched live from OpenAlex

This paper presents an Ultra-Wideband miniaturized antenna with WLAN band notch characteristics, measuring only 22 mm×13 mm×0.8 mm, and achieves UWB operating characteristics of 4.12-18 GHz through optimization of the M-shaped multi-branch coupling slot structure. At 4.52 GHz, 9.68 GHz and 13.16 GHz, the S11 achieves excellent impedance matching performance of -28.5 dB, -37.88 dB and -24.4 dB respectively. Its wideband characteristics can be applied to satellite communications (C-band, 4-8 GHz) and military radar systems (X-band, 8-12 GHz) and space radio communication (Ku band, 12-18 GHz) and other fields. With a specially designed notch function, the antenna achieves active signal suppression in the 5.8 GHz (5.030-5.835 GHz) band where the WLAN operates, effectively avoiding co-frequency interference with the WLAN system. This antenna demonstrates its unique application value in multi-band integrated systems and electromagnetic compatibility scenarios, as well as in scenarios such as IoT devices, medical electronics, avionics systems, satellite relay communication systems, and military equipment that requires covert communication, which need to operate independently in complex electromagnetic environments.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.628

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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