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Record W4243932163 · doi:10.1002/wcm.540

Polarization filtering for narrowband interference suppression in ultra‐wideband communications

2007· article· en· W4243932163 on OpenAlexaff
Xingpeng Mao, J.W. Mark

Bibliographic record

VenueWireless Communications and Mobile Computing · 2007
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNarrowbandBand-stop filterComputer sciencePolarization (electrochemistry)Filter (signal processing)Spread spectrumTime-hoppingDirect-sequence spread spectrumTelecommunicationsPhysicsElectronic engineeringBandwidth (computing)Low-pass filterCode division multiple accessEngineeringChemistryPulse-amplitude modulation

Abstract

fetched live from OpenAlex

Abstract To suppress narrowband interference (NBI) in an ultra‐wideband (UWB) communications environment, a null phase‐shift polarization (NPSP) filter is proposed. The proposed NPSP filter is a combination of a linear polarization‐vector transformer (PVT), a conventional single notch polarization (SNP) filter, and an amplitude and phase compensator (APC). The NBI, which has polarized states different from those of the UWB, can be suppressed completely and the UWB signal can be recovered without distortion if the polarized states can be estimated exactly. Analytical and simulation results indicate that the signal‐to‐interference ratio (SIR) can be improved effectively after NPSP filtering. The proposed NPSP filter can be implemented in a time‐hopping spread spectrum (TH‐SS) or a direct‐sequence spread spectrum (DS‐SS) UWB system. Copyright © 2007 John Wiley & Sons, Ltd.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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