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Record W2164630989 · doi:10.1109/tap.2010.2090487

Experimental Characterization of UWB Beamformers Based on Multidimensional Beam Filters

2010· article· en· W2164630989 on OpenAlex

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

VenueIEEE Transactions on Antennas and Propagation · 2010
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBeamformingComputer scienceElectronic engineeringSmart antennaAntenna (radio)Bit error rateChannel (broadcasting)Antenna arrayFilter (signal processing)Spatial filterComputational complexity theoryAdaptive beamformerAcousticsAlgorithmTelecommunicationsDirectional antennaPhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Ultrawideband (UWB) communication systems can benefit significantly by employing adaptive spatial filtering, or beamforming, using an array of UWB antenna elements. Previously, the authors have reported on a multidimensional and low-complexity beamforming technique that predicted significant improvements in communication system performance based on computational models of the radio channel. Here, the authors utilize a low-complexity spatial filter in conjunction with measured UWB signals using an experimental antenna array to demonstrate a significant improvement in system bit error rate using a real UWB channel in a multi-user environment.

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 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: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.486

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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