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Record W2567615326 · doi:10.1109/milcom.2016.7795490

A new simple Unmanned Aerial Vehicle doppler effect RF reducing technique

2016· article· en· W2567615326 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Wave Propagation Studies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRepeater (horology)Base stationDoppler effectSIGNAL (programming language)Computer scienceWirelessSignal-to-noise ratio (imaging)Limit (mathematics)Noise (video)Simple (philosophy)Electronic engineeringTelecommunicationsEngineeringPhysics

Abstract

fetched live from OpenAlex

The purpose of this paper is to present a solution to reduce the Doppler effect in wireless communication systems. As distance increases, pathloss increases too and the signal to noise ratio decreases. A major problem that affects the quality of the link is the horizon. A solution to improve signal quality is to use an Unmanned Aerial Vehicle (UAV) relaying far mobile stations to the base station. However, because of UAV's speed, Doppler frequency shift decreases the signal to noise ratio and cannot be supported by the base station for the values that are higher than the measured limit. The simple solution explained in this paper reduces dramatically the Doppler effect and makes possible the use of UAVs, as a repeater, to extend the communication even at high speed.

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 score0.496
Threshold uncertainty score0.495

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Quick stats

Citations13
Published2016
Admission routes1
Has abstractyes

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