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Record W2131776754 · doi:10.1109/vetecf.2008.83

Impact of the Angular Velocity on the Signals Spectrum and Performance of Antenna-Array Receivers

2008· article· en· W2131776754 on OpenAlexaff
Mamadou Abdoulaye Diop, Karim Cheikhrouhou, Sofiène Affes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsWidebandAntenna (radio)Doppler effectContext (archaeology)Antenna arrayAcousticsTransmission (telecommunications)Computer scienceAngular velocityPhysicsTelecommunicationsElectronic engineeringOpticsEngineeringGeology

Abstract

fetched live from OpenAlex

Tremendous effort was previously made to estimate the location of moving sources with large angular velocities. However, to the best of our knowledge, no previous work has thoroughly investigated the effect of the combined angular velocity and mobile speed on the spectrum of the signal received by an antenna-array. In this contribution, we address this issue in the particular context of wideband CDMA transmission. We first show both by theoretical development and by simulations that the maximum frequency shift is the sum of the conventional Doppler term and a new term due to angular speed and that it is a linear function of both. We also show that the additional frequency shift due to the angular speed increases channel identification errors and thereby degrades the performance of antenna-array receivers. This performance loss becomes even higher at a larger number of antennas in the array.

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)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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 designSimulation or modeling
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
Published2008
Admission routes1
Has abstractyes

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