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Record W2077990300 · doi:10.1109/icassp.2002.5745147

SNR-independent velocity estimation for mobile cellular communications systems

2002· article· en· W2077990300 on OpenAlex
Wei Sheng, Steven D. Blostein

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 International Conference on Acoustics Speech and Signal Processing · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsEstimatorComputer scienceFadingAutocorrelationBandwidth (computing)WirelessMonte Carlo methodMobile radioMobile telephonyDoppler effectAlgorithmTelecommunicationsStatisticsMathematicsChannel (broadcasting)Physics

Abstract

fetched live from OpenAlex

Knowledge of the velocity of a mobile terminal is useful for a variety of radio resource management functions being contemplated for future wireless communications systems. Currently, the radial component of velocity of a mobile terminal can be inferred from estimating the maximum Doppler fading bandwidth. Unfortunately, the practicality of current methods are limited since they require an estimate of the signal-to-noise ratio (SNR) of the link. In this paper, we propose two novel autocorrelation function (ACF) based velocity estimators. These estimation methods are then extended to estimate mobile velocity without requiring knowledge of the SNR of the link. Monte-Carlo simulation of the proposed estimators are provided and compared to that of Sampath and Holtzman [1].

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.749

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 science0.0010.000
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 head0.063
GPT teacher head0.308
Teacher spread0.245 · 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