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Record W1994029329 · doi:10.1109/vtcf.2006.62

Comparison of Expected Performance on B3G Spread Spectrum Mobile Radio Links at 1.9 and 5.8 GHz Based on Propagation Measurements

2006· article· en· W1994029329 on OpenAlexaff
Robert Bultitude, Mi Kyung Han, Nikhil Adnani, Roshdy M. Hafez

Bibliographic record

VenueIEEE Vehicular Technology Conference · 2006
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsCommunications Research Centre CanadaCarleton University
Fundersnot available
KeywordsInterference (communication)Channel (broadcasting)Computer scienceRadio spectrumSpread spectrumElectronic engineeringFrequency bandTelecommunicationsBinary numberCo-channel interferenceNoise (video)Radio channelEngineeringMathematicsBandwidth (computing)Artificial intelligence

Abstract

fetched live from OpenAlex

For planning purposes, there is a need for the evaluation of expected performance on mobile radio links in anticipated new frequency bands and comparison of results with 2 GHz band performance estimates evaluated by the same methods. To that end, this paper reports the application of a semi-analytical technique to estimate average binary phase shift keyed direct sequence spread spectrum mobile link error rates at 1.9 and 5.8 GHz from time series of channel response estimates derived from data recorded during propagation experiments with a 5 mchps pseudo-noise channel sounder. This work is unique, as the methods used incorporate the consideration of self interference as well as random channel variations based on direct analysis of the experimentally-determined channel response estimates, rather than simplified models for either the self interference or the channel variations.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.292
Teacher spread0.252 · 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 designObservational
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

Citations1
Published2006
Admission routes1
Has abstractyes

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