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Record W2153438840 · doi:10.1109/vetecf.1999.801487

Analytical calculation of outage probability for a general cellular mobile radio system

2003· article· en· W2153438840 on OpenAlexaff
S.J. Grant, J.K. Cavers

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsFadingPath lossComputer scienceShadow mappingMonte Carlo methodComputationOutage probabilityCoverage probabilityMeasure (data warehouse)Cellular radioLog-distance path loss modelChannel (broadcasting)AlgorithmSimple (philosophy)Spatial correlationMobile radioCellular networkChannel capacityMathematicsTelecommunicationsBase stationStatisticsWirelessArtificial intelligenceData mining

Abstract

fetched live from OpenAlex

Outage probability in the presence of fading, shadowing, and path loss is a useful measure of the capacity of a cellular mobile radio system. Due to the complicated nature of the spatial average, though, previous capacity studies have resorted to numerical techniques such as Monte Carlo simulation. In this paper, we develop a fully analytical and computationally straightforward technique for the computation of outage probability through a simple, yet accurate, geometric approximation in the spatial average. An attractive feature of the technique is that it does not rely upon a hexagonal cell layout, thus enabling the study of more generalized systems in which the co-channel cells are of arbitrary size and location.

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)0.002
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.299
Teacher spread0.260 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

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