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Record W2152339012 · doi:10.1109/lcomm.2006.1638613

Global expansion model for mobile networks

2006· article· en· W2152339012 on OpenAlexaff
Marc St‐Hilaire, Steven Chamberland, Samuel Pierre

Bibliographic record

VenueIEEE Communications Letters · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsUMTS frequency bandsComputer scienceCore networkCellular networkGeneralizationMathematical optimizationNetwork planning and designMobile telephonyComputer networkNetwork modelDistributed computingCore (optical fiber)TelecommunicationsMobile radioArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

In this letter, we propose a global model to solve the expansion problem of universal mobile telecommunications system (UMTS) networks. Since the network expansion problem is a generalization of the network design problem, the proposed model can be used for the design of UMTS networks. The proposed model deals simultaneously with the cell, the access network and the core network planning subproblems. This global approach has the advantage of providing better results since, in general, optimal solutions to all subproblems do not provide an optimal solution to the global problem. Moreover, this model fits real life situations in which mobile users have the choice to subscribe or to leave a service providers. Numerical results are presented and analyzed

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 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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.527

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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations6
Published2006
Admission routes1
Has abstractyes

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