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Record W1922004413 · doi:10.1109/twc.2015.2450216

Stochastic Analysis of Uplink Interference in Two-Tier Femtocell Networks: Open Versus Closed Access

2015· article· en· W1922004413 on OpenAlexafffund
Wei Bao, Ben Liang

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaBell Canada Enterprises
KeywordsMacrocellFemtocellTelecommunications linkStochastic geometryComputer scienceCorrectnessInterference (communication)Computer networkUpper and lower boundsCoverage probabilityStochastic geometry models of wireless networksMathematical optimizationWireless networkTelecommunicationsWirelessMathematicsAlgorithmRadio resource managementBase stationStatisticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

We introduce a stochastic analytical framework to compare the performance of open-access and closed-access modes in a two-tier femtocell network with regard to the uplink interference and the outage at both the macrocell and femtocell levels. A stochastic geometric approach is employed as the basis for our analysis. We present numerical methods to characterize the distributions of the uplink interference and the outage probabilities. We further derive sufficient conditions for the open-access and closed-access modes to outperform each other in terms of the outage probability at either the macrocell level or the femtocell level. This leads to closed-form expressions to upper and lower bound the difference in the targeted received power between the two access modes. Simulations are conducted to validate the accuracy of the analytical model and the correctness of the bounds.

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: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.083
GPT teacher head0.346
Teacher spread0.263 · 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
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

Citations17
Published2015
Admission routes2
Has abstractyes

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