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Record W3015106737 · doi:10.1109/lnet.2020.2984008

Performance Analysis for H-CRANs Under Constrained Capacity Fronthaul

2020· article· en· W3015106737 on OpenAlexafffund
Walaa Hamouda

Bibliographic record

VenueIEEE Networking Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCloud computingComputer scienceMonte Carlo methodHigh data rateMillimeterExtremely high frequencyElectronic engineeringStochastic geometrySpace (punctuation)TelecommunicationsEngineeringWirelessPhysicsOpticsMathematicsStatistics

Abstract

fetched live from OpenAlex

In this letter, we investigate the impact of the capacity-limited hybrid millimeter waves/free space optical fronthaul on the performance of the heterogeneous cloud radio access network. By adopting stochastic geometry, analytical expressions for the average user data rate and Rate Coverage are derived, which are used to shed light on the impact of fronthaul capacity. Finally, Monte Carlo simulations are introduced to assess the accuracy of the analytical findings. In addition, the simulation results show that different biasing factors should be adopted for the different remote radio heads with different fronthaul capacities for a better Rate Coverage.

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)0.002
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.225
Teacher spread0.178 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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