MétaCan
Menu
Back to cohort
Record W2747522389 · doi:10.5555/3107979.3107980

Modeling and simulation of user mobility and handover in LTE and beyond mobile networks using DEVS formalism

2017· article· en· W2747522389 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications and Networking Symposium · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsCarleton University
Fundersnot available
KeywordsHandoverDEVSComputer scienceMobility modelComputer networkFormalism (music)Cellular networkMobility managementMobile telephonyUser equipmentDistributed computingMobile radioBase stationModeling and simulationSimulation

Abstract

fetched live from OpenAlex

User mobility and handover are two important functions in mobile networks that provide seamless connectivity of user when moving from one cell to another cell. Hence, handover and its performance are of high importance to improve the performance of mobile networks. In this study, we present a technical overview of mobility and handover management of 3GPP Long Term Evolution (LTE) and beyond mobile networks. We present an open source simulation model of user mobility and handover that allows investigating the performance of handover process within 3GPP LTE and beyond mobile networks. To model the user mobility and handover process we introduce Discrete EVent System Specification (DEVS) formalism, a flexible formal modeling and simulation methodology. We perform modeling and simulation of typical urban area propagation, with different user speed, cell radius and traffic load per cell for both homogeneous and heterogeneous mobile networks.

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.

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: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.524

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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