Simulation of mobile networks using discrete event system specification theory
Bibliographic record
Abstract
"The fourth generation (4G) of mobile telecommunication technology provides ultra-band internet access for mobile devices such as smartphones, tablets, and laptops. One of the challenges in the Long Term Evolution (LTE) 4G networks is the low data rate for cell-edge users as well as coverage gaps. In this paper, we define and evaluate models for analysis of performance of mobile networks architectures defined by 3GPP. We used the Discrete-Event System Specification (DEVS) formalism to model the mobile networks and implement the framework. The proposed model implements the deployment layout of the Base Station (BS) cellular antennas, and it manages the distribution and movement of the User Equipment (UE) devices. The model calculates the Propagation for each BS, as well as the pathloss in the links between BSs and the UEs in the range. It also computes the power received by the BS and the UE in each link. These results will be used in the design of models for Coordinated Multipoint approach in delivering faster data."--From the paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".