Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Recurso digital |
| Sprache: | Englisch |
| Veröffentlicht: |
Zenodo
2026
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| Online-Zugang: | https://doi.org/10.5281/zenodo.20051347 |
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Inhaltsangabe:
- <p>This study presents a regression-based framework integrating 3GPP TR 38.901 channel models with vendor-specific equipment parameters (Nokia, Huawei, ZTE) to predict 5G link performance across diverse scenarios (0.7–60 GHz). Findings indicate that ANN and decision tree models achieve high throughput accuracy, while mixed-scenario training is essential for model generalization across urban and rural environments.</p>