| 标 题： |
A Data-Based Cell Load Model for Efficient Network Simulation
基于数据的蜂窝负载模型：用于高效网络仿真 |
| 作 者： |
Philip Schwarzinger
Agnes Fastenbauer
Lukas Eller
Philipp Svoboda
Markus Rupp |
| 关键词： |
5G [5G]
6G [ 6G]
Campus networks [ 校园网络]
Non-public networks [ 非公共网络]
Monitoring data [ 监控数据] |
| 出版年： |
2024 |
| 文集名： |
66th International Symposium ELMAR
第66届国际ELMAR研讨会 |
| 会议名： |
66th International Symposium ELMAR
第66届国际ELMAR研讨会 |
| 届 次： |
66th |
| 摘 要： |
Campus networks are shown to be able to offer service guarantees for specific user groups. However, investigations on the user throughput of campus users are missing in literature. In order to fill this gap, an efficient cell load model is developed. For this, we verify an existing model for the number of connected users to a cell in a mobile network. We then use previously proposed cell load models, in combination with the generation of the number of connected users, to offer an computationally efficient way to generate realistic cell load values. With the cell load model, simulations are performed showing that a campus cell can increase the user throughput compared to the public network if the campus cell transmit power is sufficiently high.
研究表明，校园网络能够为特定用户群体提供服务保障。然而，目前文献中关于校园用户吞吐量的研究仍较为缺乏。为弥补这一空白，我们开发了一种高效的蜂窝负载模型。为此，我们验证了现有移动网络中一个蜂窝连接用户数量的模型，随后结合先前提出的蜂窝负载模型与连接用户数量的生成方法，提出了一种计算效率高、可生成真实蜂窝负载值的方案。通过该蜂窝负载模型进行仿真后发现，若校园蜂窝的发射功率足够高，其用户吞吐量可高于公共网络。 |
| 中文内容为网络AI翻译，专业术语未必准确，仅供参考。 |
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