在亚马逊地区物联网网络规划的LoRa技术传播模型
Wirlan G Lima1, Andreia V R Lopes2, Caio M M Cardoso1
1Computer and Telecommunications Laboratory (LCT), Institute of Technology (ITEC), Federal University of Pará (UFPA), Belém 66075-110, Brazil.
Sensors (Basel, Switzerland)
|March 13, 2024
概括
这项研究模拟了亚马逊地区的LoRaWAN传播损失,用于物联网 (IoT) 网络. 一个新的密集植被模型提高了准确性,这对于在具有挑战性的地形上部署移动物联网至关重要.
科学领域:
- 电信工程 电信工程 电信工程
- 无线通信系统无线通信系统
- 环境无线电科学 环境无线电科学
背景情况:
- 由于亚马逊地区的地形复杂,在亚马逊地区部署无线网络面临着独特的挑战.
- 低功耗广域网 (LPWAN) 对于偏远地区的物联网 (IoT) 应用至关重要.
研究的目的:
- 为亚马逊地区的LoRaWAN (915 MHz) 开发和验证大规模传播损失模型.
- 为了促进河边社区移动物联网网络的规划.
- 评估LoRa物理层 (PHY) 通信的通道质量.
主要方法:
- 在河岸进行了收到信号强度指示 (RSSI) 和信号对噪声比 (SNR) 的广泛现场测量.
- 配备了经验性近距离 (CI) 和浮式拦截 (FI) 传播模型,用于向上链路路径损失.
- 将CI,FI和Okumura-Hata模型进行比较,并引入了密集植被的新模型.
- 分析收到的数据包速率统计,以评估频道质量.
主要成果:
- CI和FI模型的表现相似;一个新的拟议模型在密集植被场景中表现出更高的准确性.
- 与Okumura-Hata相比,新模型实现了较低的根平均平方误差 (RMSE),特别是在扩散因子9 (SF9) 时.
- 确定了945m的半径覆盖值,考虑到终端节点的移动性.
结论:
- 拟议的传播模型提高了在密集植被的亚马逊环境中无线电损失预测的准确性.
- 结果为优化在具有挑战性的地形上基于LoRaWAN的物联网网络部署提供了关键数据.
- 该研究支持在偏远的河社区有效规划弹性物联网连接.
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