基于LoRaWAN自适应数据速率的地下无线传感网络性能评估

Adaptive Data Rate Mechanism for Network Efficiency Evaluation in LoRaWAN-based Wireless Underground Sensor Networks

摘要:

随着城镇化进程的不断加快和物联网技术的迅速进步，地下复杂土壤介质中的无线传感网络正成为新的研究热点。在此背景下，首先概述了基于LoRaWAN的地下无线传感网络基本架构和研究现状，接着搭建了网络仿真器并实现了自适应数据速率（ADR）调节机制在传感器节点端和网络服务端的2个优化算法，最后依据网络整体数据接收率和网络能耗等性能指标，分别从传感器节点的地下部署环境（土壤含水量和传感器埋藏深度）和LoRa物理层参数两方面进行了网络性能定量评估。结果表明，针对土壤这一复杂介质，ADR调节机制对LoRaWAN中的物理层参数具有较好的调节能力，该机制可为地下无线网络性能优化提供有利手段，有望大幅降低网络能耗。

Abstract:

With the continuous acceleration of urbanization and the rapid advancement of the Internet of Things technology， the study of wireless sensor networks within complex underground soils has become a new hot spot. In this paper， we first summarize the basic architecture and research status of LoRaWAN-based wireless underground sensor networks and build a network simulator to implement two optimization algorithms of adaptive data rate （ADR） mechanism at the sensor node and the network server， respectively. Furthermore， we conduct a quantitative evaluation of network performance from the aspects of the underground deployment environment （soil’s moisture content and sensor’s burial depth） and physical layer parameters of LoRa， according to the performance indicators of the overall data extraction rate and network energy consumption. The results show that for the complex soil， the ADR mechanism has a good ability to adjust the physical layer parameters of nodes in LoRaWAN-based wireless underground sensor networks， which can provide a favorable means for the performance optimization of wireless underground sensor networks， and is expected to greatly reduce the network energy consumption.