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DyLoRa: Towards Energy Efficient Dynamic LoRa Transmission Control

机译:Dylora:迈向节能动态LORA传输控制

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LoRa has been shown as a promising platform for connecting large scale of Internet of Things (IoT) devices, by providing low-power long-range communication with a low data rate. LoRa has different transmission parameters (e.g., transmission power and spreading factor) to tradeoff noise resilience, transmission range and energy consumption for different environments. Thus, adjusting those parameters is essential for LoRa performance. Existing approaches are mainly threshold based and fail to achieve optimal energy efficiency. We propose DyLoRa, a dynamic LoRa transmission control system to improve energy efficiency. The high level idea of DyLoRa is to adjust parameters to different environments. The main challenge is that LoRa has very limited data rate and sparse data, making it very time- and energy-consuming to obtain physical link properties. We show that symbol error rate is highly related to the Signal-Noise Ratio (SNR) and derive the model to characterize this. We further derive energy efficiency model based on the symbol error model. DyLoRa can adjust parameters for optimal energy efficiency from sparse LoRa packets. We implement DyLoRa based on LoRaWAN 1.0.2 with SX1276 LoRa node and SX1301 LoRa gateway and evaluate its performance in real networks. The evaluation results show that DyLoRa improves the energy efficiency by 41.2% on average compared with the state-of-the-art LoRaWAN ADR.
机译:LORA通过提供低数据速率的低功率远程通信,作为连接大规模的物联网(物联网)设备的有希望的平台。 LORA具有不同的传输参数(例如,传输功率和扩散因子),以进行不同环境的权衡噪声弹性,传输范围和能耗。因此,调整这些参数对于Lora性能至关重要。现有方法主要是基于阈值,并且未能实现最佳能源效率。我们提出达伦拉,一种动态LORA传输控制系统,以提高能源效率。 Dylora的高级思想是将参数调整到不同环境。主要挑战是,LORA具有非常有限的数据速率和稀疏数据,使得获得物理链路属性非常有时间和耗能。我们表明符号错误率与信噪比(SNR)高度相关,并导出模型以表征此功能。我们进一步基于符号误差模型导出能效模型。 Dylora可以调整从稀疏LORA数据包的最佳能量效率的参数。我们使用SX1276 LORA节点和SX1301 LORA网关实现基于Lorawan 1.0.2的Dylora,并评估其在实际网络中的性能。评价结果表明,与最先进的Lorawan ADR相比,达伦拉平均将能源效率提高了41.2%。

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