Signal Quality Measurement (SQM) dataset

To illustrate the impact of the obstacles, we consider indoor and outdoor scenarios. We consider the Department of Computer Science and Engineering, IIT(BHU) buildings as indoor buildings and the railway platform as an outdoor scenario. Here, we use single-channel LG in our experiment. The distance between LNs and LG varies from 5 to 50 meters. The floor map illustrates the walls, doors, and windows between LNs and LG. We consider railway stations for the outdoor environment. The outdoor environment did not consist of obstacles between LNs and LG. The number of LNs varies from 5 to 100 meters, and the number of LNs 1 to 5. Figure 1 illustrates the example scenario of an end-to-end LoRa Network with an inference problem.

为阐释障碍物的影响，本研究考虑了室内与室外两种场景。室内场景选取印度理工学院（BHU）计算机科学与工程学院的建筑，而室外场景则选取铁路站台。在本实验中，我们采用单通道LG进行测试。LNs与LG之间的距离介于5至50米之间。楼层平面图描绘了LNs与LG之间的墙壁、门和窗户。室外环境考虑了火车站，LNs与LG之间不存在障碍物。LNs的数量介于5至100米之间，且数量在1至5之间不等。图1展示了端到端LoRa网络在推理问题中的示例场景。

搜集汇总

背景与挑战

背景概述

该数据集提供了LoRaWAN网络中信号质量的详细测量数据，包括SNR和RSSI值，覆盖不同传播因子和节点数量的场景。数据集适用于信号处理、物联网和机器学习等领域的研究，特别关注室内和室外环境下的信号传播特性。