A Comprehensive Analysis of LoRa Network Wireless Signal Quality in Indoor Propagation Environments

Abstract

This paper investigates how key Long-Range (LoRa) sensor network transmission parameters and the number and material composition of physical obstacles on the signal propagation path impact wireless signal transmission quality in indoor propagation environments. A dedicated test platform was developed to assess how different combinations of the LoRa transmission parameters, which include spreading factor, transmit power, transmit duty cycle, message payload size, and the quantity and material composition of physical obstacles, with the signal propagation path length influence critical signal quality indicators, specifically the signal-to-noise ratio (SNR) and the received signal strength indicator (RSSI). The developed experimental test platform was implemented for a real-world indoor LoRa network composed of LoRa end devices (DVs) and gateways (GWs), utilizing technologies such as Node-RED for service orchestration, InfluxDB for data storage, The Things Network (TTN) for LoRa wide-area network connectivity, and Grafana for data visualization. The results of the performed analyses reveal how different combinations of LoRa transmission parameters, specifically the number and material composition of physical obstacles encountered during signal transmission among the LoRa end DVs and GWs, affect wireless signal quality indicators, namely RSSI and SNR, in indoor propagation environments of LoRa sensor networks. The obtained findings contribute to the optimization of LoRa transmission parameter selection for reliable and efficient signal transmission in LoRa indoor sensor network deployment, such as in urban environments with obstacles of varying structural composition and density encountered on the communication paths of different lengths between the LoRa end DVs and GWs.