Research On LoRa Gateway And Networking Method Enhanced By Edge Computing

With the rapid development of the Industrial Internet of Things,hundreds of millions of wireless sensor devices are connected to the wireless network.In order to meet the connection requirements of more low-power long-distance wireless sensor devices,Long Range Radio(LoRa),as one of the Low Power Wide Area Network(LPWAN)technologies,has gradually become a hot spot in the development of wireless sensor networks.During the communication process of LoRa wireless network,the link quality is mainly affected by link interference and radio frequency parameter configuration.The traditional LoRa network cannot determine the change of the link,which leads to unreasonable resource allocation,resulting in waste of resources,reducing the network scale,and the reliability and stability of communication cannot be guaranteed.Aiming at the problems existing in the existing LoRa wireless network research,this paper designs a LoRa gateway enhanced by edge computing,builds a link quality evaluation model at the gateway to realizes real-time evaluation and monitoring of the link quality,and then adaptively updates the radio frequency parameters of the LoRa module according to the evaluation results.To realize online monitoring and display of nodes on the cloud platform.The main research contents are as follows:(1)Analysis and design of LoRa gateway functions enhanced by edge computing.The advantages of LoRa based on Chirp spread spectrum modulation in link and communication distance such as multipath,fading and interference are analyzed,and the relationship between the transmission rate,air transmission time,receiving sensitivity,etc.and radio frequency parameters of LoRa network in the process of communication is discussed.On this basis,a system architecture of a multi-module LoRa integrated gateway based on edge computing is designed,and its main functions are analyzed.(2)Research on the quality evaluation method of LoRa network link.The characteristics of LoRa links are studied from the aspects of time,space,interference,etc.According to the tested link parameter samples,the whale algorithm based on adaptive weight and search strategy is designed to optimize the link quality evaluation model of BP neural network,and the RSSI(Received Signal Strength Indicator)and the mapping relationship between SNR(Signal Noise Ratio)and PLR(Packet Loss Ratio).Compared with the link evaluation methods of other scholars,the accuracy and advantages of the prediction based on the AWOA-BP neural network method are analyzed.(3)Research on LoRa networking method enhanced by edge computing.Research the internal and external factors that affect the quality of LoRa link,and design the formula for adjusting the transmit power.The research adopts the networking method enhanced by edge computing,analyzes the characteristics and advantages of different access methods,and updates the parameters adaptively by evaluating the link quality at the LoRa gateway.Design the specific implementation method and software process of LoRa networking,and customize the communication protocol according to the existing networking protocol.(4)Test and analysis of LoRa gateway and networking method enhanced by edge computing.Verify the function of the designed LoRa network system,and test the stability and feasibility of communication between nodes,gateways and servers.Design the adaptive experiment of transmit power,observe the update curve of transmit power online according to the change of link quality,and verify the rationality of the designed spreading factor and bandwidth adaptation.Through the comparative experiments of different processing methods under external link interference,it is verified that the designed parameter adaptive algorithm can improve network performance,respond quickly to changes in link quality,and improve the reliability and robustness of communication in complex environments.