Optimizing the Energy Consumption Level in LoRaWan Networks

Abstract

Long range wide area network (LoRaWAN) is a type of Low Power Wide Area (LPWA) technologies, which is designed to support long-range communication with low data rates and low power consumption requirements. LoRaWAN consists of many nodes that sense the environment and send their measurements to the gateway, which in turn directs the received data to the network server to process the collected data. Each one of these nodes is configured using five transmission parameters, (the spreading factor (SF), center frequency (CF), bandwidth (BW), coding rate (CR), and transmission power (TP). The optimal selection of the values plays a vital role in providing an efficient and energy preserving network implementation. In this paper, an algorithm that selects the optimal transmission power for each node in the network depending on the receiver sensitivity and the path loss of the communication link between the node and the gateway is developed by utilizing the Reinforcement Learning algorithm that is used to choose the best value of spreading factor. The simulation results of our proposed algorithm showed a significant decrease in the consumed power in the network compared with the other techniques in literature.