Experimental Evaluation of the Packet Reception Performance of LoRa

Abstract

LoRa technology is currently one of the most popular Internet of Things (IoT) technologies. A substantial number of LoRa devices have been applied in a wide variety of real-world scenarios, and developers can adjust the packet reception performance of LoRa through physical layer parameter configuration to meet the requirements. However, since the important details of the relationship between the physical layer parameters and the packet reception performance of LoRa remain unknown, it is a challenge to choose the appropriate parameter configuration to meet the requirements of the scenarios. Moreover, with the increase in application scenarios, the requirements for energy consumption become increasingly high. Therefore, it is also a challenge to know how to configure the parameters to maximize the energy efficiency while maintaining a high data rate. In this work, a complex evaluation experiment on the communication capability under a negative Signal to Noise Ratio is presented, and the specific details of the relationship between physical layer parameters and the packet reception performance of LoRa are clarified. Furthermore, we study the impact of the packet length on the packet reception performance of LoRa, and the experimental results show that when there is a large amount of data to be transmitted, it is better to choose long packets instead of short packets. Finally, considering the influence of physical layer parameters and the packet length on the packet reception performance of LoRa, the optimal parameter combination is explored, so as to propose a transmission scheme with a balanced reliability, delay, and energy consumption. This scheme is the first to consider the physical layer parameters and packet length together to study the communication transmission scheme, which reduces the communication time by 50% compared with the traditional transmission scheme and greatly reduces the energy consumption.

Spectrum Based Power Management for Congested IoT Networks

“…In order to have an estimation of the device lifetime for a given battery capacity, network configuration, and transmission frequency, we need to understand the power consumption of an IoT device during (1) initial turn-on, (2) connected state, (3) re-transmission and (4) sleep/listen state. To the best of our knowledge, literature research is more focused on optimizing energy efficiency through different scheduling sachems, which is not on solving the cause [4,5,[10][11][12]23,24]. Instead, this work is based on empirical evaluation of real deployments, which shed light on the relation between power consumption and spectrum management in congested IoT environment.…”

“…In IoT, Figure 1, generally a sensor is placed near or around the object to be monitored remotely to collect data. The collected data by sensor is included to form an Internet Protocol (IP) packet and sent to the Coordinator Node (CN) by using a transmitter in the sensor device [3][4][5]. This packet sending process should be carried out in a very short time.…”

Decentralized Adaptive Spectrum Learning in Wireless IoT Networks Based on Channel Quality Information

“…Packet losses are the main drawback for IoT [16]. Hence, packet losses cause many retransmissions at the cost of a lower battery lifetime of the end nodes and may lead to an increase of the RF (Radio Frequency) contention level.…”

A Reinforcement Learning Based Transmission Parameter Selection and Energy Management for Long Range Internet of Things

“…Another work proposed a new MAC protocol called DG-LoRa and evaluated that varying the number of gateways, channel BW, and CR improves the number of re-transmissions better than the default LoRa method [ 38 ]. The impact of the packet size on the LoRa performance was evaluated in [ 39 ]. The study aimed to balance the reliability, delay, and energy consumption of LoRa under different physical layer parameters.…”