TY - GEN
T1 - Improved ADR and Initial SF Allocation in LoRaWAN Network and their Simulation on NS3
AU - Chen, Sitong
AU - Zhao, Honggang
AU - Zhang, Zhaolin
AU - Gong, Yanyun
AU - Li, Rongfeng
AU - Wang, Ling
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - LoRaWAN is a low-power wide-area network (LPWAN) protocol based on LoRa technology, which is mainly used in the field of IoT. While LoRaWAN Network can achieve long-distance, low-cost, and large-capacity wireless communication, it encounters challenges in improving the reliability, efficiency, and scalability of networks. In order to address these challenges, we specifically delve into the study of the adaptive data rate (ADR) mechanism. ADR is a crucial component that dynamically manages the data rate and transmission power of each terminal device. Additionally, we also investigate the initial allocation of spreading factors to enhance ADR's adaptability in more complex network scenarios. There are three main contributions in this paper: Firstly, we propose an improved ADR mechanism based on device average transmission cycle, which can dynamically adjust the data rate according to the transmission behavior of terminal devices, so that to reduce network congestion, increase network throughput, and enhance adaptivity to different network scenarios. Secondly, in order to further improve the performance of our ADR mechanism, we have proposed a spreading factor allocation method based on airtime, which can assign suitable spreading factors for terminal devices in the initial stage, and improve the network coverage and transmission efficiency. Finally, the improved ADR and initial SF allocation are implemented on NS3 simulation platform, and compared with other ADR mechanisms under different network traffics. The results show that our proposed ADR mechanism and initial SF allocation method can improve the performance of LoRaWAN network effectively.
AB - LoRaWAN is a low-power wide-area network (LPWAN) protocol based on LoRa technology, which is mainly used in the field of IoT. While LoRaWAN Network can achieve long-distance, low-cost, and large-capacity wireless communication, it encounters challenges in improving the reliability, efficiency, and scalability of networks. In order to address these challenges, we specifically delve into the study of the adaptive data rate (ADR) mechanism. ADR is a crucial component that dynamically manages the data rate and transmission power of each terminal device. Additionally, we also investigate the initial allocation of spreading factors to enhance ADR's adaptability in more complex network scenarios. There are three main contributions in this paper: Firstly, we propose an improved ADR mechanism based on device average transmission cycle, which can dynamically adjust the data rate according to the transmission behavior of terminal devices, so that to reduce network congestion, increase network throughput, and enhance adaptivity to different network scenarios. Secondly, in order to further improve the performance of our ADR mechanism, we have proposed a spreading factor allocation method based on airtime, which can assign suitable spreading factors for terminal devices in the initial stage, and improve the network coverage and transmission efficiency. Finally, the improved ADR and initial SF allocation are implemented on NS3 simulation platform, and compared with other ADR mechanisms under different network traffics. The results show that our proposed ADR mechanism and initial SF allocation method can improve the performance of LoRaWAN network effectively.
KW - adaptive data rate
KW - lora
KW - lorawan
KW - ns-3
UR - http://www.scopus.com/inward/record.url?scp=85184848753&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC59353.2023.10400320
DO - 10.1109/ICSPCC59353.2023.10400320
M3 - 会议稿件
AN - SCOPUS:85184848753
T3 - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
BT - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
Y2 - 14 November 2023 through 17 November 2023
ER -