Kaur Gagandeep, Balyan Vipin, Gupta Sindhu Hak
Department of Electronics and Communication Engineering, Amity University, Sector-125, Noida, India.
Department of Electrical, Electronics and Computer Engineering, Cape Peninsula University of Technology, Cape Town, South Africa.
Sci Rep. 2025 Mar 22;15(1):9902. doi: 10.1038/s41598-025-95138-z.
LoRa being an open standard has fascinated the research community due to its promising features to support IoT applications. LoRa fulfils all the requirements of low power, delay tolerance, long transmission range and scalability of the application nodes in the IoT concept. The duty cycle limitations imposed by LoRaWAN hinder the overall performance of the network. The network performance declines due to increasing in several devices communicating through the same channel, thereby degrading the network efficiency. Certain IoT deployments such as monitoring and control applications require low latency and extended network lifetime. Aspiring to attain efficient network performance, the current work proposes a nature-inspired low duty cycle MAC algorithm using the concept of the golden ratio (GR) approach to optimize the duty cycle of the LoRa network. Further, PSO algorithms have also been utilized to validate the performance of the proposed algorithm. The simulation results unveil that the proposed method outperforms the PSO algorithm by reducing the latency and power consumption by 26% and 12% respectively and extending the network lifetime by 14% as compared to the DC constraint approach.
由于其在支持物联网应用方面具有诸多 promising 特性，LoRa 作为一种开放标准吸引了研究界的关注。LoRa 满足了物联网概念中应用节点的低功耗、延迟容忍、长传输距离和可扩展性等所有要求。LoRaWAN 施加的占空比限制阻碍了网络的整体性能。由于通过同一信道通信的设备数量增加，网络性能下降，从而降低了网络效率。某些物联网部署，如监测和控制应用，需要低延迟和延长网络寿命。为了实现高效的网络性能，当前的工作提出了一种受自然启发的低占空比 MAC 算法，该算法使用黄金分割率（GR）方法的概念来优化 LoRa 网络的占空比。此外，还利用粒子群优化（PSO）算法来验证所提算法的性能。仿真结果表明，与直流约束方法相比，所提方法分别将延迟和功耗降低了 26%和 12%，并将网络寿命延长了 14%，性能优于 PSO 算法。
