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利用多个网关提高 LoRaWAN 网络的能效。

Improving Energy Efficiency in LoRaWAN Networks with Multiple Gateways.

机构信息

Ecole Supérieure d'Ingénieurs de Beyrouth (ESIB), Faculty of Engineering, Saint Joseph University of Beirut, Beirut 1107 2050, Lebanon.

Centre de Recherche Scientifique en Ingénierie (CRSI), Faculty of Engineering, Lebanese University, Beirut 1533, Lebanon.

出版信息

Sensors (Basel). 2023 Jun 3;23(11):5315. doi: 10.3390/s23115315.

Abstract

LoRaWAN has imposed itself as a promising and suitable technology for massive machine-type communications. With the acceleration of deployment, improving the energy efficiency of LoRaWAN networks has become paramount, especially with the limitations of throughput and battery resources. However, LoRaWAN suffers from the Aloha access scheme, which leads to a high probability of collision at large scales, especially in dense environments such as cities. In this paper, we propose EE-LoRa, an algorithm to improve the energy efficiency of LoRaWAN networks with multiple gateways via spreading factor selection and power control. We proceed in two steps, where we first optimize the energy efficiency of the network, defined as the ratio between the throughput and consumed energy. Solving this problem involves determining the optimal node distribution among different spreading factors. Then, in the second step, power control is applied to minimize the transmission power at nodes without jeopardizing the reliability of communications. The simulation results show that our proposed algorithm greatly improves the energy efficiency of LoRaWAN networks compared to legacy LoRaWAN and relevant state-of-the-art algorithms.

摘要

LoRaWAN 已经成为大规模机器类型通信的一种有前途和适用的技术。随着部署的加速,提高 LoRaWAN 网络的能量效率变得至关重要,特别是在吞吐量和电池资源有限的情况下。然而,LoRaWAN 受到 Aloha 接入方案的限制,这导致在大规模情况下(特别是在城市等密集环境中)碰撞的概率很高。在本文中,我们提出了 EE-LoRa,这是一种通过扩频因子选择和功率控制来提高多网关 LoRaWAN 网络能量效率的算法。我们分两步进行,首先优化网络的能量效率,定义为吞吐量和能耗的比值。解决这个问题涉及到在不同扩频因子之间确定最优的节点分布。然后,在第二步中,应用功率控制来最小化节点的传输功率,而不会影响通信的可靠性。仿真结果表明,与传统的 LoRaWAN 和相关的最先进算法相比,我们提出的算法大大提高了 LoRaWAN 网络的能量效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a12/10256030/97f06e0437bf/sensors-23-05315-g002.jpg

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