Internet-of-Things (IoT) applications require a network that covers a large geographic area, consumes less power, is low-cost, and is scalable with an increasing number of connected devices. Low-power wide-area networks (LPWANs) have recently received significant attention to meet these requirements of IoT applications. Long-range wide-area network (LoRaWAN) with long range (LoRa) (the physical layer design for LoRaWAN) has emerged as a leading LPWAN solution for IoT. However, LoRa networks suffer from the scalability issue when supporting a large number of end devices that access the shared channels randomly. The scalability of LoRa networks greatly depends on the spreading factor (SF) allocation schemes. In this article, we propose an exponential windowing scheme (EWS) for LoRa networks to improve the scalability of LoRa networks. EWS is a distance-based SF allocation scheme. It assigns a distance parameter to each SF to maximize the success probability of the overall LoRa network. Using stochastic geometry, expressions for success probability are derived under co-SF interference. The impact of exponential windowing and packet size is analyzed on packet success probability. In addition, the proposed scheme is compared with the existing distance-based SF allocation schemes: equal-interval-based and equal-area-based schemes, and it is shown that the proposed scheme performs better than the other two schemes.

中文翻译：

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EWS：提高 LoRa 可扩展性的指数窗口方案

物联网 (IoT) 应用需要一个覆盖大地理区域、耗电少、成本低且可随着连接设备数量增加而扩展的网络。低功耗广域网 (LPWAN) 最近受到极大关注，以满足物联网应用的这些要求。具有远程 (LoRa) 的远程广域网 (LoRaWAN)（LoRaWAN 的物理层设计）已成为物联网的领先 LPWAN 解决方案。然而，当支持大量随机访问共享信道的终端设备时，LoRa 网络会遇到可扩展性问题。LoRa 网络的可扩展性很大程度上取决于扩频因子 (SF) 分配方案。在本文中，我们为 LoRa 网络提出了一种指数窗口化方案 (EWS)，以提高 LoRa 网络的可扩展性。EWS 是一种基于距离的 SF 分配方案。它为每个 SF 分配一个距离参数，以最大化整个 LoRa 网络的成功概率。使用随机几何，成功概率的表达式是在 co-SF 干扰下导出的。分析了指数窗口和数据包大小对数据包成功概率的影响。此外，将所提出的方案与现有的基于距离的SF分配方案：基于等间隔和基于等面积的方案进行了比较，表明所提出的方案优于其他两种方案。分析了指数窗口和数据包大小对数据包成功概率的影响。此外，将所提出的方案与现有的基于距离的SF分配方案：基于等间隔和基于等面积的方案进行了比较，表明所提出的方案优于其他两种方案。分析了指数窗口和数据包大小对数据包成功概率的影响。此外，将所提出的方案与现有的基于距离的SF分配方案：基于等间隔和基于等面积的方案进行了比较，表明所提出的方案优于其他两种方案。