Almuhaya Mukarram, Al-Hadhrami Tawfik, Brown David J, Qasem Sultan Noman
Computer Science Department, School of Science and Technology, Nottingham Trent University, Clifton, Nottingham NG11 8NS, UK.
Computer Science Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia.
Sensors (Basel). 2025 Sep 3;25(17):5457. doi: 10.3390/s25175457.
Internet of Things (IoT) applications are rapidly adopting low-power wide-area network (LPWAN) technology due to its ability to provide broad coverage for a range of battery-powered devices. LoRaWAN has become the most widely used LPWAN solution due to its physical layer (PHY) design and regulatory advantages. Because LoRaWAN has a broad communication range, the coverage of the gateways might overlap. In LoRa technology, packets can be received concurrently by multiple gateways. Subsequently, the network server selects the packet with the highest receiver strength signal indicator (RSSI). However, this method can lead to the exhaustion of channel availability on the gateways. The optimisation of configuration parameters to reduce collisions and enhance network throughput in multi-gateway LoRaWAN remains an unresolved challenge. This paper introduces a novel low-complexity model for ZBMG-LoRa, mitigates the collisions using channel utilisiation, and categorises nodes into distinct groups based on their respective gateways. This categorisation allows for the implementation of optimal settings for each node's subzone, thereby facilitating effective communication and addressing the identified issue. By deriving key performance metrics (e.g., network throughput, energy efficiency, and probability of effective delivery) from configuration parameters and network size, communication reliability is maintained. Optimal configurations for transmission power and spreading factor are derived by our method for all nodes in LoRaWAN networks with multiple gateways. In comparison to adaptive data rate (ADR) and other related state-of-the-art algorithms, the findings demonstrate that the novel approach achieves higher packet delivery ratio and better energy efficiency.
物联网（IoT）应用正在迅速采用低功耗广域网（LPWAN）技术，因为它能够为一系列电池供电设备提供广泛覆盖。由于其物理层（PHY）设计和监管优势，LoRaWAN已成为使用最广泛的LPWAN解决方案。由于LoRaWAN具有广泛的通信范围，网关的覆盖范围可能会重叠。在LoRa技术中，多个网关可以同时接收数据包。随后，网络服务器选择接收信号强度指示（RSSI）最高的数据包。然而，这种方法可能导致网关的信道可用性耗尽。在多网关LoRaWAN中，优化配置参数以减少冲突并提高网络吞吐量仍然是一个未解决的挑战。本文介绍了一种新颖的低复杂度ZBMG-LoRa模型，利用信道利用率减轻冲突，并根据各自的网关将节点分类为不同的组。这种分类允许为每个节点的子区域实施最佳设置，从而促进有效通信并解决所确定的问题。通过从配置参数和网络大小推导出关键性能指标（例如，网络吞吐量、能源效率和有效交付概率），保持通信可靠性。我们的方法为具有多个网关的LoRaWAN网络中的所有节点推导了发射功率和扩频因子的最佳配置。与自适应数据速率（ADR）和其他相关的最新算法相比，研究结果表明，该新方法实现了更高的数据包交付率和更好的能源效率。
