论文标题
具有不完美的SF正交性的多门洛拉网络的时空建模
Spatiotemporal Modelling of Multi-Gateway LoRa Networks with Imperfect SF Orthogonality
论文作者
论文摘要
低功率宽区域（LPWA）网络的细致建模和性能分析对于大规模密集的互联网（IoT）部署至关重要。由于远距离（LORA）目前是最突出的LPWA技术之一，因此我们在本文中提出了一个基于随机几何的框架，以分析由Matern cluster Process（MCP）建模的多门链路LORA网络的上行链路传输性能。提出的模型首先考虑所有多细胞拓扑，不完美的扩散因子（SF）正交性，随机启动时间和几何数据到达率。考虑到所有这些因素，我们最初为任何开始时间分布开发了依赖SF的碰撞时间函数。然后，我们分析了集群内和群间干扰的拉普拉斯变换，并制定了上行链路传输成功概率。通过仿真结果，我们突出显示了每个SF对干扰的脆弱性，说明了参数（例如网络密度）的影响以及功率分配方案对网络性能的影响。独特的是，我们的结果阐明了何时更好地激活自适应功率机制，因为我们表明基于SF的功率分配近似于Lora ADR，对群集头附近的节点产生了负面影响。此外，我们表明，干扰性能降低性能的干扰最大取决于解码阈值范围和功率分配方案。
Meticulous modelling and performance analysis of Low-Power Wide-Area (LPWA) networks are essential for large scale dense Internet-of-Things (IoT) deployments. As Long Range (LoRa) is currently one of the most prominent LPWA technologies, we propose in this paper a stochastic-geometry-based framework to analyse the uplink transmission performance of a multi-gateway LoRa network modelled by a Matern Cluster Process (MCP). The proposed model is first to consider all together the multi-cell topology, imperfect spreading factor (SF) orthogonality, random start times, and geometric data arrival rates. Accounting for all of these factors, we initially develop the SF-dependent collision overlap time function for any start time distribution. Then, we analyse the Laplace transforms of intra-cluster and inter-cluster interference, and formulate the uplink transmission success probability. Through simulation results, we highlight the vulnerability of each SF to interference, illustrate the impact of parameters such as the network density, and the power allocation scheme on the network performance. Uniquely, our results shed light on when it is better to activate adaptive power mechanisms, as we show that an SF-based power allocation that approximates LoRa ADR, negatively impacts nodes near the cluster head. Moreover, we show that the interfering SFs degrading the performance the most depend on the decoding threshold range and the power allocation scheme.
