The system-level performance of multi-gateway downlink long-range (LoRa) networks is investigated in the present paper. Specifically, we first compute the active probability of a channel and the selection probability of an active end-device (ED) in the closed-form expressions. We then derive the coverage probability (Pcov) and the area spectral efficiency (ASE) under the impact of the capture effects and different spreading factor (SF) allocation schemes. Our findings show that both the Pcov and the ASE of the considered networks can be enhanced significantly by increasing both the duty cycle and the transmit power. Finally, Monte-Carlo simulations are provided to verify the accuracy of the proposed mathematical frameworks.
翻译:本文调查了多端下行链路长程网(LoRa)的系统级性能,具体地说,我们首先在封闭式表达式中计算频道的主动概率和主动终端设备(ED)的选择概率,然后根据捕获效应和不同扩散系数分配计划的影响,得出覆盖概率(Pcov)和区域光谱效率(ASE),我们的调查结果显示,通过增加值班周期和传输能力,可大大加强所考虑网络的Pcov和ASE, 最后,提供蒙特卡洛模拟,以核实拟议的数学框架的准确性。