Time-frequency ALOHA-like random access: A scalability study of Low-Power Wide-Area Networks for IoT using stochastic geometry

In wireless networks, interferences between transmissions are modelled either in time or frequency domain. In this article, we jointly analyze interferences in the timefrequency domain using a stochastic geometry model assuming the total time-frequency resources to be a two-dimensional plane and transmissions from Internet of Things (IoT) devices timefrequency patterns on this plane. To evaluate the interference, we quantify the overlap between the information packets: provided that the overlap is not too strong, the packets are not necessarily lost due to capture effect. This flexible model can be used for multiple medium access scenarios and is especially adapted to the random time-frequency access schemes used in Low-Power Wide-Area Networks (LPWANs). By characterizing the outage probability and throughput, our approach permits to evaluate the performance of two representative LPWA technologies Sigfox R © and LoRaWAN R ©.