Make or Break? How LoRaWAN Duty Cycle Impacts Performance in Multihop Networks

LoRaWAN is a widely adopted protocol for Internet of Things applications with energy constraints and large coverage area demands. The protocol standardization defines a star-of-stars topology, where end-devices send their packets directly to a gateway that forwards the messages to the network server, where they are handled depending on the application. LoRaWAN is at the top of the Long Range (LoRa) physical layer based on the Chirp Spread Spectrum (CSS) modulation, where signals are spread along the frequency by the Spreading Factor (SF). The modulation technique gives the LoRaWAN long range coverage characteristics, that could reach 45 kilometers in theory. Furthermore, the protocol adopts the Industrial, Medical, and Scientific (ISM) frequency band plans, which impose spectrum occupation limitations, and the constraints are defined by a device Duty Cycle (DC). The DC imposes a restriction of 0.1% up to 10% in transmission time, limiting the total amount of messages an end-deceive could send. In order to increase even more the coverage area, many works proposed the adoption of multihop techniques in LoRaWAN networks. Proposed solutions are based on routing and relay approaches, both with benefits and limitations. However, the literature does not explore the DC constraints on the multihop LoRaWAN solutions since packets might be enqueued. The packet delay increases due to the time spent in the buffer, and the delivery ratio decreases because packets are dropped when the buffer is full. To understand such impact, we provide a model to generalize the DC behavior on multihop LoRaWAN networks, focused on the packet delivery ratio and delay metrics. We evaluate our model analytically and experimentally. First, we conducted a numerical comparison between the standard network with the multihop Long Range Wide Area Network (LoRaWAN) over duty cycle constraints. The comparison considers a rural area and the coverage area limited by the 802.11 ah propagation model. The results elucidated the tradeoff between packet size, number of packets, and delay. The two-hop solution could decrease the delay compared with direct transmission using high spreading factors. However, in dense networks, the intermediate device buffer increases the packet delivery delay. It could reduce the packet delivery ratio because the device must respect the duty cycle to forward packets. On the other hand, higher spreading factors decrease the payload size and need more packets to transmit the