LoRaWAN Gateway Placement for Network Planning Using Ray Tracing-Based Channel Models

Abstract

Network planning for long range wide area networks (LoRaWAN) relies heavily on the channel models used to estimate wireless coverage and connectivity. Consequently, the quality of gateway (GW) deployment decisions may be strongly affected by the propagation assumptions adopted during the planning process. Given this motivation, this work investigates how different channel models influence the placement of LoRaWAN GWs,formulating an optimization problem that contrasts stochastic and empirical models with ray-tracing-based models. To this end, we developed a framework that integrates ray tracing (RT) simulators with a discrete-event network simulator. Using this framework to generate LoRaWAN data metrics, we employ an optimization model that determines the optimal GW placement under different channel models, received power constraints, and network scenarios. Our results show that the optimized solution is highly sensitive to the chosen channel model, even when considering the same scenarios with different RT simulators, revealing a clear trade-off between computational cost and the fidelity of the solution to real-world conditions.