arXiv subjects

Lucas Mozart

Publications and source records attributed to Lucas Mozart.

3 recordsLinked to original sources

arXiv2026

Ray Tracing-Based LoRaWAN Gateway Placement for Reliable Connectivity in Amazonian Regions

Network planning is an important task in wireless communications, as it helps network operators avoid unnecessary costs. In the context of the internet of things, using long-range wide-area network technologies in the Amazon rainforest, a key challenge is ensuring reliable communication between end-devices and gateways (GWs). In this sense, this reliability is strongly affected by channel conditions. Thus, during the planning phase, choosing the appropriate channel model is an important decision for accurate simulations. Given this motivation, in this work, we propose an optimization model to evaluate the impact of different types of channels on coverage and packet delivery ratio in a forest scenario. We used channels from ray tracing, empirical, and stochastic approaches to assess how decisions made during the network planning phase, in terms of the channel used, affect GW placement and, specifically, the percentage of end-devices covered and the reliability of the communication system. Our results show that GW placement based on site-independent channels can overestimate the number of GWs required to meet the network requirements, whereas using site-specific channels allows us to satisfy the same requirements with fewer GWs.

cs.NI↗

arXiv2026

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

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.

cs.NI↗

arXiv2025

Accelerating Ray Tracing-Based Wireless Channels Generation for Real-Time Network Digital Twins

Ray tracing (RT) simulation is a widely used approach to enable modeling wireless channels in applications such as network digital twins. However, the computational cost to execute ray tracing (RT) is proportional to factors such as the level of detail used in the adopted 3D scenario. This work proposes RT pre-processing algorithms that aim at simplifying the 3D scene without distorting the channel, by reducing the scenario area and/or simplifying object shapes in the scenario. It also proposes a post-processing method that augments a set of RT results to achieve an improved time resolution. These methods enable using RT in applications that use a detailed and photorealistic 3D scenario while generating consistent wireless channels over time. Our simulation results with different urban scenarios scales, in terms of area and object details, demonstrate that it is possible to reduce the simulation time by more than 50% without compromising the accuracy of the multipath RT parameters, such as angles of arrival and departure, delay, phase, and path gain.

cs.NI↗