Geometry-Aware LoRaWAN Gateway Placement in Dense Urban Cities Using Digital Twins
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin

TL;DR
This paper presents a geometry-aware digital twin and GPU-accelerated ray tracing approach for optimizing LoRaWAN gateway placement in dense urban environments, improving coverage planning accuracy.
Contribution
It introduces a realistic 3D city model with ray tracing for evaluating gateway placement, advancing beyond simplified models and sparse measurements.
Findings
A single rooftop gateway covers 20% of the area at a robust SNR threshold.
Six sites still leave large uncovered areas in residential streets.
Digital twin and ray tracing tools help plan effective gateway deployment.
Abstract
LoRaWAN deployments rely on rough range estimates or simplified propagation models to decide where to place/mount gateways. As a result, operators have limited visibility into how rooftop choice, streets, and building shadowing jointly affect coverage and reliability. This paper addresses the problem of gateway placement in dense urban environments by combining a geometry accurate Digital Twin (DT) with a GPU accelerated ray tracing engine. Existing studies optimize placement on abstract grids or tune models with sparse measurements; few works evaluate LoRaWAN gateways on a full 3D city model using a realistic link budget. In this paper, we develop a DT with ITU radio materials and evaluate eight candidate rooftops for RAK7289 WisGate Edge Pro gateways under a sub-GHz link budget derived from the data sheet. For each rooftop, we obtain Signal-to-Noise Ratios (SNR) on a 5 meter grid,…
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Taxonomy
TopicsIoT Networks and Protocols · Millimeter-Wave Propagation and Modeling · Advanced MIMO Systems Optimization
