3D building geometry is now a baseline requirement in telecom network planning. Propagation engines such as Atoll’s Aster and Aster mmWave expect accurate vertical information to simulate LOS, shadowing, diffraction, and reflection.
Figure 1: Coverage prediction in Atoll b) with and a) without ONEGEO building height data. The addition of 3D geometry immediately reveals realistic signal shadows and LOS limits.
The difference between a good model and a great one isn’t simply having 3D data, it’s having the right 3D data: current, accurate, consistent, and tailored to the frequencies, sites, and environments that matter to your network.
That’s where ONEGEO comes in, not as a data vendor, but as your data partner.
ONEGEO provides the building intelligence your models depend on, delivered in the formats and quality levels your project demands.
Integrating ONEGEO into Atoll — easily, reliably
With ONEGEO, your planning environment starts with data that’s ready for engineering use. Each dataset is curated to match your target area, workflow, and propagation models. Typical building attributes include:
- Standardised, clean footprint geometry
- Above Ground Height (AGL) derived from measured or LiDAR sources
- Confidence and quality metrics
- Optional level counts, minHeight, and classification fields
Once integrated, Atoll uses this information to:
- Compute LOS/NLOS accurately
- Simulate blockage, reflections, and diffraction
- Generate realistic coverage (RSRP) and quality (SINR) maps that reflect actual city structure
The result is a propagation model that performs as expected in the field, with geometry that mirrors reality, not an approximation of it.
Tailored data for complex environments
Every network is different. Urban canyons, mixed topography, and high-density zones demand more than off-the-shelf datasets.
ONEGEO’s consulting and enterprise services deliver the precision and flexibility your models require:
- High-resolution 3D building models, including LiDAR-derived data where available
- Enhanced terrain and elevation surfaces, refined to project specifications
- Custom / manual editing or enhancements for specific geographic zones (e.g., stadiums, campuses, dense downtown cores)
- Expert collaboration on data structure and Atoll integration
- Clear licensing and data lineage suitable for enterprise and regulatory use
Accurate 3D building geometry reveals how antenna height and downtilt decisions affect street-level coverage — higher isn’t always better.
Figure 2: Accurate 3D building geometry reveals how antenna height and downtilt decisions affect street-level coverage — higher isn’t always better.
What’s revealed when building geometry is accurate
Even in advanced planning environments, having better 3D data reveals nuances that matter to engineers:
1. Antenna height tradeoffs
· A rooftop at +20 m might seem ideal, but accurate geometry shows it could overshoot street-level users.
· Use ONEGEO height data to optimize height, tilt, and orientation.
2. Urban canyon & shadow detection
· Realistic modeling of side alleys, narrow lanes, and façade-to-façade blockage that 2D models flatten.
· Identifies small-cell locations that standard models miss.
Figure 3: Street-level coverage prediction in Atoll using ONEGEO height data — realistic urban canyon shadowing becomes visible between buildings (left), and the effect on coverage at street level when adding two smaller transmitters (right).
3. High-frequency sensitivity (mmWave / n258)
· These frequencies offer extremely limited diffraction and maximum blockage sensitivity.
· The difference between a “flat model” and a 3D-aware model can be catastrophic in mmWave.
· Consulting-level accuracy matters in critical zones (e.g. city cores, stadiums).
Figure 4: N258 delivers ultra-high capacity, but short range.
4. Cross-layer consistency
· Using the same building geometry across n28, n78, n258 ensures your coverage layers align physically, reducing planning errors.
Figure 5: Multi-band coverage in Atoll using ONEGEO data — consistent building geometry enables coherent modelling across low-band, mid-band, and mmWave layers.
5. Signal Variation within buildings
· Beyond street-level analysis, accurate 3D building geometry also exposes how signal strength changes within a building, floor by floor.
· Lower floors can be heavily attenuated by neighbouring structures, while upper levels see significant improvements once above the urban clutter. This insight helps engineers tune beamforming, downtilt, and indoor coverage strategies with precision.
Figure 6: Impact of height within a building on signal strength (red = weaker, green = stronger)
From data to design confidence
When your Atoll models are powered by building data that’s built for your project, you gain:
- Closer prediction-to-field correlation
- Improved small-cell and in-building planning
- Reduced over- or under-design risk
- Stronger confidence in regulatory and client deliverables
- Scalable, repeatable workflows across markets and teams
With ONEGEO, you’re not just buying data — you’re engaging a partner that builds, validates, and delivers the exact 3D environment your models need to perform.
Partner with ONEGEO for precision network planning
Every RF model is only as good as the data beneath it.
ONEGEO’s consulting and enterprise solutions give you the ability to design with confidence, using 3D building and terrain data tailored to your specific area, frequency, and propagation model.
Whether you’re planning a city-wide rollout, a high-frequency pilot, or a nationwide update of legacy models, ONEGEO ensures your data inputs meet your engineering standards.
Build smarter. Design with precision.
Partner with ONEGEO to make your Atoll models reflect the real world. Contact us to learn more or request a consultation.
Attribution of sources: Google Earth, Esri, TomTom, Garmin, FAO, NAOO, USGS, Open Street Map contributors and the GIS user community, Maxar, Airbus DS, NGA, CGIAR, N Robinson, NCEAS, NLS, OS, NMA, Geodatastzrelsen, Rijkswaterstaat, GSA, Geo and FEMA, Intermap
