Let’s explore in more detail. Typically, 4G towers are anywhere from 15-60m high in the urban and suburban environments. With the need to install many more towers for 5G, antennae are more likely to be installed on utility poles and buildings that are, on average, just 10-12m high.
The satellite data that’s traditionally used in propagation models for 4G networks has a horizontal accuracy of one to two meters, and a vertical accuracy of two to five meters. When doing the modelling for 4G towers (~30m high), the relative error in the elevation data with respect to the height of the tower is about 6-15%. If the same data is used for generating the propagation models of 5G antennae (~12m high), the relative vertical error reaches the range of ~15-37%. So, to generate the models that achieve an acceptable standard of reliability and accuracy, geodata three to five times more accurate than satellite data is a must.
High-res 3D data is also crucial to the effective use of beamforming, or the practice of managing radio frequencies to make sure a signal reaches the end user device with the maximum speed and efficiency. As described by IEEE, beamforming is akin to a “traffic signalling system for cellular signals” that optimises the travel route for the radio signal by “allowing a base station to send a focused stream of data to a specific user.”
Since radio wave propagation is impacted by obstructions and surface materials that can cause refraction of the signal, and because the required higher frequency signals carry far shorter distances, more efficient routing is required to ensure signals reach their intended devices successfully.
3D beamforming involves not just a horizontal scan of the signal, but uses devices that tilt in 3D space, so the resulting signal is more focussed and targeted at the end user device. Because antennae are also 3D objects moving in a 3D environment, 3D data provides the context for understanding, for example, what floor of an office building the signal needs to target.