When you think of cellular networks, you probably envision radio towers and invisible data streams. But AT&T, by necessity, needs to see everything in between: buildings, trees and the multitude of obstacles that can interfere with wireless signals getting to your phone.
The cellular provider is turning to a key technology from gaming and computer graphics to get an accurate picture. AT&T Wireless Geo Modeler is a new system that uses ray tracing and AI to generate detailed representations of the areas covered by its network and improve connectivity. In doing so, AT&T says it can react to service interruptions quickly and also better predict how its network can be configured in response to large social events or during natural disasters.
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How ray tracing works in a cellular context
AT&T's Geo Modeler uses ray tracing and other data to build a 3D model of the area surrounding a cell tower. AT&T
In computer graphics, ray tracing is a technique for rendering three-dimensional scenes. Software simulates light beams emanating from a virtual camera and calculates how the light affects objects and materials in the scene. Ray tracing is notable for rendering shadows and reflections, leading to more realistic-looking environments.
In the past, ray tracing was computationally challenging. Early examples, such as the original Toy Story movie, required rooms full of processing hardware and up to 24 hours to render a single frame of footage. The graphics processor in high-end smartphones can now render photorealistic, ray-traced scenes in games in real time.
According to Velin Kounev, lead inventive scientist at AT&T Labs, the technology's cellular application works the same way. "Whatever Nvidia is doing for games, whatever Disney is doing... we are doing at a much bigger scale," he said.
In the context of AT&T's Geo Modeler, Kounev explained, radio propagation from cellular towers is high-frequency light that our eyes cannot see. The towers measure how the rays react to the surrounding environment, such as colliding with structures or reflecting off surfaces. That collected data is processed and analyzed by several internal AT&T systems and machine learning models to determine if changes or optimizations need to be made, in what AT&T calls "near scale time."
Those changes can include everyday adjustments to the angle of nearby antennas or compensating for a tower that has gone offline during a natural disaster. Modifications can be deployed automatically in seconds or minutes, ideally in a way that doesn't impact customers.
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