Illinois Tech Develops AI Tool to Optimize Drones as Mobile Cell Towers

Using drones as pop-up cell towers isn’t new. Figuring out how many to deploy, and exactly where, has been the real challenge according to researchers at Illinois Institute of Technology who say they’ve solved that problem with a machine-learning algorithm that can determine, in near real time, the optimal number and placement of UAV base stations to supplement fixed towers.

Led by Professor Yu Cheng, the team published its findings in IEEE Transactions on Vehicular Technology. The system jointly optimizes drone quantity and location a complex combinatorial problem that traditional methods solve too slowly for real-world deployment.  

The payoff: carriers could adjust aerial coverage throughout the day as demand shifts, boosting capacity for events, disasters or rural surges, then pulling drones back when traffic drops.

As regulators like the FCC open spectrum for drone operations, and companies experiment with airborne networks, the missing piece has been fast optimization software. This research aims to provide that layer.

Cheng estimates drone-based network supplementation could become commercially viable within five years, especially for disaster response and large events where flexible capacity is critical.