Associate Professor Mingyue Ji
Assistant Professor Cunxi Yu
Associate Professor Rong-Rong Chen

University of Utah electrical and computer engineering professors Mingyue Ji, Rong-Rong Chen, and Cunxi Yu, along with University of Buffalo assistant professor Zhangyu Guan, have been awarded a $750,000 grant from the National Science Foundation to support their research around drone and unmanned aerial vehicle (UAV) networks.

The grant, titled “Collaborative Research: SWIFT: Decentralized Intelligent Spectrum Sharing in UAV Networks (DISH-uNET) via Hardware-software Co-Design,” will allow the team to develop innovative solutions to the current challenges facing the design of wireless communication networks for decentralized networks of UAVs.

Due to the high mobility, non-stationary environment, and limited power constraint of UAV’s or drones, designing wireless networks in decentralized situations – ones in which drones cannot communicate with each other or communication is limited – has been a significant difficulty for the industry. This interdisciplinary team of experts are implementing machine learning techniques to advance the design of these UAV networks. Ultimately, the goal is to improve these networks to allow for the full potential of UAVs or drones to be utilized.

“The main technology we are using in this project is called millimeter wave (mmWave),” states Ji. “It is very fast with lower latency and a higher bandwidth than 800MHz, which is the typical minimum bandwidth for mmWave in 5G standard. The one thing that can significantly improve the performance of these networks is an increase in the bandwidth – mmWave can do that. More importantly, our proposed novel hardware-software co-design approach is the key to implementing the real time signal processing and tracking for the communications among UAVs.”

“One major application that this technology could be used for is in emergency and disaster networks – if an infrastructure is damaged or destroyed, our current response and communication systems are very weak and slow,” explains Ji. “The mmWave technology is much faster and will greatly improve these response networks.”

“A second application we are focusing on with this specific grant is the industrial Internet of Things (IoT) application,” explains Ji. “For example, in a warehouse drone network, the drones with different tasks may be from different operators who cannot communicate with each other. Hence, the decentralized feature of our proposed system can enable such applications.”

Other areas this research will impact include precision agriculture, environmental monitoring, transportation and delivery of goods, and more.

“This technology we are working on is fundamental technology – it can be applied to many cases and uses beyond the cases outlined in this grant,” says Ji. “We are not just developing algorithms; we also care about theory and the ‘why’ of how this technology works.”

This grant will allow each of the principal investigators on this project to hire one new Ph.D. student. If you are interested in learning more about the opportunities available, contact Mingyue Ji.