Evangelos Kranakis, Joaquin Garcia-Alfaro, John Lambadaris, Ramy H. Gohary
Hatem Abou-Zeid, Aroosh Elahi
Emerging 5G/B5G (beyond 5G) wireless networks will provide ubiquitous connectivity to diverse device types and services such as autonomous vehicles, Internet of Things (IoT), real time monitoring, emergency communications. Communications with Unmanned Aerial Vehicles (UAVs), in particular drones, are expected to be an important application of the of 5G/B5G networks. Compared to current wireless technologies, 5G will be offering superior throughput and latencies that will lead to flexible and efficient deployment of drones. Aerial drone networks have already attracted the interest of researchers with efforts focusing primarily on aerial network configuration over existing wireless technologies such as LTE.
The goal in this project is to perform research for and provide solutions to the following challenges:
a) Investigate drone control algorithms implemented over wireless 5G channels. We will consider full dynamic drone models and the effect of the variable delay (of the wireless 5G system) on the on the drone control inputs.
b) Develop the required dynamic drone models and simulations to evaluate the performance of our control techniques with respect to parameters that are exhibited by the wireless channel, such as delays and interference.
c) Investigate efficient network resource allocation (e.g., bandwidth adaptation) for Beyond Visual Line of Sight (BVLOS)drone communication and control.
d) Perform research on the use of artificial intelligence and machine learning techniques towards robust drone control.
e) Develop a practical 5G test bed/interface to verify our results in a commercial wireless 5G network.
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