Home / Research Experiences for Undergraduates / Research Experiences for Undergraduates / REU - Cognitive Reconfigurable Radio Architectures for Connected Autonomous Maritime Vehicles

Network the Oceans

Cognitive Reconfigurable Radio Architectures for Connected Autonomous Maritime Vehicles

Led by George Sklivanitis, Ph.D.

George Sklivanitis, Ph.D.

George Sklivanitis received the Diploma degree in electronic and computer engineering from the Technical University of Crete, Greece, in 2010, and the Ph.D. degree in electrical engineering from The State University of New York at Buffalo in 2018. He is currently a Research Assistant Professor with I-SENSE and the Department of Computer and Electrical Engineering and Computer Science at Florida Atlantic University. His research interests span the areas of signal processing, software-defined wireless communications and networking, cognitive radio, and underwater acoustic communications.

In 2014, he was the first finalist and was a recipient of the 2014 Nutaq Software-Defined Radio Academic U.S. National Contest and in 2015 he received the Best Demo Award in the 10th ACM International Conference on Underwater Networks and Systems. He was also a recipient of the 2015 SUNY Buffalo Graduate Student Award for Excellence in Teaching, the 2016 SUNY Buffalo Student Entrepreneur Fellowship, and the 2017 SUNY Chancellor’s Award for Student Excellence. Dr. Sklivanitis is a member of the IEEE Communications, IEEE Signal Processing, IEEE Oceanic Engineering Societies and serves as the co-organizer and TPC co-chair of the IEEE INFOCOM Workshop on Wireless Communications and Networking in Extreme Environments (WCNEE) since 2017.


A. Overview
We envision the design and development of small-form-factor cognitive communication modems that can be rapidly deployed and autonomously form wireless mesh multi-hop networks to connect maritime robots in real time, whether they are on the water surface, flying in the sky or lurking underwater. The proposed modems have access to the entire device-accessible frequency/space/time continuum and can dynamically optimize resource allocation parameters that span multiple networking layers, such as link waveforms and network routes. Our goal is to evaluate multi-hop networking algorithms that tackle cross-layer issues, from the physical to the network layer and above, to avoid interference and guarantee connectivity in a super network testbed of autonomous underwater vehicles (AUVs), unmanned aerial vehicles (UAVs), and autonomous surface vehicles (ASVs). Rapid implementation and testing of new cross-layer algorithmic designs will be enabled by software-defined programmable platforms. Wireless networking of robotic assets with multi-domain capabilities will enable autonomous and coordinated operation of fleets of vehicles in communication-constrained environments and enable a rich body of scientific and defense applications.

B. Objectives
The objective of the REU project is focused on the design and prototyping of key hardware and software subsystems of the cognitive modem architecture to support the implementation and evaluation of cross-layer optimized algorithms. Testing of the modem prototype will be conducted with remotely operated and autonomous underwater and surface vehicles at the FAU SeaTech campus in Dania Beach, FL.

C. Tasks
The REU student will work as part of a small team of researchers to design electronic circuit subsystems and implement software blocks in embedded software-defined radio platforms to support the development and evaluation of cognitive networking algorithms with autonomous maritime vehicles. The student will gain experience and skills to a variety of research areas ranging from signal processing, to embedded systems, to underwater communications and wireless mesh networking.