Collaborative Research: SWIFT: Decentralized Intelligent Spectrum Sharing in UAV Networks (DISH-uNET) via Hardware-software Co-design

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Intelligent unmanned aerial vehicles (UAVs, or “drones”) are attracting the interest of the networking community as a “tool” to provide new capabilities, to extend the infrastructure of wireless networks and to make it more flexible and resilient. UAV-aided wireless networks will enable present and future Internet of Things (IoT) and 5G applications and be a driver for new military and civilian applications spanning battlefield inspection, border control and aerial surveillance, precision agriculture, environmental monitoring, transportation and delivery of goods. Currently, despite the great potential of UAV networks, the design of such networks faces great challenges due to the high mobility of UAVs, the limited power constraint of UAVs, and the non-stationary environment. In this project, we will develop novel approaches for decentralized intelligent spectrum sharing in mmWave UAV networks (DISH-uNET). This project will have a significant engineering and societal impact and substantially advance the state-of-the-art in the design of intelligent UAV networks with strong resiliency attributes. The proposed DISH-uNET achieves high efficiency and resilience based on hardware-software co-design through (1) domain-specific energy-efficient systolic accelerators, (2) novel learning-based transceiver design for high mobility UAVs, (3) new decentralized spectrum sharing multiple access control (MAC) for efficient spectrum management and utility optimization, (4) fast adaptation of mobility resilient mmWave beam learning for UAV networks. This project has four main thrusts. (1) Energy-efficient systolic accelerator for simultaneous real-time signal processing and machine learning. (2) Transceiver design for high mobility UAV Communication. (3) Bridging Lyapunov optimization framework, game theory, and reinforcement learning in decentralized spectrum sharing. (4) Mobility-resilient mmWave beam learning. The research team has the unique access to a large-scale UAV testbed, equipped with the state-of-the-art mmWave transceivers. This testbed will be used for extensive evaluations of the proposed DISH-uNET system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.