The Center of Excellence will address a number of fundamental research questions in the development of a robust, resilient, secure, and Fully Networked Command, Control and Communications infrastructure. The Center will focus on research that allows systems and sub-systems for sensing, data analysis, communications and networking, to be seamlessly integrated and adaptive to novel mission needs.
The CoE research is organized into four inter-dependent thrusts. The following figure shows the inter-relationships between the thrusts:
Thrust 1: Reconfigurable Framework for Integrated Command and Control, which will develop a new software plane and functional architecture, guided by robust machine learning (ML) models, to assess dynamic mission requirements, available resources, and environmental factors.
Thrust 2: Software Defined Flexible and Dynamic Network Resource Allocation and Resilience, which focuses on flexible division of available communication and computing resources into slices and can dynamically allocate these slices to the plurality of missions.
Thrust 3: Physical Layer Convergence of Sensing and Communications, whose goal is to maximize the utilization of the resources that are made available to the mission, via appropriate physical layer division and invocation of different physical modes.
Thrust 4: Robustness to Adversarial Disruptions on Sensing and Communications Infrastructure, which aims to provide robustness to adversarial attacks and fault resilience on all of the above.
Publications can be found here.
Year 1 Accomplishments
Thrust 1 accomplishments include development of a distributed learning framework with uncertain data and resource constraints, that accounts for available resources (computation, bandwidth) and noise in data. Additionally, work was done on developing verification approaches for assessing application requirements on bandwidth, which will be applied to drive robust and flexible resource allocation.
Within Thrust 2, a preliminary design for a framework to reduce the computational overhead on edge devices while rapidly producing desired data has been completed, with implementation in progress. The framework is designed to achieve efficient adaptability to support dynamic data and resource fluctuation. Also, various SDN-based execution environments have been evaluated and analyzed to support agile ramp up of computational resources. An initial design of an agile computational environment with network function virtualization was completed.
In Thrust 3, a programmable massive MIMO millimeter-wave platform was developed. Novel research was performed on spectrum sharing for federated learning. Finally, two methods of waveform sharing between radar sensing and communications were designed and realized on hardware.
For Thrust 4, a novel method to thwart potent full-duplex jammers and eavesdroppers was developed. A new method to boost TCP performance of critical applications under resource duress was designed and implemented. Additionally, an investigation was performed on TCP impact during link switching between RF and millimeter wave links, and undergraduate project studied multi-path TCP. Finally, adversarial attacks on ML-based joint source-channel coding were studied, and initial work was performed on secret key establishment using full-duplex communications.