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Completed TRL 3 (started at 2, targeting 3)
The success of any space or terrestrial mission depends heavily on its communication system. The enormous distances that are typically involved in these missions produce long delays, link disruptions, and unexpected disturbances that continuously pose challenges to these communications. To overcome some of these issues and to manage the increasing demand for data transmissions, the network is regularly updated to enhance the traditional radio systems. These options include cognitive radio, free-space optical links, and delay tolerant technologies. Novel networking mechanisms that fully employ these options and require minimal or no human assistance are becoming decisive for future space endeavors. The goal of this research is to advance core knowledge of cognitive networking. Inspired by the way the brain learns from experience to carry out a broad variety of complex tasks, this work develops the theory and algorithms that seek to harness the brain-like computational power of spiking neural network models for autonomous decision-making purposes in data networking. This work also designs and implements a cognitive routing module for space and earth data network communications. This module will autonomously recognize user requirements, acquired network observations, and given constraints to determine the best way of transferring information over a mixed set of communication technologies. Outputs of this research can help to improve the reliability, performance, and asset efficiency of space communication networks.
Significant improvements to the reliability, performance, and asset efficiency of space communication networks. Low-power and small footprint implementation with cognitive processors. Integrates multiple communication technologies: cognitive radio, delay-tolerant networks, free-space optical, and conventional systems.
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