Collaborative Research: SWIFT: LARGE: Dynamics and Security Aware Predictive Spectrum Sharing with Active and Passive Users

This project is helping to lay the foundation for more efficient and secure access to wireless spectrum while protecting essential existing uses of that spectrum. This access is critical to meet the demands from both legacy and emerging wireless applications, that have potential benefits across society. To this end, we are developing novel sensors, algorithmic solutions, models and architecture for future Data-Aware Spectrum Access Systems (DASASs) that will extend the current state-of-the-art to enable date driven solutions for spectrum access.

Other impacts of this project include outreach to K-12 education, training and mentoring students including undergraduates and under-represented minorities, and developing new courses related to the proposed research.

The envisioned system will leverage extensive low-cost sensing to support spectrum sharing across different frequency bands at different timescales for a rich set of different use cases including static and mobile users, active and passive spectrum utilization, and planned versus random uses. We are taking a multidisciplinary approach to design this system including: developing low cost spectrum sensors that utilize novel low-power distributed algorithms; understanding how to efficiently integrate and query the data obtained from these algorithms with other sources (e.g., weather, spatial density of demands) and use it to predictively trigger algorithms for spectrum allocation decisions; developing new and scalable spectrum allocation algorithms that use the acquired data to manage a wide range of users of the spectrum while accounting for market competition; and ensuring that the resulting system can leverage the available data to be secure against malicious attackers and unintentional user behavior.

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.