Robustifying Predictive Intelligence for
A New Spectrum Market
This project is supported by NSF Award #2433966 (2024/10/01-2027/09/30): Robustifying Predictive Intelligence for A New Spectrum Market
Project Description
From autonomous driving to the metaverse, from digital democracy to intelligent healthcare, our next-generation revolutionizing applications are faced with an unprecedented shortage of frequency spectrum resources to meet their high demands from wireless technologies. This calls for a fundamental paradigm shift of the wireless ecosystem, from the current exclusive usage of licensed spectrum to dynamic, market-driven spectrum utilization that allows free spectrum trading and maximizes spectrum efficiency for a better digital future. As a pillar technology of the new spectrum market, intelligent algorithms based on advanced artificial intelligence and machine learning are expected to provide the ever-needed scalability and adaptability for managing and decision making in the new dynamic and complex environment, working in conjunction with or even replacing traditional algorithms used in the current wireless ecosystem. Building on top of the latest advances from machine learning, robust optimization, economic markets and wireless system design, this project designs robust intelligent algorithms for wireless stakeholders to ensure a reliable and resilient wireless infrastructure and ecosystem that can meet the critical requirements of spectrum access for current and future applications.
Project Personnel and Major Participants
Publications
Students receiving funding support from this project are marked with asterisk. PI is underscored in the publications.
Infiltrating the Sky: Data Delay and Overflow Attacks in Earth Observation Constellations
Xiaojian Wang, Ruozhou Yu, Dejun Yang, Guoliang Xue,
Accepted by IEEE International Conference on Network Protocols (ICNP), 2024.