CAREER: Automating the measurement and management of the radio spectrum for future spectrum-sharing applications

Suny At Albany, Albany NY

Investigators

Abstract

A growing number of domains that drive economic growth and humanity's well-being, including healthcare, emergency management and national defense, hinge on wireless network connectivity. This has created a market potential of $640.9 billion, which cannot be realized as existing networks operate at capacity. Despite this potential, only 8% of the radio spectrum is allocated to wireless communication technologies. This minimal allocation creates artificial scarcity of frequency resources, whereby popular bands are saturated, while others are under-utilized. In response, wireless technologies have begun to incorporate new hardware and software to boost their spectrum efficiency through opportunistic frequency reuse. While promising, this trajectory of innovation cannot be sustained unless we establish a framework for principled spectrum measurement and management that can embrace unforeseen network and sensor capabilities in support of future spectrum policy, policing and technology. This project develops a long-term, integrated program of research, education and outreach to (i) establish a scientific and technological framework for automated spectrum measurement in support of shared-spectrum access, and (ii) to train the next generation of wireless specialists at the intersection of networks, digital communications and machine learning. The project will work closely with industry and standardization efforts to ensure broader adoption. The research will be carried out in three thrusts at the confluence of signal processing, digital communications, machine learning, graph mining, and large-scale measurement. First, it will study the effects of real-world scan imperfections on signal features. Following these insights, the project will contribute algorithms for spectrum cognizance and transmitter fingerprinting from imperfect scans. Second, it will enable application-driven measurement by creating an analytical framework that links sensor properties with data quality and algorithm performance. Third, models and algorithms will be integrated in an open system accessible to the community. This project will lay the foundation for future-proof and application-driven spectrum measurement that leverages wide-band and heterogeneous sensing for end-to-end support of emerging wireless networks. It will contribute data-driven and platform-aware abstractions, models and algorithms that produce domain-informed features for automatic spectrum analytics. The outcomes will bridge the existing gap between measurement capabilities and algorithm requirements while tackling realistic scenarios with rogue or incompletely scanned transmitters. The project will produce a cost-utility framework to explore tradeoffs between sensor price, bandwidth, computation and power; and algorithm accuracy, stability and confidence. The integration of research outcomes into an open system will allow systematic and reproducible research and education, while complying with and informing standardization efforts. 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.