CRII: NeTS: Next Generation Spectrum Measurement Algorithms and Infrastructures

Suny At Albany, Albany NY

Investigators

Abstract

The current paradigm of exclusive spectrum allocation is creating artificial scarcity of spectrum resources that has a dramatic impact on network performance and user experience. Underutilized bands provide an opportunity for more efficient, shared spectrum access that has recently brought together policymakers, industry leaders and academic researchers to set an agenda for next-generation spectrum management. A critical enabler of such advances is deep understanding of spectrum use. This award will support research seeking to impact the scientific community, the policy domain and the public, by providing methods and informing system designs for efficient spectrum measurement and characterization, and informing the design of future mobile wireless networks and spectrum policy. Products from this research will be included in the PI's undergraduate and graduate courses, demonstrating the positive policy and societal impact of computer science and promoting the discipline to diverse groups of students. The goal of this project is to employ fundamental knowledge in signal processing and propagation, machine learning, and large-scale measurement to devise fast and robust algorithms and inform spectrum measurement infrastructure design. Of main research interest, will be the tight-knit mutual dependence between algorithms and infrastructures. The project will achieve this goal in two research tasks: (i) design and development of spectrum measurement algorithms for adaptive spectrum sensing, spectrum data management and spectrum characterization; and (ii) evaluation of spectrum measurement infrastructures that will illuminate the impact of spectrum sensor properties on spectrum characterization quality and will inform the design of mixed sensor cost/mobility measurement infrastructures. This research will bridge the gap between algorithm design and infrastructures. It will introduce the first holistic framework for spectrum measurement and characterization to facilitate next generation spectrum management. The design of adaptive, data-driven algorithms will facilitate rapid and efficient spectrum measurement and characterization. Exploration of the cost and mobility trade-offs in spectrum sensing infrastructure will inform efficient end-to-end infrastructure design that minimizes cost while maximizing the learning outcomes of spectrum sensing.