Minimization of energy consumption is critical to developing green, sustainable technologies for cognitive radio terminals that can connect to networks that operate on different frequency bands with a variety of air interfaces. The intellectual merit of this project is a unified and coherent consideration of RF components, communication system algorithms, baseband computation platforms, and design tools, to greatly increase spectrum sharing efficiency. Dataflow methodologies are a promising candidate for the modeling, analysis and verification of cognitive radio systems. As dataflow models are abstract and platform independent, the same model can be used to generate implementations for very different devices from low-power sensor nodes to high-end mobile terminals. The key novelty is in the development of systematic methods for design, implementation, and integration of configurable RF chains, and in the development of dataflow methods for formal analysis and optimization of these new capabilities. The expected results are: (1) Energy consumption models and a design framework for computation, control and configuration of future radio devices, leveraging the investigators' existing experimental testbeds, (2) Configurable radio architectures for wide-scale cognitive access of noncontiguous RF spectrum, and (3) Design methodologies for flexible, energy-efficient cognitive wireless networks. The broader impact includes international collaboration through the WiFiUS program creating a holistic design for configurable frequency agile terminals. A novel interdisciplinary approach is enabled by the unique international team, which builds upon collaborations between experts at the Tampere University of Technology and University of Oulu in Finland, and Rice University and the University of Maryland in the US.
In this project, we have developed new techniques and software tools for design and implementation of energy-efficient cognitive radio systems. By strategic, dynamic selection of wireless channels, cognitive radio technologies are important for enabling more efficient use of limited spectrum, and improving the effectiveness of wireless communications services. Our emphasis on minimization of energy consumption in this project has contributed to the development of green, sustainable technologies for cognitive radio terminals that can connect to networks that operate on different frequency bands with a variety of air interfaces. Specific technical outcomes of this project have included: (1) energy consumption models and a design framework for computation, control and configuration of future radio devices, leveraging the investigators' existing experimental testbeds; (2) configurable radio architectures for wide-scale cognitive access of non-contiguous RF spectrum; and (3) design methodologies for flexible, energy-efficient cognitive wireless networks. The broader impact of this project includes international collaboration through the WiFiUS Program creating holistic design methodologies for configurable frequency agile terminals. The Wireless Innovation between Finland and U.S. (WiFiUS) Program "provides a platform for building long-term research and education collaboration" between Finland and the U.S., the two world leaders in the field of wireless networking. Our project has led to novel interdisciplinary approaches that have been enabled by our unique international team, which has built upon collaborations among experts at the Tampere University of Technology and University of Oulu in Finland, and Rice University and the University of Maryland in the U.S. Through its strong interdisciplinary emphasis, the project has helped to train several Ph.D. students in interdisciplinary research spanning embedded systems, signal processing and wireless communications. These are major technical areas in the field of Electrical and Computer Engineering where greater cross-fertilization of ideas is important in advancing the field. The project has also helped to train these students in international and multi-institution collaboration. Additionally, by its involvement of women Ph.D. students, the project has contributed to broadening participation in engineering research. Building on the collaborations that were developed in this project, we have spun out a new project, as part of the FiDiPro Programme (www.fidipro.fi) in Finland. FiDiPro stands for the "the Finland Distinguished Professor Programme". Our FiDiPro project is entitled "Advanced Dynamic Stream Processing for Networking and Big Data (StreamPro)". The project is sponsored by Tekes, the Finnish Funding Agency for Innovation, which "is the most important publicly funded expert organisation for financing research, development and innovation in Finland".
