CSR: Medium: Collaborative Research: Embedded System Design Optimization and Adaptation using Compact System-Level Models

University Of Nebraska-Lincoln, Lincoln NE

Investigators

Abstract

This project will develop new techniques to help advanced computing systems for signal processing better adapt to the environments in which they operate. This project is important because signal processing is everywhere (cell phones, computer networks, manufacturing systems, agriculture, etc.). Adapting to the environment helps these systems to operate more reliably by, for example, adapting to changing radio interference or the challenging radio environments presented by clusters of tall buildings. Many of these communication systems are also battery-operated or must run on limited energy; adapting to their operating environments helps to reduce their energy consumption and improve battery life. These techniques are particularly useful for cognitive radio, an emerging technology that allows devices for wireless communication (such as cell phones) to more efficiently use radio spectrum. This project will develop new methods for creating software that can be reconfigured at run time. Typical software is created to operate in a particular mode; changing the software?s operating conditions requires redesigning the software itself. New mathematical models and algorithms will allow system designers to create software that is designed to adapt itself dynamically to its environment. The project will address both models specifying the behavior of the software and for translating that specification into an efficient implementation. The principal investigators will collaborate with colleagues at the Institut National des Sciences Appliquées (INSA) in Rennes, France, and National Chiao Tung University in Hsinchu, Taiwan. The collaborators in France and Taiwan will provide expertise in cognitive radio algorithms and hardware that complements the principal investigators? expertise in software design. The collaboration will also provide valuable international experience for the student research assistants involved in the project. Cognitive radio will be used a driving example in coursework for undergraduate and graduate students to integrate research results from this project into education. The PIs will actively recruit underrepresented minority students for this project.