Advances in process technology, manufacturing, and architecture have ushered in an age of faster, smaller, and cheaper electronic devices. Emerging processor technology has made it possible to migrate applications that were traditionally implemented in custom silicon to general purpose processors (GPP). In the area of wireless communication, this transition has given birth to the field of software-defined and cognitive radio. Theses “smart” radios, or Cognitive/Sofware-defined Radios (C/SDR), can potentially make more efficient use of the available RF spectrum and adapt to a wide
range of protocols and environments. One of the key benefits of having a C/SDR is it's ability to change communication parameters in response to changes in application needs and the radio frequency (RF) landscape. While understanding the effects of changing communication parameters is a critical precursor to the development of a predictive model, it is not the focus of this paper. This research builds upon our investigation of the affects of varying these communication parameters through the development of a predictive model. This model allows a C/SDR to dynamically modify its configuration in order to improve system performance.
Troy Weingart is a Major in the United States Air Force and is currently a Ph.D. student at the University of Colorado at Boulder. Prior to this, Troy was an assistant professor in computer science at the Air Force Academy. During his 14-year military career, Troy has served as the Chief of Network and Computer Operations for the 93rd Air Control Wing, Robins Air Force Base, Georgia and chief of Satellite Command and Control Segment Support, 50th Space Wing, Shriever Air Force Base, Colorado. Troy is a student member of the IEEE and the ACM. His research interests include cognitive and software-defined radios and operating systems. Troy received his masters degree in computer science from the University of Colorado in 2000 and will receive his Ph.D. in December of 2006.