Accession Number:

ADA461562

Title:

A Method for Dynamic Reconfiguration of a Cognitive Radio System

Descriptive Note:

Doctoral thesis

Corporate Author:

COLORADO UNIV AT BOULDER DEPT OF COMPUTER SCIENCE

Personal Author(s):

Report Date:

2006-01-01

Pagination or Media Count:

158.0

Abstract:

Advances in process technology has made it possible to migrate applications that were traditionally implemented in custom silicon to general purpose processors. This transition has given birth to the field of cognitive and software-defined radio CSDR. These CSDRs offer a broad range of opportunities for improving the use and utilization of radio frequency spectrum. This includes the creation of radio networks that can reconfigure their operation based on application requirements, policy updates, environmental conditions, and the ability to adapt to a wide range of protocols. One of the key benefits of having a CSDR is its ability to change communication parameters in response to changes in application needs andor changes in the radio frequency landscape. Such reconfiguration requires an understanding of how these communication parameters interact within the network protocol stack. Analysis of these parametric cross-layer interactions is a critical precursor in the development of a predictive model and algorithm for dynamic reconfiguration of a CSDR. This work investigates how parameters at the physical, data link, network, and application layers interact, how desirable configurations of these parameters can be determined, and how these parameters affect the performance of file transfer and Voice over IP applications. An analysis of varying communication parameters across networking layers is used to inform the design, implementation, and evaluation of a predictive model and algorithm for dynamic reconfiguration of a cognitive radio. This model and algorithm allow a CSDR to dynamically modify its configuration in order to improve system performance. A systematic method for development of a cognitive platform is presented. This method uses statistical analysis of variance and design of experiments techniques to inform the design and implementation of a dynamic reconfiguration algorithm.

Subject Categories:

  • Operations Research
  • Computer Programming and Software
  • Radio Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE