Abstract
This paper proposes a methodology for the development of a correlation model between Quality of Service and Experience in cognitive radio networks. The aim of this research is to provide the cognitive radio networks ecosystem player the tools to assess the contribution of the network performance to the overall level of user's satisfaction. The performance parameters of several types of applications are addressed to highlight how delay, delay variation and information loss affect the service quality. Furthermore we thoroughly discuss, evaluate and test the proposed methodology, i.e., non-linear regression and genetic algorithms, by comparing it to the IETF recommended games MUSE G-Model. The obtained results are very promising. Future work includes verifying the effectiveness of the proposed methodology in the context of more complex fitting equations.
Authors: Daniel Robalo and Fernando J. Velez