Exploring Qualitative Probabilistic Networks for knowledge modeling in Cognitive Wireless Networks

The suitability of using Qualitative Probabilistic Networks (QPN) for knowledge modeling and inference in Cognitive Wireless Networks is studied in this paper. This can be considered as a light weight approach compared to the complexity associated with the use of Bayesian Networks. This study brings out the advantages and issues involved in using QPN for modeling the dynamic behavior of wireless networks. Application and limitations of using QPN is illustrated with the modeling of a cognitive radio link and subsequently its performance while driving a link adaptation. The same methodology is extendable to model network layer behaviors as well.