User Characterization through Dynamic Bayesian Networks in Cognitive Radio Wireless Networks

摘要

The current shortage and inefficient use of the frequency spectrum lead researchers to seektechnological solutions to this problem [1], thus Cognitive Radio (CR) [2] is proposed, allowing a moreefficient management of the existing resources so they can be exploited opportunistically by cognitiveusers. This paper presents the design and use of a Bayesian network for the characterization of theprimary user (PU) in wireless networks (GSM 824.9 MHz) in order to generate a PU activity predictor,which could serve to the central entity of a cognitive network in making spectral decisions. From theresults found, it is concluded that the artificial intelligence technique based on Bayesian networks allowsto model and predict the behavior of the primary user above 80% for short future lapses of time.