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In this paper, the authors consider cooperative localization and tracking of Primary Users (PU) in a cognitive radio network using Bayesian techniques. They use particle filtering methods to track the location of a PU in the network using cooperative localization techniques and present some results for noisy measurements. The Cognitive Radio (CR) nodes estimate the information related to the geographical position of the PU based on existing location identification and localization techniques and forward the noisy information to a Cognitive Radio Base station (CRB), which then fuses the information to estimate the position of the PU in the network in order to perform a radio scene analysis.
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