Networked and Embedded Systems Laboratory

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Localizing primary users using observations collected from secondary users sensing the spectrum is a key aspect for improved operations in cognitive radio networks. However, malicious secondary users may obfuscate their location reports causing disruption in the network operation. In this paper we take a first step towards addressing the challenging problem of primary user localization in the presence of secondary users of varying trust that may randomly obfuscate their reports while maintaining plausibility of their content. Using localization reports as evidences in support of (or against) hypotheses about user locations, we develop the foundations of an evidential reasoning-based approach that uses subjective logic for information fusion and inferencing for localization in the presence of incomplete and conflicting knowledge. To do so, we exploit our recent extensions of subjective logic that accommodate the spatial relationships that naturally exists between location reports. After highlighting our spatial extensions, we apply them in building an inferencing algorithm for primary user localization. Through extensive simulations, we analyze its performance and the effect of various design parameters, showing a 90\% accuracy in localization. Finally, we compare it with other localization techniques via simulations.

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