Localization in Cognitive Radio Systems In The Presence of Spatially Obfuscated Data

Localizing primary users using observations collected from secondary users sensing the spectrum is a key asp ect for improved operations in cognitive radio networks. However, malicious secondary users may obfuscate their location rep orts 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 us ers 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 a bout user locations, we develop the foundations of an evidential reasoning-based approach that uses subjective logic for in formation fusion and inferencing for localization in the presence of incomplete and conflicting knowledge. To do so, we exploit ou r 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. Th rough extensive simulations, we analyze its performance and the e ff ct of various design parameters, showing a 90% accuracy in loca lization. Finally, we compare it with other localization techniques via simulations.