Joint Localization of Primary and Secondary Users in Cognitive Radio Network

Abstract

In this paper we implemented a local geometry alignment algorithm for locating the primary user (PU) in cognitive radio network. Based on the estimated distance between PUs and Secondary users (SUs) for the neighbors within certain communication range, the relative configuration of all users in the network is obtained initially and is refined finally to get the global position of every user in the network. The localization performance of the proposed approach is compared to multidimensional scaling and principal component analysis.