Primary Signal Transmitter Localization Using Cognitive Radio Networks

In communication technology, cognitive radio networks can be effectively used to detect and track targets of interested (primary users). Primary transmitter location through the collaborative effort of multiple cognitive radio nodes is relevant in this investigate. A two stage source localization process is proposed in this work, the time difference of arrival values (TDOA) are first determined using the generalize cross correlation (GCC) method and then TDOA values are used by a least squares (LS) estimation scheme to determine the primary transmitter location. The effect number of CR nodes, spacing of inter node, topology, noise, distance of source to node, node failure, location perturbation on the location estimation performance have been studied through MATLAB simulation. Simulation result illustrate that the error difference can be reduced by increasing the number of CR nodes or the spacing inter nodes and improve the location estimation accuracy. The CR node topology should be well represented in all three dimensions to obtain required location estimation performance. In additional, result show that the primary transmitter location estimation accuracy is not harmfully affected by CR node failures or location perturbations.