Estimating the primary user location and transmit power in cognitive radio systems using extended Kalman filters

In cognitive radio systems, the primary user location and transmit power are valuable information in order to create an efficient secondary network that uses spatial spectrum holes without introducing interference to the primary users. Since primary users cannot be assumed to cooperate, their locations and transmit powers need to be estimated at the secondary users. Existing localization techniques, based on the received signal strength require a high amount of secondary users in order to achieve a high accuracy while direction of arrival based methods alone suffer from the random secondary user positions and the requirements for making the associated devices portable. In this paper we propose a hybrid solution using an extended Kalman filter that is able to localize a moving primary user and estimate its transmit power under the aforementioned conditions. Its performance is compared to an extended Kalman filter that uses only direction of arrival estimation by means of Monte Carlo simulations, and shown to clearly outperform the DOA-only based processing.