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The radio spectrum in wireless communication systems is being allocated up quickly with ever increasing demands in wireless industries. Cognitive radio is a way of opportunistically sharing the scare spectrum among primary and secondary users of the spectrum. The key challenge in deploying cognitive radio networks is to find out the spectrum holes in the primary wireless systems in order to allow the secondary users to operate. In this paper, we present novel localization algorithms based on grid-search and EM (expectation maximization) methods under the GMM (Gaussian mixture model) to find out the positions of the base stations and identify the spatial spectrum holes for cognitive radio deployments. Under this approach, we model the problem as localizing multiple unknown radio sources using a mobile measurement station, which is different from the problem modeling of many previous localization solutions. We evaluate our localization algorithms using both simulations and experiments.