Geo-localization services are an important functionality in cellular networks. Besides, the use of Ultra Dense Networks and small cells, in current and future cellular networks, greatly increases the complexity of centralized localization approaches. Consequently, we propose a Self-Synchronization Positioning Estimation (SSPE) algorithm that estimates the transmitter position in a distributed fashion. The proposed SSPE algorithm reaches consensus for the posterior distribution of the transmitter position rather than on the final estimates. Such consensus ensures that the proposed SSPE algorithm converges to the centralized Direct Positioning Estimation (DPE) approach, which has the best performance of all localization approaches. We show that the proposed algorithm is related to the Iterative Positioning Estimation (IPE) algorithm, since both exploit the self-synchronization mechanism. As a result, the improvements and extensions for IPE, previously studied in other works, can be directly applied to the proposed SSPE algorithm. In addition, the proposed algorithm is able to localize the transmitter even when it is not time synchronized with the network as it is usually the case. The performance of the algorithms is numerically assessed through Monte-Carlo simulations by the mean distance error and mean range offset error. Finally, we not only show that our approach gets close to the DPE performance after a few iterations, but also that it converges for different logical network configurations.