In the field of mobile application, location base services have been an interesting topic for researchers. The following research works in mobile location in GSM network have been reported in journal publication and reviewed in this section.
Mobile location estimation using an interpolative neural network was proposed in (Chien-Sheng, Jium-Ming, and Chin-Tan, 2013). It used three angles of arrival measurement to achieve a better result than the analytical (the weighted average and optimal position) in the presence of noisy and NLOS measurement error. The neural network uses its ability to memorize and generalize data to interpolate the measured angles to estimate the mobile position. In order to avoid over-fitting of the network, the training of the neural network was done with ideal patterns gotten from the mathematical relationship that exists between the angles of arrival and the mobile position. The performance of this technique is highly dependent on the noisy and NLOS measurements of AOA, and the mobile propagation environment.