Mobile location estimation for DS‐CDMA systems using self‐organizing maps

In this paper, a self‐organizing map (SOM) scheme for mobile location estimation in a direct‐sequence code division multiple access (DS‐CDMA) system is proposed. As a feedforward neural network with unsupervised or supervised and competitive learning algorithm, the proposed scheme generates a number of virtual neurons over the area covered by the corresponding base stations (BSs) and performs non‐linear mapping between the measured pilot signal strengths from nearby BSs and the user's location. After the training is finished, the location estimation procedure searches for the virtual sensor which has the minimum distance in the signal space with the estimated mobile user. Analytical results on accuracy and measurement reliability show that the proposed scheme has the advantages of robustness and scalability, and is easy for training and implementation. In addition, the scheme exhibits superior performance in the non‐line‐of‐sight (NLOS) situation. Numerical results under various terrestrial environments are presented to demonstrate the feasibility of the proposed SOM scheme. Copyright © 2006 John Wiley & Sons, Ltd.