Artificial Intelligence Techniques for Mobile Station Location Estimation

Abstract

Modern wireless communication systems require positioning functions, which provide are automatic location estimation of stations within a network. However, when new networks are implemented, much higher accuracy is required when determining geographical coordinates of a mobile station to develop of services related to the station location. To solve the problem of mobile station positioning, its geographical coordinates are calculated, coordinates of the closest base stations being known. The paper proposes to use a genetic neuro-fuzzy controller for improving the effectiveness of positioning a mobile station. Positioning methods providing usage of artificial intelligence methods are based on measurements of levels for signals from the closets access points or base stations, their coordinates are known. The proposed localization method is based on values of received signal strength indicator – RSSI. At the same time, the RSSI method has a disadvantage – low accuracy, which is proposed to be increased by applying methods of artificial intelligence – fuzzy logic, neural networks, genetic algorithms. Therefore, the objective of this paper is to elaborate an optimized method for determining location of a mobile station. In compliance with the suggested method, RSSI values and ToA values enter the genetic neuro-fuzzy controller, after corresponding processing, the distance from the mobile station to the base station appears at its output.