Location Determining Technique Using Signal Correlation Method in Suburban Environment

In this study, a Location Determining Technique (LDT) to determine the approximate position of a cellular mobile user in a suburban environment is presented. This LDT uses Signal Correlation Method (SCM) where the Received Signal Strength (RSS) of one Node B is used to approximate the location of the 3G data user in a suburban environment. A new training technique called Unique Sample Undefined Collection (USUC) is introduced for SCM which uses Neural Network to match the current RSS with stored signal strength of Node Bs detected around the User Equipment (UE). With this new technique, the Cumulative Distribution Function (CDF) for location estimation at 67% error distance between the simulated samples and the actual positions of UE was significantly reduced from 379 to 107.4 m, while at 95% of the simulated samples, the error distance remains approximately the same, at 379 m. SCM-USUC may not be suitable for emergency location search but should be utilized by Universal Intelligent Positioning System (UIPS) for tracking location of UE when data or voice services are used especially in larger cell areas, such as in suburban environment.