Geolocation Based on Signal Level Measurement and Time Advance Inside the Network
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The increasing demands for location-based services in recent years led to provide accurate location information inside the network. The applications for location-based service are assisting emergency request, fraud defense, social media, and marketing. All these demands make the position accuracy highly required. Various techniques and methods have been developed to estimate the position of mobile device inside the network such as RSS, TOA, AOA, and TDOA. In this work, a new method to estimate the accuracy of locating active LTE cellular subscribers. The proposed method is a network-based technique and relies on the Reference Signal Received Power (RSRP) measurements and the predicted cell serving area. It uses LTE measurements and cell information, together with a simple predictive model, for the user equipment (UE) geo-location in two dimensions plan. Additionally, we propose a novel method to combine the timing advance (TA) with signal level measurement to limit the search area and obtain better accuracy. The proposed work is evaluated by comparing estimations with Global Positioning System measurements in various scenarios determined by the number of cells and sites that UE simultaneously reports. In this work, we depend on seven different cases in evaluation started from one reported cell to five reported cells from up to 3 sites.The root mean square error is calculated to validate for both without and with TA. The main result shows how the location accuracy depends on the number of reported sectors and sites. Also, the results are compared between the both methods, the mean RMSE improves by using TA-method between 70m-191m based on cases.