Mobile Location Algorithm Based On LTE Signaling Data

In recent years,mobile phones have become an indispensable part of people's lives.According to statistics,the number of global mobile phone users in 2017 has exceeded 4billion,of which the number of 4G users more than 1 billion.As the 4G LTE network be widely deployed,each call between the phone,and each interaction with the base station will produce massive signaling data.The location information of the user can be extracted from these signaling data,therefore,based on signaling data,we can locate users in real time.With the massive user's real-time location information,we can apply it to reveal the user travel habits,dealing with urban planning,traffic navigation and traffic prediction and other fields.In order to overcome the shortcomings of traditional positioning system like GPS in a certain scene with low accuracy,high energy consumption,this paper proposes a new mobile positioning system based on signaling data,which named LTETrack.LTETrack tries to solve how to use the signaling data accurately and effectively to calculate the user's historical driving track,so as to obtain the real-time location of the user.First,LTETrack only uses the data contained in the LTE standard,without having to change any hardware device or use special software to obtain special data.By analyzing a large number of signaling data,we found that the TA data in the base station has the characteristics of stable stability and low noise,and is suitable for mobile positioning method.The TA value is defined as the length of time that the signal in the LTE standard arrives at the base station from the handset.Based on the TA value,we can get the distance between the mobile user and the base station.While obtaining TA data does not require additional data acquisition costs.In addition,due to the huge number of mobile phone users,it's easy to access massive data,so LTETrack is suitable for large-scale applications.LTETrack uses the new filtering algorithm to filter out the most accurate TA data,and then uses the improved map matching algorithm based on the hidden Markov model to locate the user.We also use RSRP(signal received power)data as a criterion for judging whether the user is moving.We collected about 800 km of travel data in Dalian.The experimental results show that the trajectory matching accuracy of LTETrack in the urban area is close to the GPS positioning result,and the positioning accuracy of the LTETrack has high positioning accuracy in the specific scene(remote area,tunnel and so on).