Localization in Real GSM Network with Fingerprinting Utilization (original) (raw)
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On the Accuracy Improvement Issues in GSM Location Fingerprinting
IEEE Vehicular Technology Conference, 2006
Determining the position of mobile users in GSM networks has become more and more important. Such services as emergency calls and other location dependent services have been of great importance in the last years. A key factor for the success of any localization technology is its accuracy. This work is focused on localization in a dense urban scenario or in any other area where the GPS signal is not available or its error is very big due to some obstruction of the satellites. Different methods such as those based on neural network localization, database correlation, dead reckoning and a tracking algorithm in case of user mobility have been examined in this work in order to find the optimal in terms of accuracy. The pre-processing of the received signal strengths (rss) is performed to reduce the positioning error due to the rssstochastic behaviour. Results show that, a tracking algorithm using NN positioning results and an extended Kalman filter (EKF) supplies better results in case of mobility of the user.
A Low-cost Fingerprint Positioning System in Cellular Networks
2007 Second International Conference on Communications and Networking in China, 2007
An ultimate aim of mobile positioning research is to find a method providing high estimation accuracy to the user within minimum delay and at minimum cost. Conventional location techniques based on trilateration and triangulation rely on line-of-sight path between the base station antenna and the mobile unit. In densely built urban areas, this assumption is rarely valid. This fact degrades the location performance of the conventional techniques and motivates the need for development of more accurate technique suited for these areas. Positioning system developed in this research is divided into three sub-systems. The first sub-system solves the problems related to fingerprint localization and involves neural network as key element of the positioning algorithm. The postprocessing tasks which include tracking and map-matching are performed in the second and third sub-systems respectively.
Automatic Positioning of Mobile Users via GSM Signal Measurements
Automatic Positioning of Mobile Users via GSM Signal Measurements, 2021
Today the need for mobile communication systems and the high increase in the number of users have also made the development of new generation mobile applications indispensable. Obtaining location information has been one of the most interesting and significant areas of improvement. The purpose of the services used to determine the location is generally to obtain the information of the users such as approximate location, speed, and time. The GPS is the most preferred and globally accurate positioning system among global positioning systems. However, in addition high installation cost of the system; galactic and meteorological factors, high buildings, other physical obstacles, and especially indoor areas are some of the main constraints that can lead to serious signal degradation and losses which may cause the system to be out of service. In this context, there is an urgent need for positioning systems that will be alternative and complementary to global positioning systems. The cellular network is widely used by almost everyone and its coverage area is increasing day by day. The network has been trained and tested in the simulation environment using machine learning algorithms, namely, extreme learning machine (ELM), generalized regression neural network (GRNN), and nearest neighborhood (NN). When compared to other cellular localization methods in the literature, the proposed system performs positioning with much higher accuracies with distance error rates below a meter (m) at minimum, and between 76-216 m on average. The test results show that it can successfully localize the mobile users with a significant accuracy for indoor, where GPS signals are very weak or cannot be received at all; and it can also stand in the breach for outdoor, where GPS may be disabled for different reasons.
An Improved Cellular positioning technique based on Database Correlation
2008
The paper proposes an improved network-based positioning technique based on database correlation and presents the application of the proposed technique to GSM. The fingerprint database is created using field measurements and a novel and a more practical method for gathering fingerprints is introduced. The authors propose a Weighted k-Nearest Neighbor (WkNN) method for location estimation and the trial results obtained in urban and suburban environments in Sri Lanka are presented. Comparison with the Geometrical method shows that the proposed method is a competitive alternative for GSM location.
International Journal of Electrical and Computer Engineering (IJECE), 2021
The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user's location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario.
User positioning system for mobile devices
2013 Federated Conference on Computer Science and Information Systems, 2013
In the recent years, the Global Positioning System (GPS) has become a standard for the location and navigation for a huge number of people all over the world. This system is unquestionably one of the most significant developments of the twentieth century. GPS employs a great variety of applications from car navigation and cellular phone emergency positioning even to aeronautic positioning. Despite the fact that it plays an essential role in today's world, GPS has some limitations. The main disadvantage is the inability to operate inside the buildings because of the loss of signal from the satellites. During the last decade, the interest in location based services has significantly increased. It is related to the existence of ubiquitous computers and context awareness of mobile devices. Information about the position plays the great role in the field of security, logistics and convenience nowadays. Thus, it is necessary to fill the gap at the point where Global Positioning System does not perform satisfactorily.
Using of GSM and Wi-Fi Signals for Indoor Positioning Based on Fingerprinting Algorithms
Advances in Electrical and Electronic Engineering, 2015
In the paper framework for indoor positioning utilizing Wi-Fi and GSM signals is introduced. Nowadays, indoor positioning is a very attractive topic for researchers, since accurate and reliable positioning system can unlock new market to service providers. In this paper we will analyse the use of Wi-Fi and GSM signals and their combination for the fingerprinting based positioning in the indoor environment. Performance of positioning system in terms of accuracy was analysed using simulations. In the simulations the position of the mobile device was estimated in three ways, when only GSM signals were used, when only Wi-Fi signals were utilized and when a combination of both signals was used. Three positioning algorithms from the Nearest Neighbour (NN) family were used in the simulations. Simulations were performed in the simulation model created in MATLAB environment.
Fingerprinting based localization of mobile terminals
2011
This dissertation is a collection of our approaches to solve the problem of mobile terminal (MT) location estimation. Main focus is on fingerprinting based localization methods which are suitable for multipath and NLoS environments. This feature is one of the many advantages of fingerprinting methods over "traditional" geometrical localization methods, i.e., they exploit multipath and NLoS conditions instead of trying to mitigate them. Hence a curse for "traditional" geometrical localization methods turns into a blessing for fingerprinting methods. This characteristic property of fingerprinting algorithms makes them a promising solution for MT localization problem. Being inspired from this, we steered our research direction towards this field and we can categorize our studies into the following main groups: • development of new, high precision fingerprinting-based localization algorithms which get use of an additional dimension (Doppler dimension), I know that, without the love of my family, I would not be able to accomplish any of my achievements in my life. Hence, my deepest gratitudes go to them, to my parents, Bahri and Esen and to my brothers, Fatih and Sinan. I feel very lucky to be a member of this family. And you, my dear father, you could not have the chance to see that I became a doctor. You have always been the person who inspired me the most in my life with your everlasting energy, cheer, honesty and strong character. Although it is a negligible present compared to what you have given to me, I dedicate my PhD to you.
Location Fingerprinting in GSM network and Impact of Data Pre-processing
Different techniques for locating the user terminal in cellular networks have been developed in the recent years. This paper proposes a method which is designed to obtain optimal performance in urban environments. Such performance metrics as accuracy, cost, reliability, scalability, and demanding effort are the key points in this paper. A fingerprint method is used for some of these reasons: firstly, no additional hardware is required for it implementation to existing networks. Secondly, compared to other methods, this one performs better in areas with significant multipath propagation. Due to the big demanding effort during radio signal strength (RSS) collection from the streets to realize a fingerprint database, predicted RSS data of the concerned area are rather used. The high sensitivity of the RSS to the environmental changes is taken into account. A system is developed which calibrates the predicted RSS on basis of a sample real collected RSS. A robust neural network (NN) architecture and training algorithm are used in the positioning unit in order to get a good mapping between locations and RSS.
Using of mobile device localization for several types of applications in mobile information systems
Abstract. The area of interest is in a model of a radio-frequency based system enhancement for locating and tracking users of our information system inside the buildings. The developed framework as it is described here joins the concepts of location and user tracking as an extension for a new type of mobile information systems. The realized framework uses a WiFi network infrastructure to let a mobile device determine its indoor position. User location can be used by several types of applications.