Cellular positioning using fingerprinting based on observed time differences (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.
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.
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.
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.
Localization in Real GSM Network with Fingerprinting Utilization
2010
This paper attempts to present current state in the area of user localization in cellular networks and shows custom solution for positioning using pocket computer and fingerprint method also known as fingerprinting. It operates in Global System for Mobile communications (GSM) network, although fingerprinting is also applicable in other wireless networks, such as Universal Mobile Telecommunications System (UMTS), Bluetooth or 802.11. Implementation is explained and it is compared to existing solutions. The performance of the system is evaluated for various scenarios by statistical characteristics and Circular Error Probability (CEP). The scenarios are proposed from observation of various parameters that influence the localization accuracy.
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.
2011
Depuis plusieurs annees, le positionnement de terminal mobile recoit un interet particulierement grand. Il existe de nombreux algorithmes developpes pour le probleme de localisation MT. Les methodes traditionnelles de localisation geometrique sont concues pour fonctionner sous les conditions de line-of-sight (LoS). Cependant, les conditions LoS pourraient ne pas etre toujours presentes entre la station de base (BS) et le MT. Par consequent, les techniques de localisation basee sur fingerprinting qui sont egalement l’objet de cette these attirent l’attention en raison de leur capacite a travailler aussi en multi trajet et dans des environnements non-line-of-sight (NLoS). Dans cette these, nous introduisons de nouveaux algorithmes de fingerprinting, a savoir l’algorithme de power delay Dopplerprofile- fingerprinting (PDDP-F) qui exploite la mobilite du MT. Le but est d’augmenter la precision de localisation en utilisant la dimension Doppler. Nous etudions egalement les performances de...
CellSense: An Accurate Energy-Efficient GSM Positioning System
Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this paper, we present CellSense, a probabilistic RSSI-based fingerprinting location determination system for GSM phones. We discuss the challenges of implementing a probabilistic fingerprinting localization technique in GSM networks and present the details of the CellSense system and how it addresses these challenges. We then extend the proposed system using a hybrid technique that combines probabilistic and deterministic estimation to achieve both high accuracy and low computational overhead. Moreover, the accuracy of the hybrid technique is robust to changes in its parameter values. To evaluate our proposed system, we implemented CellSense on Android-based phones. Results from two different testbeds, representing urban and rural environments, for three different cellular providers show that CellSense provides at least 108.57% enhancement in accuracy in rural areas and at least 89.03% in urban areas compared to the current state of the art RSSI-based GSM localization systems. In additional, the proposed hybrid technique provides more than 6 times and 5.4 times reduction in computational requirements compared to the state of the art RSSI-based GSM localization systems for the rural and urban testbeds respectively. We also evaluate the effect of changing the different system parameters on the accuracy-complexity tradeoff and how the cell towers density and fingerprint density affect the system performance.
2009
An extensive research has been carried out to evaluate method for the tracking of mobile equipment using it's base stations in a GSM network. Enhanced Observed Time Difference (E-OTD) method is one of the promising and fairly developed positioning technologies that has been standardized for GSM systems. This Method has been utilized in this research work to locate the mobile equipment's position. Urban-area measurements were performed in an area consisting of both micro GSM900 and GSM1800 cells. Measurements were carried out in a rural area with macro-cell structure having diameters of 20 to 30 kilometers. Simulation runs were performed with only two neighbouring BTSs, to show the difference when three or four BTSs are used in the E-OTD location estimate calculation. The location accuracy increases when E-OTD is performed with four or more BTSs. The difference in the location estimate when more than four or just four BTSs are involved, is found to be minimum.