Mobile User Positioning in GSM/UMTS Cellular Networks

Kos, Tomislav; Grgić, Mislav; Šišul, Gordan

doi:10.1109/elmar.2006.329545

Cited by 35 publications

(16 citation statements)

References 2 publications

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“…These include mobile telephone, or cellular network localisation [12], GPS [13], inertial measurement systems (IMU) [14], laser range-finding systems (LIDAR) [15] and computer vision systems [5]. In addition to these hardware technologies other software technologies can be used to improve localisation estimates.…”

Section: Sources Of Localisation Datamentioning

confidence: 99%

Quantifying the impact of probe vehicle localisation data errors on signalised junction control

Waterson

Box

2012

IET Intell. Transp. Syst.

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This study investigates theoretical signal control algorithms based solely on probe vehicle data. Through development of a simulation system that can model urban signalised junction control using localisation probe data from all vehicles in the local area, improvements in junction operational efficiency that result from the improved input data are demonstrated for both isolated and coordinated junctions. Results from the isolated junction scenario show that the richness of the information contained within probe vehicle data means that control algorithms based just on positions and velocities of vehicles can produce 25% reductions in average delay compared to the current standard control algorithm MOVA. Results from the twin junction scenario confirm the importance of using high-level synchronisation to coordinate closely connected junctions, achieving reductions in average delays (compared to independent control approaches) of up to 40% through a process of weighting the probe vehicle data to reflect prior stage decisions of other parts of the junction. Critical to achieving these benefits, however, is the availability of high localisation accuracy probe data, with results indicating that the levels of accuracy necessary are representative of the typical performance of current in-vehicle global positioning system units, except when those vehicles are operating in urban canyon environments.

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Section: Sources Of Localisation Datamentioning

confidence: 99%

Quantifying the impact of probe vehicle localisation data errors on signalised junction control

Waterson

Box

2012

IET Intell. Transp. Syst.

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“…The serving BS after retrieving the measurements, further appends its geographical location information and forwards them to a TCE, which can then generate the coverage map. The reported geographical coordinates of the UEs and BSs are obtained from positioning techniques, such as OTDOA or A-GPS [4], [5]. However, these techniques are prone to errors, and, hence the reports may be tagged to a wrong location.…”

Section: Autonomous Coverage Estimation Frameworkmentioning

confidence: 99%

“…Location information can be obtained by using positioning techniques, such as observed time difference of arrival (OTDOA) or assisted global positioning system (A-GPS) [4], [5]. For indoor environments, position estimation techniques based on WLAN, radio frequency identification (RFID) and ultrasonic have been proposed [6]- [9].…”

Section: Introductionmentioning

confidence: 99%

Impact of inaccurate user and base station positioning on autonomous coverage estimation

Akbari

Onireti

Imran

et al. 2015

2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD)

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Abstract-Autonomous monitoring of key performance indicators, which are obtained from measurement reports, is well established as a necessity for enabling self-organising networks. However, this reports are usually tagged with geographical location information which are obtained from positioning techniques and are therefore prone to errors. In this paper, we investigate the impact position estimation errors on the cell coverage probability that can be estimated from autonomous coverage estimation (ACE). We derive novel and accurate expressions of the actual cell coverage probability of such scheme while considering: errors in user equipment (UE) location and; errors in both UE and base station location. We present generic expressions for channel modelled with path-loss and shadowing, and much simplified expressions for the path-loss dominant channel model. Our results reveal that the ACE scheme will be suboptimal as long as there are errors in the reported geographical location information. Hence, appropriate coverage margins must be considered when utilising ACE.

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“…Figure 1 shows the basic operation of the triangulation method using CPICH RSCP and RACH PD information, for the estimation of the starting location point of a UMTS call. This procedure is similar to the GSM case [14], where RxLevel and TA data are used instead. The distance of the UE to the best serving BS is estimated using the RACH PD information and the distance to the neighboring BSs is estimated applying a propagation loss model, antenna gain and CPICH transmission power.…”

Section: Triangulationmentioning

confidence: 99%

Localization in Wireless Networks: The Potential of Triangulation Techniques

Osa

Matamales

Monserrat

et al. 2012

Wireless Pers Commun

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User localization is one of the key service-enablers in broadband mobile communications. Moreover, from a different point of view, next steps towards automatic network optimization also depend upon the capability of the system to perform real-time user localization, in order to obtain the traffic distribution. The aim of this paper is to get deeper into the feasibility and accuracy of different localization mechanisms ranging from triangulation to database correlation. Call tracing data extracted from a real operating mobile network have been used to assess these algorithms after the execution of an extensive measurements campaign. Results show that enhanced triangulation offers the best performance even outperforming other more sophisticated mechanisms like fingerprinting, without introducing any change in the network and without requiring any special characteristic of the user equipment. Indeed, the lack of precision of channel estimates, which for the same position could differ up to 10 dB, introduces a large uncertainty that harms localization mechanisms based on database correlation. Finally, this paper identifies the areas for improvement in triangulation to reach its maximum potential, provides details for its implementation and analyzes the performance of the different proposed enhancements.

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Mobile User Positioning in GSM/UMTS Cellular Networks

Cited by 35 publications

References 2 publications

Quantifying the impact of probe vehicle localisation data errors on signalised junction control

Quantifying the impact of probe vehicle localisation data errors on signalised junction control

Impact of inaccurate user and base station positioning on autonomous coverage estimation

Localization in Wireless Networks: The Potential of Triangulation Techniques

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