Localization in Wireless Networks: The Potential of Triangulation Techniques

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. © 2012 Springer Science+Business Media, LLC.The authors would like to thank the funding received from the Ministerio de Industria, Turismo y Comercio within the Project number TSI-020100-2010-183 and from the Generalitat Valenciana IMIDTA/2010/800 funds.Osa Ginés, V.; Matamales Casañ, J.; Monserrat Del Río, JF.; López Bayo, J. (2013). Localization in Wireless Networks: The Potential of Triangulation Techniques. Wireless Personal Communications. 68(4):1525-1538. https://doi.org/10.1007/s11277-012-0537-2S15251538684Laiho J., Wacker A., Novosad T. (2006) Radio Network Planning and Optimisation for UMTS 2nd Edn. Wiley, AmsterdamOsa V., Matamales J., Monserrat J. et al (2010) Expert systems for the automatic optimisation of 3G networks. WAVES 2: 97–105Gustafsson F., Gunnarsson F. (2005) Mobile positioning using wireless networks: Possibilites and fundamental limitations based on available wireless network measurements. IEEE Signal Processing Magazine 22(4): 41–53. doi: 10.1109/MSP.2005.1458284Gezici S. (2008) A survey on wireless position estimation. Springer Wireless Personal Communications 44(3): 263–282. doi: 10.1007/s11277-007-9375-zBahillo, A., Mazuelas, S., & Lorenzo, R.M., et al. (2010). Accurate and integrated localization system for indoor environments based on IEEE 802.11 round-trip time measurements.EURASIP Journal on Wireless Communications and Networking, 2010, Article ID 102095, p. 13. doi: 10.1155/2010/102095 .Yang Z., Liu Y. (2010) Quality of trilateration: Confidence-based iterative localization. IEEE Transactions on Parallel and Distributed Systems 21(5): 631–640. doi: 10.1109/TPDS.2009.90Zimmermann, D., et al. (2004). Database correlation for positioning of mobile terminals in cellular networks using wave propagation models. In IEEE 60th Vehicular Technology Conference (Vol. 7, pp. 4682–4686) doi: 10.1109/VETECF.2004.1404980 .Zhao Y. (2002) Standardization of mobile phone positioning for 3G systems. IEEE Communications Magazine 40(7): 108–116. doi: 10.1109/MCOM.2002.1018015Caffery J.J., Stuber G.L. (1998) Overview of radiolocation in CDMA cellular systems. IEEE Communications Magazine 36(4): 38–45. doi: 10.1109/35.667411Kaaranen H., Ahtiainen A., Laitinen L., Naghian S., Niemi V. (2005) UMTS networks: Architecture, mobility and services. Wiley, Amsterdam3GPP. (2010). TS 25.215 Physical layer; Measurements (FDD). http://www.3gpp.org/ftp/Specs/archive/25_series/25.215/25215-920.zip .3GPP. (2010). TS 25.133 Requirements for support of radio resource management. http://www.3gpp.org/ftp/Specs/archive/25_series/25.133/25133-950.zip .3GPP. (2009). TS 45.010 Radio subsystem synchronization. http://www.3gpp.org/ftp/Specs/archive/45_series/45.010/45010-900.zip .Kos, T., Grgic, M., & Sisul, G. (2006). Mobile user positioning in GSM/UMTS cellular networks. In 48th International Symposium ELMAR-2006 focused on multimedia signal processing and communications (pp. 185–188). doi: 10.1109/ELMAR.2006.329545 .Kirkpatrick S., Gelatt C. D. Jr., Vecchi M. P. (1983) Optimization by simulated annealing. Science 220(4598): 671–680. doi: 10.1126/science.220.4598.671Hepsaydir, E. (1999). Analysis of mobile positioning measurements in CDMA cellular networks. In Radio and Wireless Conference, RAWCON 99 (pp. 73–76). doi: 10.1109/RAWCON.1999.810933 .Villebrun, E., Ben Hadj Alaya, A., Boursier, Y., & Noisette, N. (2006). Indoor Outdoor user discrimination in mobile wireless networks. In Vehicular Technology Conference 2006 Fall (pp. 1–5, 25–28). doi: 10.1109/VTCF.2006.500 .Farr, T.G., et al. (2007). The shuttle radar topography mission. Reviews of geophysics, Vol. 45, RG2004, 33 pp. doi: 10.1029/2005RG000183

Bayesian algorithms for mobile terminal positioning in outdoor wireless environments

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Cellular positioning in WCDMA networks using pattern matching.

Cellular positioning has opened the doors for various creative technological expansions in the field of Location Based Services, in addition to the safety function that it allows for. Despite the significant advances in cellular positioning, the developing and third world countries are being left behind. Better levels of accuracies are required in these nations where the majority of the population cannot afford GPS-enabled phones. The pattern matching technique is focused on in this research. It involves studying signal patterns from the Base Stations to a mobile phone, to obtain fingerprints at each reference location to form a database. During the location estimation process, the observed fingerprint is compared with the database, and a subsequent match is made. The primary advantage of this technique is that high accuracies can be achieved with minimal costs. This research focuses on studying the efficiency and accuracy of various pattern matching techniques which are investigated in both WCDMA and GSM networks in suburban areas in South Africa. Since certain areas have predominantly GSM coverage, it is necessary to include GSM network in this research. In addition, the inclusion of both GSM and WCDMA network data can be beneficial as it provides further criteria for correlation. Field measurements are carried out to obtain the Radio Frequency measurements that are needed to construct the database. Various methods are analyzed and enhanced to obtain better levels of accuracies during the correlation process of the pattern matching procedure. This includes investigating the effects of penalty terms, weights, map matching, Exponential and Least Means Square approaches, as well as the use of measurements from GSM, WCDMA, and the combined networks. High levels of accuracies were obtained and it can be concluded that these techniques do work in a suburban area, irrespective of its geographical location. The literature study shows that some of these pattern matching techniques would also yield good results in urban areas, while other techniques are more suitable for rural areas

Investigation of indoor localization with ambient FM radio stations

Localization plays an essential role in many ubiquitous computing applications. While the outdoor location-aware services based on GPS are becoming increasingly popular, their proliferation to indoor environments is limited due to the lack of widely available indoor localization systems. The de-facto standard for indoor positioning is based on Wi-Fi and while other localization alternatives exist, they either require expensive hardware or provide a low accuracy. This paper presents an investigation into localization system that leverages signals of broadcasting FM radio stations. The FM stations provide a worldwide coverage, while FM tuners are readily available in many mobile devices. The experimental results show that FM radio can be used for indoor localization, while providing longer battery life than Wi-Fi, making FM an alternative to consider for positioning.Comment: 10th IEEE Pervasive Computing and Communication conference, PerCom 2012, pp. 171 - 17

Space-partitioning with cascade-connected ANN structures for positioning in mobile communication systems

The world around us is getting more connected with each day passing by – new portable devices employing wireless connections to various networks wherever one might be. Locationaware computing has become an important bit of telecommunication services and industry. For this reason, the research efforts on new and improved localisation algorithms are constantly being performed. Thus far, the satellite positioning systems have achieved highest popularity and penetration regarding the global position estimation. In spite the numerous investigations aimed at enabling these systems to equally procure the position in both indoor and outdoor environments, this is still a task to be completed. This research work presented herein aimed at improving the state-of-the-art positioning techniques through the use of two highly popular mobile communication systems: WLAN and public land mobile networks. These systems already have widely deployed network structures (coverage) and a vast number of (inexpensive) mobile clients, so using them for additional, positioning purposes is rational and logical. First, the positioning in WLAN systems was analysed and elaborated. The indoor test-bed, used for verifying the models’ performances, covered almost 10,000m2 area. It has been chosen carefully so that the positioning could be thoroughly explored. The measurement campaigns performed therein covered the whole of test-bed environment and gave insight into location dependent parameters available in WLAN networks. Further analysis of the data lead to developing of positioning models based on ANNs. The best single ANN model obtained 9.26m average distance error and 7.75m median distance error. The novel positioning model structure, consisting of cascade-connected ANNs, improved those results to 8.14m and 4.57m, respectively. To adequately compare the proposed techniques with other, well-known research techniques, the environment positioning error parameter was introduced. This parameter enables to take the size of the test environment into account when comparing the accuracy of the indoor positioning techniques. Concerning the PLMN positioning, in-depth analysis of available system parameters and signalling protocols produced a positioning algorithm, capable of fusing the system received signal strength parameters received from multiple systems and multiple operators. Knowing that most of the areas are covered by signals from more than one network operator and even more than one system from one operator, it becomes easy to note the great practical value of this novel algorithm. On the other hand, an extensive drive-test measurement campaign, covering more than 600km in the central areas of Belgrade, was performed. Using this algorithm and applying the single ANN models to the recorded measurements, a 59m average distance error and 50m median distance error were obtained. Moreover, the positioning in indoor environment was verified and the degradation of performances, due to the crossenvironment model use, was reported: 105m average distance error and 101m median distance error. When applying the new, cascade-connected ANN structure model, distance errors were reduced to 26m and 2m, for the average and median distance errors, respectively. The obtained positioning accuracy was shown to be good enough for the implementation of a broad scope of location based services by using the existing and deployed, commonly available, infrastructure

Performance Evaluation of Mobile U-Navigation based on GPS/WLAN Hybridization

This paper present our mobile u-navigation system. This approach utilizes hybridization of wireless local area network and Global Positioning System internal sensor which to receive signal strength from access point and the same time retrieve Global Navigation System Satellite signal. This positioning information will be switched based on type of environment in order to ensure the ubiquity of positioning system. Finally we present our results to illustrate the performance of the localization system for an indoor/ outdoor environment set-up.Comment: Journal of Convergence Information Technology(JCIT