On the optimisation of practical wireless indoor and outdoor microcells subject to QOS constraints

Wireless indoor and outdoor microcells (WIOMs) have emerged as a promising means to deal with a high demand of mobile users for a variety of services. Over such heterogeneous networks, the deployment of WIOMs costs mobile/telecommunications company high capital expenditures and operating expenses. This paper aims at optimising the WIOMs taking into account various network communication environments. We first develop an optimisation problem to minimise the number of cells as well as determining their optimal locations subject to the constraints of the coverage and quality-of-service (QoS) requirements. In particular, we propose a binary-search based cell positioning (BSCP) algorithm to find the optimal number of cells given a preset candidate antenna positions. The proposed BSCP algorithm is shown to not only reduce the number of cells for saving resources but also requires a low computational complexity compared to the conventional approaches with exhaustive search over all available sites. Moreover, EDX SignalPro is exploited as a simulation platform to verify the effectiveness of the proposed BSCP for the WIOMs with respect to various propagation modes and antenna parameters of different types, including isotropic, multiple-input single-output and multiple-input multiple-output

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

Locating Small Cells Using Geo-located UE Measurement Reports & RF Fingerprinting

This paper proposes a number of methods to determine potential small cell site locations using geo-located UE measurement reports in order to maximise the traffic offload from the macrocell network onto the small cells. The paper also shows how the information contained within the measurement reports can be used to create “RF fingerprints#x201D; which in turn can be used to discard UE measurement reports with erroneous location information and by doing so increase the effectiveness of the small cell placement algorithm. Simulations are presented which suggest that when addressing traffic hotspots in central London using small cells with coverage radii of 50m and 100m, the gains provided by the placement algorithms using simple RF fingerprinting technique are significant for UE reports with large location errors (>100m RMS error) when compared to techniques not using RF fingerprinting