Return on Investment (roi) for Multi-Technology son juan Ramiro, Mark Austin and Khalid Hamied



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Table B.1 Mean error (mean) and standard deviation (std.) for different X-maps using the real positions and GPS as positioning method

Approach 1 Approach 2


Mean Std.

Mean Std.

Real position

0.0 0.2

2.1 6.6

Position estimate

0.1 2.3

2.6 6.6

Approach 1 strongly depends on the applied positioning method as can be seen in Table B.1. The standard deviation of the X-map based on approach 1 is increased by 2 dB using GPS as positioning method instead of using the real positions. In contrast, approach 2 is not sensitive to the applied positioning method regarding the standard deviation, which is the same for using the real position or a position estimate applying GPS.

B.4. References


  1. 3GPP, Technical Report, Technical Specification Group Radio Access Network (2010) Study on Minimization of Drive-Tests in Next Generation Networks, 3GPP TR 36.805 Version 9.0.0, Release 9, 5 January 2010, http:// www.3gpp.org/ftp/Specs/archive/36_series/36.805/36805-900.zip (accessed 3 June 2011).

  2. 3GPP, Technical Specification, Technical Specification Group Radio Access Network (2010) Stage 2 Functional Specification of User Equipment (UE) positioning in E-UTRAN”, 3GPP TS 36.305 Version 9.2.0, Release 9, 28 April 2010, http://www.3gpp.org/ftp/Specs/archive/36_series/36.305/36305-920.zip (accessed 3 June 2011).

  3. 3GPP, Technical Report, Technical Specification Group Radio Access Network (2009) Self-Configuring and Self-Optimizing Network Use Cases and Solutions, 3GPP TR 36.902 Version 9.0.0, Release 9, 9 October 2009, http://www.3gpp.org/ftp/Specs/archive/36_series/36.902/36902-900.zip (accessed 3 June 2011).

  4. van den Berg, J.L., Litjens, R., Eisenblätter, A., Amirijoo, M., Linnell, O., Blondia, C., Kürner, T., Scully, N., Oszmianski, J. and Schmelz, L.C. (2008) Self-Organisation in Future Mobile Communication Networks, Proc. ICT - Mobile Summit 2008, Stockholm, Sweden, June 10–12 2008.

  5. Catovic, A. and Dills, J.F.M.M.K. (2009) Apparatus and method for generating performance measurements in wireless networks, Patent US 2009/0310501, issued December 2009.

  6. Brunner, C. and D. Flore, D. (2009) Generation of Pathloss and Interference Maps as SON Enabler in Deployed UMTS Networks, Proc. IEEE 69th Vehicular Technology Conference (VTC 2009-Spring), pp. 1–5.

  7. COST 231 (1999) Final Report http://www.lx.it.pt/cost231/ (accessed 3 June 2011).

  8. Erik, A. and S. Holm, S. (2004) Tuning of Empirical Radio Propagation Models Effect of Location Accuracy, Wireless Personal Communications, 30, pp. 267–281, Kluwer Academic Publishers, Dordrecht.

  9. Clancy, J.G. (2003) Clutter database enhancement methodology, Patent US 6,580,911 B1, issued June 2003.

  10. SOCRATES Project (2009) Deliverable: Review of use cases and framework II, December 2009, http://www. fp7-socrates.eu (accessed 3 June 2011).

  11. Fritsche, C. and Klein, A. (2008) Cramér-Rao Lower Bounds for Hybrid Localization of Mobile Terminals, Proc.

1 For example, Microsoft Excel has a simple multi-regression solver with the LINEST() command.

2 A chip corresponds to 0.26 ms or 78 m.

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