A Real-Time Laboratory Testbed For Evaluating Localization Performance Of WIFI RFID Technologies

I Abstract A realistic comparative performance evaluation of indoor Geolocation systems is a complex and challenging problem facing the research community. This is due to the fact that performance of these systems depends on the statistical variations of the fading multipath characteristics of the wireless channel, the density and distribution of the access points in the area, and the number of the training points used by the positioning algorithm. This problem, in particular, becomes more challenging when we address RFID devices, because the RFID tags and the positioning algorithm are implemented in two separate devices. In this thesis, we have designed and implemented a testbed for comparative performance evaluation of RFID devices in a controlled and repeatable laboratory environment. The testbed consists of a real-time RF channel simulator, several WiFi 802.11 access points, commercial RFID tags, and a laptop loaded with the positioning algorithm and its associated user interface. In the real-time channel simulator, the fading multipath characteristics of the wireless channel between the access points and the RFID tags is modeled by a modified site-specific IEEE 802.11 channel model which combines this model with the correlation model of shadow fading existing in the literature. The testbed is first used to compare the performance of the modified IEEE 802.11 channel model and the Ray Tracing channel model previously reported in the literature. Then, the testbed with the new channel model is used for comparative performance evaluation of two different WiFi RFID devices.

[1]  H. Aghababa,et al.  Minimizing the error of time difference of arrival method in mobile networks , 2005, Second IFIP International Conference on Wireless and Optical Communications Networks, 2005. WOCN 2005..

[2]  B. Alavi,et al.  Distance Measurement Error Modeling for Time-of-Arrival Based Indoor Geolocation , 2006 .

[3]  Ainslie,et al.  CORRELATION MODEL FOR SHADOW FADING IN MOBILE RADIO SYSTEMS , 2004 .

[4]  T. Jamsa,et al.  Implementation techniques of broadband radio channel simulators , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[5]  Ahmad Hatami Application of Channel Modeling for Indoor Localization Using TOA and RSS , 2006 .

[6]  K. Pahlavan,et al.  Analysis of the effects of handoff on the performance of tactical communication systems using WLANs , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[7]  David Kotz,et al.  Risks of Using AP Locations Discovered Through War Driving , 2006, Pervasive.

[8]  K. Pahlavan,et al.  Comparative statistical analysis of indoor positioning using empirical data and indoor radio channel models , 2006, CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006..

[9]  Real-time locating systems. , 2009, Health devices.

[10]  D. Deavours UHF EPC tag performance evaluation , 2005 .

[11]  K. Pahlavan,et al.  Performance evaluation of indoor geolocation systems using PROPSim hardware and ray tracing software , 2004, International Workshop on Wireless Ad-Hoc Networks, 2004..

[12]  Kaveh Pahlavan,et al.  A comparative performance evaluation of RSS-based positioning algorithms used in WLAN networks , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[13]  V. Erceg,et al.  TGn Channel Models , 2004 .

[14]  Kaveh Pahlavan,et al.  A computer graphics package for indoor radio channel simulation using a 2D ray tracing algorithm , 1992, [1992] Proceedings 17th Conference on Local Computer Networks.

[15]  Kaveh Pahlavan,et al.  RFID Technology and Applications: Performance evaluation of WiFi RFID localization technologies , 2008 .

[16]  Kaveh Pahlavan,et al.  Indoor geolocation in the absence of direct path , 2006, IEEE Wireless Communications.

[17]  Michael J. Rycroft,et al.  Understanding GPS. Principles and Applications , 1997 .