Access Point topology evaluation and optimization based on Cramér-Rao Lower Bound for WLAN indoor positioning

WLAN Access Point network is typically optimized for communication scope, and not for localization. It is thus important to understand the positioning accuracy limits under a certain given Access Point topology and to be able to make design recommendations if the Access Point topology can be adapted better for the navigation needs. This paper calculates a Cramér-Rao Lower Bound -based criterion for Received Signal Strength -based positioning. Two study cases are presented about how the proposed criterion can be used to choose the optimal Access Point density and the optimal Access Point topology in a network designed for positioning purposes. In addition, our Cramér-Rao Lower Bound-based criterion can also be used to estimate the expected accuracy bound in an existing network, based on its underlying Access Point density or topology. Measurement-based results are used to verify our proposed approach.

[1]  Shih-Hau Fang,et al.  A Novel Access Point Placement Approach for WLAN-Based Location Systems , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[2]  Wee-Seng Soh,et al.  Cramer-Rao Bound Analysis of Localization Using Signal Strength Difference as Location Fingerprint , 2010, 2010 Proceedings IEEE INFOCOM.

[3]  Gonzalo Seco-Granados,et al.  Challenges in Indoor Global Navigation Satellite Systems: Unveiling its core features in signal processing , 2012, IEEE Signal Processing Magazine.

[4]  H. Mabed,et al.  Wi-Fi access point placement within stand-alone, hybrid and combined wireless positioning systems , 2012, 2012 Fourth International Conference on Communications and Electronics (ICCE).

[5]  Edoardo Amaldi,et al.  Optimizing the placement of anchor nodes in RSS-based indoor localization systems , 2013, 2013 12th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET).

[6]  Pedro Figueiredo Silva,et al.  Received signal strength models for WLAN and BLE-based indoor positioning in multi-floor buildings , 2015, 2015 International Conference on Location and GNSS (ICL-GNSS).

[7]  Alexandre Caminada,et al.  The Impact of AP Placement in WLAN-Based Indoor Positioning System , 2009, 2009 Eighth International Conference on Networks.

[8]  Laurence T. Yang,et al.  Placement of Access Points for Indoor Wireless Coverage and Fingerprint-Based Localization , 2013, 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing.

[9]  Mohammed Khider,et al.  On-line training of the path-loss model in Bayesian WLAN indoor positioning , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[10]  R. Michael Buehrer,et al.  Handbook of Position Location: Theory, Practice and Advances , 2011 .

[11]  Emin Anarim,et al.  Location estimation using RSS measurements with unknown path loss exponents , 2013, EURASIP J. Wirel. Commun. Netw..

[12]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[13]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[14]  Alfred O. Hero,et al.  Relative location estimation in wireless sensor networks , 2003, IEEE Trans. Signal Process..

[15]  Prashant Krishnamurthy,et al.  Modeling of indoor positioning systems based on location fingerprinting , 2004, IEEE INFOCOM 2004.

[16]  Károly Farkas,et al.  Optimization of Wi-Fi Access Point Placement for Indoor Localization , 2013 .

[17]  Youngsu Cho,et al.  Improved Wi-Fi AP position estimation using regression based approach , 2013 .

[18]  Elena Simona Lohan,et al.  WLAN and RFID Propagation channels for hybrid indoor positioning , 2014, International Conference on Localization and GNSS 2014 (ICL-GNSS 2014).

[19]  Simo Ali-Löytty,et al.  A comparative survey of WLAN location fingerprinting methods , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[20]  Markku Renfors,et al.  Statistical path loss parameter estimation and positioning using RSS measurements in indoor wireless networks , 2012, 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[21]  Shih-Hau Fang,et al.  Accurate Indoor Location Estimation by Incorporating the Importance of Access Points in Wireless Local Area Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[22]  Elena Simona Lohan,et al.  Deconvolution-based indoor localization with WLAN signals and unknown access point locations , 2013, 2013 International Conference on Localization and GNSS (ICL-GNSS).