Optimization model for an Indoor WLAN-based Positioning System

Nowadays, Indoor Positioning Systems capitalize on the existing wireless local area network infrastructure and are very popular and attractive. However, most systems only focus on the network deployment for positioning but overlook that the original purpose of these WLAN infrastructures is providing the required connectivity. In this paper, we propose an innovative approach where WLAN planning and positioning error reduction are modeled as an optimization problem and tackled together during the WLAN planning process. A Mono-objective algorithm called Variable Neighborhood Search (VNS) is implemented. The simulations results demonstrate that this approach is highly efficient in solving the indoor positioning optimization problem.

[1]  Jean-Marie Gorce,et al.  Mono- and multiobjective formulations for the indoor wireless LAN planning problem , 2008, Comput. Oper. Res..

[2]  Pierre Hansen,et al.  Variable Neighborhood Search : Methods and Applications , 2008 .

[3]  Hakim Mabed,et al.  Interference Management in IEEE 802.11 Frequency Assignment , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[4]  X. Jia,et al.  An indoor wireless positioning system based on wireless local area network infrastructure , 2003 .

[5]  Yubin Xu,et al.  ANFIS-Based Wireless LAN Indoor Positioning Algorithm , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[6]  Alexandre Caminada,et al.  Wireless LAN planning: a didactical model to optimise the cost and effective payback , 2007 .

[7]  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).

[8]  Pierre Hansen,et al.  Variable neighbourhood search: methods and applications , 2010, Ann. Oper. Res..

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

[10]  Luigi Fratta,et al.  Algorithms for WLAN Coverage Planning , 2004, EuroNGI Workshop.

[11]  Di Yuan,et al.  Mathematical Optimization Models for WLAN Planning , 2010, Graphs and Algorithms in Communication Networks.

[12]  Alexandre Caminada,et al.  Efficient design of indoor positioning systems based on optimization model , 2010, 2010 IFIP Wireless Days.

[13]  M. Cesana,et al.  WLAN coverage planning: optimization models and algorithms , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[14]  A. Caminada,et al.  WLAN-based Indoor Positioning System: experimental results for stationary and tracking MS , 2006, 2006 International Conference on Communication Technology.

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

[16]  Shih-Hau Fang,et al.  A Novel Algorithm for Multipath Fingerprinting in Indoor WLAN Environments , 2008, IEEE Transactions on Wireless Communications.

[17]  Alexandre Caminada,et al.  Toward environment indicators to evaluate WLAN-based indoor positioning system , 2009, 2009 IEEE/ACS International Conference on Computer Systems and Applications.