A Software-Defined Radio Tool for Experimenting with RSS Measurements in IEEE 802.15.4: Implementation and Applications

This paper presents an open source Software-Defined Radio tool compliant with IEEE 802.15.4, which incorporates features for the collection and processing of Received Signal Strength (RSS) measurements from incoming packets. The implementation includes RSS Indicator (RSSI) feature, data handling and application code for channel estimation, ranging and localization. The tool can be used for experimenting with RSSI measurements from over-the-air IEEE 802.15.4 packets. To illustrate the tool usage, we present experimental results on packets sniffed from commercial ZigBee nodes. Moreover, we highlight some issues in the RSSI calculation, showing how different aspects of the RSS computation can be investigated at the finest granularity, hence allowing researchers and practitioners to experiment down to the PHY layer.

[1]  William H. Press,et al.  Numerical Recipes 3rd Edition: The Art of Scientific Computing , 2007 .

[2]  Angelo Coluccia,et al.  On ML estimation for automatic RSS-based indoor localization , 2010, IEEE 5th International Symposium on Wireless Pervasive Computing 2010.

[3]  Shinsuke Hara,et al.  A Joint Estimation of Target Location and Channel Model Parameters in an IEEE 802.15.4-based Wireless Sensor Network , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[4]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Francisco J. Coslado,et al.  Dynamic calibration and zero configuration positioning system for WSN , 2008, MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference.

[6]  Thomas Schmid NESL.  GNU Radio 802 . 15 . 4 En-and Decoding , 2006 .

[7]  Danilo De Donno,et al.  Challenge: towards distributed RFID sensing with software-defined radio , 2010, MobiCom.

[8]  Stefano Chessa,et al.  A Novel Approach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[9]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[10]  Ingrid Moerman,et al.  Automated linear regression tools improve RSSI WSN localization in multipath indoor environment , 2011, EURASIP J. Wirel. Commun. Netw..

[11]  Angelo Coluccia,et al.  Reduced-Bias ML-Based Estimators with Low Complexity for Self-Calibrating RSS Ranging , 2013, IEEE Transactions on Wireless Communications.

[12]  Haiyun Luo,et al.  Zero-Configuration, Robust Indoor Localization: Theory and Experimentation , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[13]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[14]  Sinan Gezici,et al.  A Survey on Wireless Position Estimation , 2008, Wirel. Pers. Commun..

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

[16]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[17]  S. Hara,et al.  Propagation characteristics of IEEE 802.15.4 radio signal and their application for location estimation , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[18]  Fernando Seco,et al.  A survey of mathematical methods for indoor localization , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.

[19]  Fredrik Gustafsson,et al.  Mobile Positioning Using Wireless Networks , 2005 .

[20]  Fabio Ricciato,et al.  Maximum Likelihood trajectory estimation of a mobile node from RSS measurements , 2012, 2012 9th Annual Conference on Wireless On-Demand Network Systems and Services (WONS).