Peer-to-Peer Networking and Applications

, Volume 9, Issue 6, pp 991–1004 | Cite as

Adaptive RSSI-based localization scheme for wireless sensor networks

  • Wail MardiniEmail author
  • Yaser Khamayseh
  • Abdalrhman Abdalkareem Almodawar
  • Ehab Elmallah


Range of applications for Wireless Sensor Networks (WSNs) is increasing rapidly. One class of such applications is Energy-Aware Wireless Positioning Systems for situation awareness. Localization deals with determining a target node’s position in WSN by analyzing signals exchanged between nodes. Received Signal Strength Indicator (RSSI) represents the ratio between received signal power and a reference power, and is typically used to estimate distances between nodes. RSSI distance estimations are affected by many factors. This paper aims to enhance the accuracy of RSSI-based localization techniques in ZigBee Networks through studying the communication channel status between two nodes. As the network nodes are exposed to high noise levels, position estimation accuracy deteriorates. A novel adaptive localization scheme is proposed; Two-State Markov model with moving average is employed to detect unpredictable RSSI readings that may reflect badly on the estimation. The proposed scheme achieves better estimation accuracy, for example, the estimation error was reduced from 11.7 m to just 3 m using the proposed scheme.


Wireless sensor networks Localization Received signal strength indicator ZigBee networks Markov model Moving average Distance estimation 


Compliance with ethical standards

The authors of this paper would like to certify that this manuscript has not been submitted to more than one journal for simultaneous consideration. Moreover, this manuscript has not been published previously (partly or in full) and this study was not split up into several parts to increase the quantity of submissions and was not submitted to various journals or to one journal over time.

Also, we certify that no data have been fabricated or manipulated (including images) to support our conclusions, and no data, text, or theories by others are presented as if they were ours.

Conflict of interest

The authors declare that they have no conflict of interest of any kind in this paper.


  1. 1.
    Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422Google Scholar
  2. 2.
    Gerla M, Carla-Fabiana C, Kenichi M, Eytan M, Redi J (2004) Mobile ad hoc wireless networks. Commun Networks, J 6(4):291–294Google Scholar
  3. 3.
    Jeličić V, Bilas V (2010) “Reducing power consumption of image transmission over IEEE 802.15.4/ZigBee sensor network,” Instrumentation and Measurement Technology Conference (I2MTC), IEEE, vol., no., pp.1211,1215, 3–6 May 2010Google Scholar
  4. 4.
    Roman R, Lopez J, Gritzalis S (2008) Situation awareness mechanisms for wireless sensor networks. Commun Mag, IEEE 46(4):102–107Google Scholar
  5. 5.
    Niculescu D, B Nath (2003) “Ad hoc positioning system (APS) using AOA.” INFOCOM 2003. Twenty Second Annual Joint Conferences of the IEEE Computer and Communications. IEEE Societies. Vol. 3. IEEEGoogle Scholar
  6. 6.
    Rong P, ML Sichitiu (2006) “Angle of arrival localization for wireless sensor networks.” Sensor and Ad Hoc Communications and Networks, 2006. SECON’06. 2006 3rd Annual IEEE Communications Society on. Vol. 1. IEEEGoogle Scholar
  7. 7.
    Gezici S (2008) A survey on wireless position estimation. Wirel Pers Commun 44(3):263–282Google Scholar
  8. 8.
    Hightower J, Borriello G (2001) A Survey and Taxonomy of Location Systems for Ubiquitous Computing.” Technical Report UW-CSE 01-08-03. University of Washington, Computer Science and Engineering, SeattleGoogle Scholar
  9. 9.
    Karl H, A Willig (2007) “Protocols and architectures for wireless sensor networks”. Wiley- InterscienceGoogle Scholar
  10. 10.
    Zvanovec S, Pechac P, Klepal M (2003) Wireless LAN networks design: site survey or propagation modeling? Radioengineering 12(4):42–49Google Scholar
  11. 11.
    Kumar P, L Reddy, S Varma (2009) “Distance measurement and error estimation scheme for RSSI based localization in Wireless Sensor Networks.” Wireless Communication and Sensor Networks (WCSN), 2009 Fifth IEEE Conference on. IEEEGoogle Scholar
  12. 12.
    Awad A, T Frunzke, F Dressler (2007) “Adaptive distance estimation and localization in WSN using RSSI measures.” Digital System Design Architectures, Methods, and Tools, 2007. DSD 2007. 10th Euromicro Conference on. IEEEGoogle Scholar
  13. 13.
    Ramadurai V, ML Sichitiu (2003) “Localization in wireless sensor networks: Aprobabilistic approach.” Proc. of the 2003 International Conference on Wireless Networks (ICWN 2003)Google Scholar
  14. 14.
    Blumenthal J, et al (2007) “Weighted centroid localization in zigbee-based sensor networks.” Intelligent Signal Processing. WISP 2007. IEEE International Symposium on. IEEEGoogle Scholar
  15. 15.
    Subaashini K, G Dhivya, R. Pitchiah (2013) “ZigBee RF signal strength for indoor location sensing-Experiments and results.” In Advanced Communication Technology (ICACT), 2013 15th International Conference on, pp. 50–57. IEEEGoogle Scholar
  16. 16.
    Adewumi OG, K Djouani, AM Kurien (2013) “RSSI based indoor and outdoor distance estimation for localization in WSN.” In Industrial Technology (ICIT), 2013 I.E. International Conference on, pp. 1534–1539. IEEEGoogle Scholar
  17. 17.
    Palazon JA, J Gozalvez, G Prieto (2012) “Experimental RSSI-based localization system using wireless sensor networks.” In Emerging Technologies & Factory Automation (ETFA), 2012 I.E. 17th Conference on, pp. 1–4. IEEEGoogle Scholar
  18. 18.
    Rasool I, Salman N, Kemp AH (2012) “RSSI-based positioning in unknown path-loss model for WSN,” Sensor Signal Processing for Defence (SSPD 2012), vol., no., pp.1,5, 25–27 SeptGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Wail Mardini
    • 1
    Email author
  • Yaser Khamayseh
    • 1
  • Abdalrhman Abdalkareem Almodawar
    • 1
  • Ehab Elmallah
    • 2
  1. 1.Department of Computer ScienceJordan University of Science and TechnologyIrbidJordan
  2. 2.Department of Computer ScienceUniversity of AlbertaEdmontonCanada

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