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Localization of a Single Sensor with Respect to a Single Beacon using Received Signal Strength (RSS) in Terrestrial Environment

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Anisur Rahman, Shafayet Khan, Khalid Bin Salahuddin

Anisur Rahman, Shafayet Khan and Khalid Bin Salahuddin. Localization of a Single Sensor with Respect to a Single Beacon using Received Signal Strength (RSS) in Terrestrial Environment. International Journal of Computer Applications 181(38):45-52, January 2019. BibTeX

	author = {Anisur Rahman and Shafayet Khan and Khalid Bin Salahuddin},
	title = {Localization of a Single Sensor with Respect to a Single Beacon using Received Signal Strength (RSS) in Terrestrial Environment},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2019},
	volume = {181},
	number = {38},
	month = {Jan},
	year = {2019},
	issn = {0975-8887},
	pages = {45-52},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2019918389},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This paper apprised the issue of finding the location of a single sensor node with a single beacon in a terrestrial wireless sensor network (WSN). Generally, the localization of a single sensor node in a terrestrial sensor network can be solved using multilateration technique with respect to three or more known beacon nodes. However, there is an area of concern, when the localization of a single sensor node (i.e. mobile station, cell phone) is to be measured with respect to only one known beacon node i.e. base transceiver station (BTS). Such a challenge is aimed to be solved with the help of received signal strength (RSS) survey data for a particular location within the desired environment. A simulated terrain and a model has been created based on RSS Survey data that defines the contours of radio frequency (RF) coverage in a particular test facility under a single beacon node. Simulation results show that our proposed model gives a solution which converges to determine the location of a single sensor node with respect to a single beacon node.


  1. Qualcomm Inc., \The 1000x data challenge," [Online] Available:, 2014
  2. Fredrik Gustafsson and Fredrik Gunnarsson, “Mobile Positioning using wireless Networks: Possibility and fundamental limitation based on available wireless networks measurements”, proceedings of the IEEE vol. 22 issue 4, July 2005, PP 41-53.
  3. Huiyu Liu, Yunzhou Zhang, Xiaolin Su, Xintong Li, and Ning Xu, “Mobile Localization Based on Received Signal Strength and Pearson’s Correlation Coefficient”, Hindawi Publishing Corporation, International Journal of Distributed Sensor Networks, Volume 2015, Article ID 157046, 10 pages.
  4. C. –Y. Chong, S. Kumar, “Sensor Networks: Evolution, Opportunities, and Challenges”, proceedings of the IEEE 91 (8) (2003) 1247-1256.
  5. M. Anisetti, C. A. Ardagna, V. Bellandi, E. Damiani, and S. Reale, “Map-based location and tracking in multipath outdoor mobile networks,” IEEE Transactions on Wireless Communications, vol. 10, no. 3, pp. 814–824, 2011.
  6. K. Yu, I. Sharp, and Y. J. Guo, Ground-Based Wireless Positioning, John Wiley & Sons, 2009.
  7. J. Shen, A. F. Molisch, and J. Salmi, “Accurate passive location estimation using TOA measurements,” IEEE Transactions on Wireless Communications, vol. 11, no. 6, pp. 2182–2192, 2012.
  8. J. Saloranta and G. Abreu, “Solving the fast moving vehicle localization problem via TDOA algorithms,” in Proceedings of the 8th Workshop on Positioning Navigation and Communication (WPNC ’11), pp. 127–130, IEEE, Dresden, Germany, April 2011.
  9. M. Dakkak, A. Nakib, B. Daachi, P. Siarry, and J. Lemoine, “Indoor localization method based on RTT and AOA using coordinates clustering,” Computer Networks, vol. 55, no. 8, pp. 1794–1803, 2011
  10. C. Gentile, N. Alsindi, R. Raulefs et al., “Multipath and NLOS mitigation algorithms,” in Geolocation Techniques, pp. 59–97, Springer, NewYork, NY,USA, 2013.
  11. M. Ibrahim and M. Youssef, “CellSense: an accurate energyefficient GSM positioning system,” IEEE Transactions on Vehicular Technology, vol. 61, no. 1, pp. 286–296, 2012.
  12. M. Bshara, U. Orguner, F. Gustafsson, and L. Van Biesen, “Fingerprinting localization in wireless networks based on received signal- strength measurements: a case study on WiMAX networks,” IEEE Transactions on Vehicular Technology, vol. 59, no. 1, pp. 283–294, 2010.
  13. P. Enge and P. Misra, “Special issue on GPS: The global positioning system,” Proc. IEEE, vol. 87, no. 1, pp. 3–15, Jan. 1999.
  14. P. Bahl, V. Padmanabhan, RADAR: an in-building RF-based user location and tracking system, in IEEE INFOCOM, vol. 2, 2000, pp. 775-784.
  15. P. Prasithsangaree, P. Krishnamurthy, P. Chrysanthis, On indoor position location with wireless LANs, in The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, vol. 2, 2002, pp. 720-724.
  16. P. Krishnan, A. Krishnakumar, W.-H. Ju, C. Mallows, S. Gamt, A system for LEASE: location estimation assisted by stationary emitters for indoor RF wireless networks, in: IEEE INFOCOM, vol. 2, 2004, pp. 1001-1011.
  17. Teemu Roos , Petri Myllymäki , Henry Tirri, A Statistical Modeling Approach to Location Estimation, IEEE Transactions on Mobile Computing, v.1 n.1, p.59-69, January 2002 [doi>10.1109/TMC.2002.1011059]
  18. S. Ray, W. Lai, I. Paschalidis, Deployment optimization of sensornet-based stochastic location-detection systems, in: IEEE INFOCOM 2005, vol. 4, 2005, pp. 2279-2289.
  19. E. Elnahrawy, X. Li, R. Martin, The limits of localization using signal strength: a comparative study, in: First Annual IEEE Conference on Sensor and Ad-hoc Communications and Networks, 2004, pp. 406-414.
  20. Http://
  21. Browning, R. C., Baker, E. A., Herron, J. A. and Kram, R. (2006). "Effects of obesity and sex on the energetic cost and preferred speed of walking". Journal of Applied Physiology. 100 (2): 390–398.
  22. Betty J. Mohler, William B. Thompson, Sarah H. Creem-Regehr, Herbert L. Pick Jr, William H. Warren Jr, (2007). "Visual flow influences gait transition speed and preferred walking speed". Experimental Brain Research. 181 (2): 221–228.
  23. Levine, R. V. & Norenzayan, A. (1999). "The Pace of Life in 31 Countries". Journal of Cross-Cultural Psychology. 30 (2): 178–205.


Wireless Sensor Networks, Received Signal Strength, Localization, Single Beacon, Heat map