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An Enhanced-Received Signal Strength Technique for Estimating Mobile Station Position in Wireless Sensor Networks

Adekunle A. Adeyelu, Onaji J. Onah, Iwuese J. Orban. Published in Signal Processing.

Communications on Applied Electronics
Year of Publication: 2020
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Adekunle A. Adeyelu, Onaji J. Onah, Iwuese J. Orban

Adekunle A Adeyelu, Onaji J Onah and Iwuese J Orban. An Enhanced-Received Signal Strength Technique for Estimating Mobile Station Position in Wireless Sensor Networks. Communications on Applied Electronics 7(33):32-38, July 2020. BibTeX

	author = {Adekunle A. Adeyelu and Onaji J. Onah and Iwuese J. Orban},
	title = {An Enhanced-Received Signal Strength Technique for Estimating Mobile Station Position in Wireless Sensor Networks},
	journal = {Communications on Applied Electronics},
	issue_date = {July 2020},
	volume = {7},
	number = {33},
	month = {Jul},
	year = {2020},
	issn = {2394-4714},
	pages = {32-38},
	numpages = {7},
	url = {},
	doi = {10.5120/cae2020652861},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Techniques to track an object from a remote location given certain information have been required for several hundred years. Existing outdoor techniques to locate a Mobile Station (MS) within a cellular network require optimization both in terms of accuracy and latency. In this paper, an enhanced Mobile Station Positioning (MSP) model for Wireless Sensor Networks was developed and its performance was appraised using accuracy and latency metrics in line with Received Signal Strength (RSS) procedure. This model used the strength of the signal received at four Base Stations (BS) positioned within the neighborhood of the MS to locate the MS. The mathematical model was formulated using circles equation and Taylor’s series expansion. The estimated position of the MS was calculated using Linear Least Square (LLS) solution iteratively. The result showed that the model located the MS within error distances of 199m for 67% and 339m for 95% of the time it was deployed. This result outperformed the RSS technique using three BS which located the MS within 256m at 67% deployment and 368m at 95% of the time the model was used. This gave approximately 15% improvement in accuracy. Simulation results also revealed that the latency experienced when the BSs were increased from three to four increased by 13.65% (0.024 seconds). It can be concluded that increasing the number of BSs from three to four gave a significant better accuracy in locating a MS within the BSs.


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Mobile Station, Base Station, Received Signal Strength.