Next Article in Journal
Evaluation of the Use of Class B LoRaWAN for the Coordination of Distributed Interface Protection Systems in Smart Grids
Next Article in Special Issue
Special Issue: Localization in Wireless Sensor Networks
Previous Article in Journal
Monitoring System of A Heat Pump Installation for Heating A Rural House Using Low-grade Heat from a Surface Watercourse
Previous Article in Special Issue
Performance Comparison of Closed-Form Least Squares Algorithms for Hyperbolic 3-D Positioning
Open AccessArticle

Characterization of the Log-Normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks

Finnish Geospatial Research Institute, National Land Survey, Geodeetinrinne 2, FI-02430 Masala, Finland
J. Sens. Actuator Netw. 2020, 9(1), 12; https://doi.org/10.3390/jsan9010012
Received: 28 October 2019 / Revised: 16 December 2019 / Accepted: 17 December 2019 / Published: 9 February 2020
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
Using the classical received signal strength (RSS)-distance log-normal model in wireless sensor network (WSN) applications poses a series of characteristic challenges derived from (a) the model’s structural limitations when it comes to explaining real observations, (b) the inherent hardware (HW) variability typically encountered in the low-cost nodes of WSNs, and (c) the inhomogeneity of the deployment environment. The main goal of this article is to better characterize how these factors impact the model parameters, an issue that has received little attention in the literature. For that matter, I qualitatively elaborate on their effects and interplay, and present the results of two quantitative empirical studies showing how much the parameters can vary depending on (a) the nodes used in the model identification and their position in the environment, and (b) the antenna directionality. I further show that the path loss exponent and the reference power can be highly correlated. In view of all this, I argue that real WSN deployments are better represented by random model parameters jointly accounting for HW and local environmental characteristics, rather than by deterministic independent ones. I further argue that taking this variability into account results in more realistic models and plausible results derived from their usage. The article contains example values of the mean and standard deviation of the model parameters, and of the correlation between the path loss exponent and the reference power. These can be used as a guideline in other studies. Given the sensitivity of localization algorithms to the proper model selection and identification demonstrated in the literature, the structural limitations of the log-normal model, the variability of its parameters and their interrelation are all relevant aspects that practitioners need to be aware of when devising optimal localization algorithms for real WSNs that rely on this popular model.
Keywords: received signal strength; wireless sensor networks; log-normal model; model identification; parameters’ variability; parameters’ correlation received signal strength; wireless sensor networks; log-normal model; model identification; parameters’ variability; parameters’ correlation
  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.3635317
    Description: Data and code related to the article "Characterization of the Log-normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks".
MDPI and ACS Style

Vallet García, J.M. Characterization of the Log-Normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks. J. Sens. Actuator Netw. 2020, 9, 12.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop