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Experimental Path-Loss Models for 2.4GHz In-field Wireless Sensor Network

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010  1008576.(doi:10.13031/2013.29656)
Authors:   Zhen Li, Ning Wang, Tiansheng Hong, Aaron Franzen
Keywords:   Wireless sensor network, path-loss, radio propagation, packet delivery rate, precision agriculture

Wireless sensor network (WSN) technology is a promising solution for large-scale, real-time, and continuous soil property data acquisition. However, the applications are still very limited due to a lack of understanding of in-field data transmission performance of the WSN. In this study, commercial 2.4 GHz wireless sensor modules (referred to as mote) and a hand-held spectrum analyzer were used to set up a test platform to evaluate radio propagation performance. Indexed packets transmitted from a module were captured by the spectrum analyzer to measure path-loss through received signal strength (RSS) and synchronously received by another module named base station to calculate packet delivery rate (PDR). Experiments were conducted in a wheat field of an experimental farm of Oklahoma State University. Canopy height, transmitter height, receiver height and transmitter-to-receiver distance (T-R distance) were considered as impact factors on radio propagation. Correlation analysis was used to evaluate the relationship between path-loss and PDR. The results indicated that, with the increase of the plant height, path-loss and PDR became more correlated with each other. A distance of 70 m was defined as a stable communication distance for the 2.4GHz in-field WSN applications. Four models were developed to predict the path-loss based on the log of T-R distance, transmitter and receiver heights under conditions of clear line-of-sight, and three different plant canopy heights, respectively. R2 of the models were 0.601, 0.599, 0.674 and 0.776. Their standard errors of the estimate were 3.761, 3.199 3.518, 2.889, respectively.

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