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Characterization of near-ground radio propagation channel for wireless sensor network with application in smart agriculture
* 1 , * 1 , * 2 , * 3
1  Dept. of Signal theory and Communications, University of Vigo, Vigo, Spain
2  TITM department, ENSATe, Abdelmalek Essaadi University, Tetouan, Morocco
3  Dept. of Electronic and Electrical Engineering, Public University of Navarre, Pamplona, Spain


In this contribution, we present a narrowband radio channel model for a scenario wherein the radio link operates under near ground conditions, occurring on a ZigBee wireless sensor networks applied to smart agriculture. The developed channel model considers the propagation or path loss caused by agriculture fields found in the propagation link when a near ground radio communication occurs. A near-ground network deployment can be useful to avoid tall antenna masts, or once crops grow.

Among the examined scenarios, we analyzed path loss caused when placing the sensor nodes in soil, short and tall grass fields.

In these scenarios, three different transmitting frequencies were used: 868MHz, 2.4GHz and 5.8GHz. We measured the received power when locating both transmitter and receiver antennas at two heights, 20cm and 40cm above ground. The path loss was then estimated as dependent of the radio link range.

In another scenario, measurements of the Signal Strength Indicator were obtained to analyze the communication quality between sensor nodes when placing them at the same two different antenna heights, only for the case of a short grass field. These nodes are working at 2.4GHz under ZigBee protocol.

A comparison between path loss and RSSI results for different antennas heights has been completed.

In the theoretical part, we performed a 3D Ray Launching simulation considering parameters of the ground materials, such as dielectric constant and conductivity.

The results have been employed in a context aware environment based on WSN deployment and integration, applied in a Smart Agriculture use case.

Keywords: Internet of Things, Wireless Sensor Networks, Smart Agriculture, near-ground, radio channel model.