Harun, A.

Jaafar, M.

Kamarudin, L.

Ndzi, David

Ramli, M.

Shakaff, A.

Zakaria, A.

English

Portsmouth University Research Portal (Pure)

Australian Journal of Basic and Applied Sciences, 7(5): 55-60, 2013 
ISSN 1991-8178 
 
Corresponding Author: A. Harun, School of Mechatronic Engineering, University Malaysia Perlis (UNIMAP), Perlis, 
Malaysia 
55 
Antenna Positioning Impact on Wireless Sensor Networks Deployment in Agriculture 
 
1A. Harun, 1M.F. Ramli, 2D.L. Ndzi, 3L.M. Kamarudin, 1A.Y.M. Shakaff, 4M.N. Jaafar, 1A. Zakaria 
 
1School of Mechatronic Engineering, University Malaysia Perlis (UNIMAP), Perlis, Malaysia 
2School of Engineering, University of Portsmouth, Portsmouth, UK 
3School of Computer and Communication Engineering, University Malaysia Perlis (UNIMAP), Perlis, 
Malaysia 
4School of Bioprocess Engineering, University Malaysia Perlis (UNIMAP), Perlis, Malaysia 
 
Abstract: quality data and network continuity are two important considerations in determining the 
success of wireless sensor network (WSN) motes deployment in agriculture. Nevertheless, these two 
factors are closely related to the behavior of antenna position and orientation during deployment which 
has often been ignored. Although extensive research has been done on antenna heights and 
characteristics, very few looked into potential antenna misplaced during deployment. This paper 
presents a study on effect of antenna heights and orientation to wireless sensor network signal power 
variation. The results showed that although the antenna height affects the signal strength significantly, 
as long as the transmitter and receiver are higher than the far field distance of the antenna, the power 
loss is insignificant. On the other hand, misplaced antenna radiating towards receiver in the absence of 
front lobe, may cause critical data loss and network continuity. The study also showed that Log-
distance model is a better fit to signal loss profile in agricultural field compared to Free Space Loss 
model. 
 
Key words: WSN, RSSI, received signal strength indicator, antenna radiation, orientation 
 
INTRODUCTION 
 
Wireless Sensor Network (WSN) devices are now becoming commonplace in various applications requiring 
instantaneous or delayed data acquisition and decision making. One of the leading applications utilizing these 
devices is modern precision farming. In this unique application, WSN devices or nodes are normally used for 
crop health and yield monitoring. As their usage becomes more widespread, especially in time critical 
applications, so too is the need to ensure that they are reliable and can meet quality of service requirements.  To 
provide reliable and adequate network coverage whilst minimizing cost, detailed knowledge of wireless signal 
propagation within the specific environment is required (Harun et al., 2012). In addition to that, another important 
factor to consider in such deployment is the network continuity which largely dependent upon the position of the 
nodes in the deployment map.   
A wireless sensor network consists of numerous nodes equipped with sensor(s) and a radio transmission unit 
for wireless communication. This radio unit is normally equipped with quality indicators such as received signal 
strength indicator (RSSI) and link quality indicator (LQI).  RSSI is calculated within the radio unit and provides a 
useful indication of the wireless link quality.  LQI is based on signal-to-noise ratio within the frequency band and 
provides average correlation value for each received packet (Lee et al., 2010). Many researchers have discussed 
the important of link quality to determine correct and accurate data acquisition in wireless sensor networks (Lee 
et al., 2010),(Thelen et al., 2005),(Liu, 2006), (Liu et al., 2009) however only some discussed antenna positioning 
as important factor in correlating the link quality between transmitting nodes to the sink or gateway (Gay-
Fernández et al., n.d.),(Wang et al., 2012) to the signal quality and network continuity.  
For specific WSN deployment, such as in modern precision farming, although link quality between the nodes 
is very important to ensure data continuity, the position of the nodes i.e. the antenna are more critical since 
dropped or misplaced antenna nodes are certain to sever the linkage from the farm to gateway and database. In 
order to fully understand the effect of various antennas positioning in the farm area to the link quality, a specific 
signal propagation profiling is required as a reference for further antenna positioning comprehension. This paper 
reports on the signal propagation study for three antenna heights and two antenna orientations in a typical tropical 
climate precision farm. 
 
Background And Literature Review: 
Application of WSN in agriculture is envisaged to be one of the major uses that will have a profound impact 
on world communities. Until recently most studies in WSN have focused on the devices (Liu et al., 2007), 
protocols (Wu and Dai, 2005),(Heinzelman et al., 2000) and the network architecture (Holderness and Sheehan, 
1988). Little interest has been paid to the signal propagation.  Studies using simulation platforms often use simple 
Aust. J. Basic & Appl. Sci., 7(5): 55-60, 2013 
56 
channel models such as the free space loss (FSL) given by (1), or the two ray channel model (Meng et al., 2010) 
which we will not be dealing with in this paper. 
 
         (1) 
 
The parameter f is the frequency in MHz, d is the distance between the isotropic transmitting and receiving 
antennas in meters. 
Gay-Fernandez et al. (Gay-Fernandez et al., 2010) have shown that WSN channel can be modeled using a 
log-distance model. The log-distance model is described by (2).  
 
                        (2) 
 
Where   is the received power (in dBm) at a distance d (in meters) from the transmitter,  is the signal 
strength at 1 m antenna separation, α is the path loss exponent and Xσ represents a Gaussian random variable 
with zero mean and standard deviation of . 
The study reported in this paper uses RSSI value for path loss comparison measurement purposes. The 
maximum range is defined as the transmitting and receiving mote separation beyond which the motes can no 
longer establish the connection. However, there are also conditions when the transmission is being stopped as the 
experiment ran out of field. 
 
Equipments And Measurements: 
This study has been performed using MEMSIC’s IRIS XM2110 mote equipped with Atmel RF230 radio 
chip.  The mote transmits in the 2.4 GHz – 2.5 GHz ISM band and of ZIGBEE/IEEE802.15.4 compliant 
(www.memsic.com). The motes are connected to external antenna as depicted in Fig. 1 (a) and (b). 
 
  
(a) 
 
(b) 
 
Fig. 1: (a) MEMSIC wireless sensor mote which has an integrated temperature and humidity sensor (b)  
            measured antenna radiation pattern 
 
Antenna height and orientation signal measurements experimentation were conducted in a large open grass 
field similar to the one shown in Fig. 1. For this measurement, the objective was to compare the signal 
propagation strength at various antenna heights and orientations. 
  
 
 
Fig. 2: Open field for measurement 
 
Aust. J. Basic & Appl. Sci., 7(5): 55-60, 2013 
57 
During the study, the receiving nodes remained at a fixed position whilst the transmitting nodes were placed 
at specific distances from the receiver in a straight line. The experiments were carried out with antenna heights of 
0.5 m, 1 m and 2.3 m.  As for the antenna orientation measurement, the height of the antenna was set at 1 m. This 
measurement looked at transmitting antenna in pointing orientation (towards the receiving antenna) and 
perpendicular orientation (against the receiving antenna). The diagram illustrating the measurement setup is as in 
Fig. 3.  
 
 
(a) 
 
(b) 
Fig. 3: Diagram illustrating the measurement (a) three antenna heights measurements and (b) antenna 
orientation at pointing and perpendicular to Tx antenna RSSI values were collected during each of the 
transmissions and analyzed.  
 
RESULTS AND DISCUSSIONS 
 
This section discusses the results obtained both from antenna heights measurement and transmitter antenna 
orientations. The results are presented based on the average RSSI values at various transmitting to receiving mote 
distances.  
Fig. 4(a) compares the performances of the three antenna heights 0.5 m, 1.0 m and 2.3 m. All the three 
signals showed almost similar variation throughout the length of the field as a result of uniform scattering from 
the grass field producing multipath signal components which arrived at the receiver in their own amplitudes and 
delays.  Signal profile for 1 m antenna height seemed to exhibit higher power compared to 0.5 m antenna height 
signal where at certain distances measured about 8 dB margins although at some other distances 0.5 m signal 
recorded higher signal strength than that of 1 m signal. On the other hand, 2.3 m signal did not seem to obey 
logarithmic pattern which could be attributed to interference from local access point or other foreign signals 
operating in the same frequency band. Nevertheless, signal profile at 2.3 m recorded on average the highest signal 
strength in comparison to the other two signals. As we ran out of the field length, all the signals did not go to the 
noise level which showed quite a long range of operation for this mote in line of sight (LOS) condition.    
 
 
(a) 
 
(b) 
Fig. 4: (a) RSSI versus range for all three antenna heights and (b) RSSI versus distance for antenna pointing and 
perpendicular towards Rx 
0 10 20 30 40 50 60 70 80
-90
-85
-80
-75
-70
-65
-60
-55
-50
-45
-40
Distance (m)
Po
we
r (
dB
m
)
RSSI vs Frequency for Various Antenna Positions
 
 
0.5m
1.0m
2.3m
0 10 20 30 40 50 60 70 80
-95
-90
-85
-80
-75
-70
-65
-60
-55
-50
-45
Distance (m)
Po
we
r (
dB
m
)
RSSI vs Frequency for Various Antenna Positions
 
 
Tx pointing
Tx perpendicular
1.0m antenna height
Aust. J. Basic & Appl. Sci., 7(5): 55-60, 2013 
58 
Fig. 4(b) showed the signal strength for transmitter antenna pointing and perpendicular towards receiver over 
various distances at 1.0 m antenna height. The figure also shows the reference signal which is the 1.0 m antenna 
height (normal straight up antenna orientation) for comparison. Signal strength variation seemed to be 
insignificant up to 50 m distance for both antenna orientations. Nevertheless, after 50 m onwards, intense 
fluctuation in signal strength observed for both and ground reflection over various Fresnel zones in addition to 
scattering by grass surface attributed to this variation. Reflection happened in odd number Fresnel zones 
supplemented direct signal path and produced signal spike while reflection in even number Fresnel zone 
cancelled some of the direct path components and caused the abrupt signal drop.  
It is apparent that the transmitter antenna in pointing orientation showed reduced signal strength where at 
some instances having very poor signals to noise ratio. The margin between these signals to reference signal is 
almost 20 dB at the highest and 4 dB at the lowest. Most signal components are only radiated by side lobe for this 
orientation accounting for the sharp reduction in the signal strength as the antenna is Omni-directional radiation in 
design. Transmitter antenna in perpendicular orientation on the other hand showed insignificant signal power 
drop in comparison to the reference signal where at most instances are about 10 dB the highest and 3 dB the 
lowest. Most of the signal components are originated from front lobe radiation and absence of side lobe radiation 
accounted for the slight drop in the signal strength. An important conclusion from this study is the radiation 
pattern of the antenna played significant impact to the misplaced antenna in any deployment application. 
To model signal power variation with distance, the log-distance model was fitted to the data. Fig. 5(a) shows 
the fitting to the mote RSSI data for measurements at 0.5 m antenna height. The equation that describes the fitted 
model is given in the figure with a root mean square error of 1.68 dBm.  Fig. 5(b) also shows the fitting to the 
data for 1.0 m antenna height. Because of large variations in the signal power with distance, the root mean square 
is slightly higher. 
 
 
(a) 
 
(b) 
Fig. 5: (a) IRIS mote antenna height at 0.5 m and Log-distance model fitting and (b) IRIS data at 1 m antenna 
height fitted with Log-distance model 
 
Compared to results from 1 m antenna height measurements, the signal decay with distance exhibited 
smoother variations at 0.5 m. This resulted in better fittings to the model as shown in Fig. 5(a). 
 
 
(a) 
 
(b) 
Fig. 6: (a) Tx antenna pointing to Rx fitted with Log-distance model and (b) Tx antenna perpendicular to Rx  
            fitted with Log-distance model 
0 10 20 30 40 50 60 70
-80
-75
-70
-65
-60
-55
-50
-45
-40
Distance (m)
Po
we
r (
dB
m
)
 
 
Data
Pr=10*-1.9814*log10(d)-41.7611: RMSE=1.6783
0 10 20 30 40 50 60 70 80
-90
-85
-80
-75
-70
-65
-60
-55
-50
-45
Distance (m)
Po
we
r (
dB
m
)
 
 
Data
Pr=10*-1.9306*log10(d)-43.4752: RMSE=3.8801
0 10 20 30 40 50 60 70 80
-95
-90
-85
-80
-75
-70
-65
-60
-55
-50
Distance (m)
Po
we
r (
dB
m
)
 
 
Data
Pr=10*0.36342*log10(d)-90.4528: RMSE=3.4302
0 10 20 30 40 50 60 70 80
-95
-90
-85
-80
-75
-70
-65
-60
-55
-50
Distance (m)
Po
we
r (
dB
m
)
 
 
Data
Pr=10*-1.6225*log10(d)-52.7703: RMSE=3.9616
Aust. J. Basic & Appl. Sci., 7(5): 55-60, 2013 
59 
Fig. 6(a) and Fig. 6(b) show the signal power decay with distance for measurements at antenna orientation 
(pointing and perpendicular respectively) at 1 m antenna heights.  The different in radiating pattern of the 
antennas showed significant signal variations from one antenna orientation to another. Nevertheless, although 
signal for pointing antenna showed significant reduction in strength, the variation is less compared to signal for 
perpendicular antenna as indicated by the RMSE for both of them. This is mainly attributed to the scattering 
produced by the grass field where the experiment is conducted affecting the higher radiation power which is the 
front lobe in the perpendicular antenna orientation. As the propagation of the signal in pointing orientation mainly 
contributed by the side lobe of the radiated antenna, less effect observed due to the scattering. In addition, the rate 
of signal power decay with distance is much higher with value of α (from Log-distance model) that are greater 
than 1.5 in perpendicular antenna orientation compared to pointing antenna orientation where the value is less 
than 0.5. 
 For comparison, the data were also fitted with free space loss model and result is tabulated in table 1. The 
result showed that FSL actually under estimated the scattering by grass field for a short distance path loss 
modeling. Log-distance on the other hand, took into consideration the effect in short distance path loss thus fit 
better to the graph. 
 
Table 1: Result for log-distance and free space loss modeling 
Antenna position Log-distance model FSL model RMSE 
α RMSE 
0.5m height 1.9814 1.6787 5.2397 
1.0m height 1.9306 3.8801 7.1661 
Antenna Pointing 0.3634 3.4302 14.054 
Antenna Perpendicular 1.6225 3.9616 7.7390 
 
Conclusions: 
This paper presented a study on antenna positioning and orientation in open grass field for references to 
WSN motes deployment in tropical agricultural farm. This would be very important in assessing the impact of 
misplaced antenna in WSN motes deployment as this would mean losing critical crop data or not. The results 
showed that antenna at 1 m height suffer less signal power loss over distance compared to antenna at 0.5 m 
height. Nevertheless differences in the power levels were not significant which measured about 8 dB margin 
between them thus both antenna heights could be utilized in the deployment, whichever fits into the requirement.  
On the other hand, antenna orientation contributed significantly to the link quality between transmitter and 
receiver for WSN motes. Transmitter antenna at pointing direction towards receiver suffered significant power 
loss while transmitter antenna at perpendicular to receiver showed slight drops in signal strength. The absence of 
front lobe radiation towards receiver in pointing antenna brought the power loss to almost at the noise floor level.  
Analysis showed that the Log-distance model is the best fit to all of the measured data when compared to 
FSL model. It is also observed that signal power decay over distance for antenna in perpendicular to receiver is 
higher than that pointing to receiver which could be explained by the stronger front lobe radiation compared to 
side lobe. In short, in order to ensure high quality data transmission and continuity in WSN deployment, antenna 
orientations have to be checked and monitored to ensure optimal positioning. 
  
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The role of majority shareholders in publicly held corporations: An exploratory analysis.

Antenna positioning impact on wireless sensor networks deployment in agriculture

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Antenna positioning impact on wireless sensor networks deployment in agriculture

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