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Performance Evaluation of ZigBee in Indoor and
Outdoor Environment
Mujahid Tabassum
Faculty of Computer Science & Information Technology
Universiti Malaysia Sarawak
Kuching, Malaysia
mujee1983@gmail.com
Dr. Kartinah Zen
Faculty of Computer Science & Information Technology
Universiti Malaysia Sarawak
Kuching, Malaysia
kartinah@fit.unimas.my
Abstract— Wireless Sensor Network (WSN) comprises of
many distributed independent tiny sensors that used to monitor
statistical data of specific environmental conditions such as
temperature, humidity, rain, pressure and many other. WSN use
unlicensed 2.4 GHz Industrial, Scientific and Medical (ISM)
radio frequency band for data transmission. WSN applications
are being used in many industries and civilian areas, for various
purposes such as environmental monitoring, habitat monitoring,
traffic monitoring, precision agriculture monitoring, security
monitoring, facility automation and traceability systems.
Deployment of WSN in an outdoor or indoor environment always
raised issue of signal loses and signal interference. In WSN, data
is transmitted over wireless medium which is easily affected by
external aspect such as walls, trees, heavy bushes, multiple signal
interference and others. Currently, IEEE standard 802.15.4
MAC protocol and ZigBee are the most famous protocols which
are been used in WSN industry. In this paper, we have
performed several experiments under various conditions such as
indoor, outdoor, co-existence of Bluetooth to observe the ZigBee
performance and interference effects. The experiments were
performed physically in real environments which showed ZigBee
signal degradation under various indoor and outdoor conditions.
Keywords—Wireless Sensor Network; Bluetooth; ZigBee;
Interference and Performance Evaluation.
I. INTRODUCTION
Wireless Sensor Network (WSN) is formed by deploying
number of sensor nodes within specific area range 100 to 1000
meter. These sensor nodes have sensing, processing,
communicating and transmitting capabilities. A WSN consists
of various types of sensors such as mechanical, thermal,
electrical, chemical and motion sensors [1]. These sensor nodes
are capable to monitor diverse environmental or object
conditions such as temperature, pressure, humidity, lighting,
soil moisture, speed, direction under various weather
conditions. Currently, many industries are using WSN to
minimize their labor cost and maximize their productivity
because WSN helps industry to achieve better standards and
results, with an automatic manner. Due to its flexibility and
adoptability, WSN has become very famous devices to assist
and facilitate people who live in rural areas. In many countries
such as Germany, Denmark and Malaysia the governments are
helping their people in rural area by introducing and
implementing wireless sensor networks in agriculture industry.
For example, wireless sensor networks help people by
monitoring their crop growth automatically. There are many
example of WSN applications which are been used for rural
enrichment such as Water waste monitoring, Landfill ground
well level monitoring and pump counter, Flare Stack
monitoring and Greenhouse monitoring systems [2].
Currently, wireless sensor network utilizes ZigBee and
IEEE 802.15.4 wireless standards for communication. IEEE
802.15.4 is a largest standard for low data rate Wireless
Personal Area Networks (WPANs) that defines the physical
layer (PHY) and media access control (MAC) layer. The PHY
layer defines frequency, power, modulation, and other wireless
conditions of the link in an Open Systems Interconnection
(OSI) model. The MAC layer defines the format of the data
handling [3].
ZigBee is an enhancement of IEEE 802.15.4 standards
which used layer 3 and layer 4 to define additional
communication features such as authentication, encryption,
data routing and forwarding capabilities. The low power
consumption limits the transmission range to only 10-100
meters with line of sight. WSN can be deployed in a large area
range with the help of mesh network topology in which data is
passed through many intermediate devices [3].
Mostly, personal area networks, short range and lower
power devices use 2.4 GHz band for their communication
which is an unlicensed spectrum. Therefore, many technologies
such as WiFi, Cordless Phones, Microwave ovens, Wireless
USB, Bluetooth and ZigBee run on 2.4 GHz band. As a result
the level of interference is quite heavy on 2.4 GHz band which
cause of signal drop or lose, multiple devices signal
interference and throughput drop.
In this paper we have performed few indoor experiments
with co-existence of multiple devices interference and outdoor
in heavy shrubby environment to observe the ZigBee
performance. This paper emphasis on practical work and
considered real time scenarios, whereas previously most of the
works have been done in simulation mode. The main purpose
of this research is to understand the environmental effects on
ZigBee performance including technological and
environmental interference and to observe its signal
degradation under various conditions. These issues need to be
considered when deploy a WSN into agriculture environment
for example; if WSN is deployed in a heavy shrubby
environment without considering the line of sight, it will have
performance degradation due to bad signal reception and signal
interference.
II. LITERATURE REVIEW
Mostly researchers used simulation tools such as Matlab,
Simulink, NS2, QualNet, Tossim to examine the performance
evaluation and signal interference of Zigbee and WSN. In our
research, we have performed the experiments using actual
hardware and real environmental conditions; this is to
understand the realistic signal degrading issues occur in indoor
and outdoor environments.
In the following paper [14], indoor experiments were
performed to observer the interference effects and throughput
of Zigbee and Bluetooth with co-existence of WLAN. The
result shows that IEEE 802.11g throughput dropped by 6% in
co-existence of Zigbee.
In another paper [15], the researcher performed simulation
based experiments to analyze the Zigbee performance with
interference of other objects. They evaluate Zigbee
performance with existence of Bluetooth and WLAN by using
Matlab & Simulink tools. The simulations were performed
based on different modulation schemes and frequency bands.
Zigbee standard operates at three bands such as 2.4 GHz band
with a maximum rate of 250kbps, 915 MHz band with a data
rate of 40 kbps, and 868 MHz band with a data rate of 20
kbps. The simulation results only show the Bit Error Rate
(BER) versus Signal to Noise Ratio (SNR) effects.
III. EXPERIMENTAL APPROACH
The main purpose of this research is to understand ZigBee
performance in indoor and outdoor environment that have line
of sight, interference and physical obstructions issues. This
research mainly emphasis on signal strength of ZigBee with
interference and without interference in shrubby and clean
environments.
A. Equipment’s Setup
We have used “2.4 GHz Cortex-M3|deRFusb-23E00” [4]
ZigBee dongle to perform ZigBee communication. This dongle
is used IEEE 802.15.4 ZigBee standard and able to act as a
gateway, network coordinator or a commissioning device.
Furthermore, it is able to function as a border router or a
coordinator in 6LoWPAN. This ZigBee dongle was connected
to a computer to be used as a wireless sensor network node that
is running on the IEEE 802.15.4 standard. This USB dongle
stick use to establish a virtual serial interface which provides
computer a direct access to the overall network [5]. The benefit
of using this stick is that it is applicable for any 802.15.4
applications at the 2.4GHz band. Besides, it also serves as a
gateway for both wired and wireless data transfer.
A spectrum analyzer “AirMagnet Spectrum Analyzer XT”
[6] was used to analyze the signal strength of communicating
devices. It provides in-depth radio frequency analysis in real
time WLAN situation. It is able to detect, locate and identify
radio frequency interferences individually, which includes non-
WLAN devices like ZigBee, Bluetooth, microwave oven and
others. By using this device, users are able to have a thorough
visibility into the physical layer of WLAN. This in turn,
enables users to identify the problems and interferences in the
environment which carries impact to the network performance
[6].
B. Indoor Setup
For indoor setup, we have chosen a computer lab and
library environment and experiments were performed with and
without Bluetooth interference. The first experiment was
performed in a computer lab which was occupied by
computers, wires, routers, switches and tables to create
interference and line of sight hurdle for ZigBee signals. The
reference point A and selected points B, C and D are shown in
Fig. 1 were marked and distance between each point were
calculated.
Fig. 1. Layout of Lab
Second experiment was performed in a library which has
great level of line of sight obstruction due to many students’
existence, movements and physical infrastructure such as
bookshelves, individual cubicles and rooms. The library also
has higher level of interference due to Bluetooth, WiFi and
mobile signals. The reference point A and selected points B,
C, D and E (Fig. 2) were marked and between distance were
calculated.
Fig. 2. Layout of Library
ZigBee set-up was done by having two ZigBee enabled
USB sticks connected to two individual laptops. Since ZigBee
is capable for self-discovery, it was able to detect the other
ZigBee dongle that was connected on the other laptop and
established a routing path between them. On each laptop, a
terminal application called Putty, were installed. Putty enables
the ZigBee dongles to communicate each another over a serial
wireless ZigBee link and visually display the sent and received
data on the transmitting and receiving ZigBee devices
respectively. The PC1 was placed on Reference point A and
the receiving ZigBee devices (PC2) was placed on various
points such as A, B, C and D (Fig. 1) to analysis the signal
degradation factor at those point due to distance and
interference. The receiving ZigBee device (PC2) was held by a
standing individual at a comfortable height of about 1.3m
above the ground. By holding the receiving device instead of
placing it on a flat surface, we were able to emulate a normal
daily life scenario.
To create signal interference, two smart phones were used
that have Bluetooth version 4.0 running on it. These phones
were placed around the reference points in order to generate
signal interference on 2.4 GHz band. To analyze and read the
Bluetooth signal strength an application called "Bluetooth
Signal App version 1.0", developed by nakaborigawa [7], was
used. Bluetooth Received Signal Strength Indication (RSSI)
values were taken at various points A, B, C and D. Both smart
phones were held at a comfortable height of about 1.3m by
standing individuals while obtaining the readings, with the
backs of the smartphones facing each other. Similar to the set-
up of ZigBee devices, the receiving ZigBee device and the
smartphone were held to emulate a normal scenario in
everyday life.
C. Outdoor Setup
For outdoor setup, we have chosen three environments
which are an empty car park with the length of 400meter (Fig.
3), a suburban village filled with knee length shrub 0.6m high
grasses and cluster of banana trees (Fig. 3) and a thick and
dense forest environment that was filled with dense tall trees,
wild plants and some thick bushes (Fig. 3). The experiments
were performed with and without Bluetooth interference.
Fig. 3. Outdoor Environments
We have also marked the reading points and calculated
distance with an increment of 10m from the reference point and
use AirMagnet Spectrum Analyzer XT to analyze any
interference in the 2.4GHz spectrum.
D. RSSI Value and Degradation Factor
All obtained signal strength reading was taken in the form
of Receive Signal Strength (RSSI). RSSI is a measurement of
power level which is available in the received radio
infrastructure [8]. For every ±3dBm change in the signal
strength value, there will be a difference in power of the signal
as the power is either halved or doubled [9].
The transmitting power of the ZigBee dongles was 3dBm
by Dresden Elektronik [5]. To standardize our results
comparison, we have formulated a degrading factor showing
in Eq. (1). This equation (1) was used to calculate degradation
factor of the received signal strength and it helps us to fine the
standard drop in the signal strength in relation to the transmit
power of Zigbee in the experiments.
(1)
The lower the value of degradation factor, the better the
signal strength and the higher the value of degradation factor
cause the worse in the signal strength. On relating each of the
results in such a way we were able to form a comprehensive
study.
IV. RESULTS AND FINDING
A. Indoor Environment – Experiment No. 1
Fig.5. Degradation Factor of ZigBee in Lab
For this experiment we noted few readings on reference
point A, and selected points B, C and D (Fig. 1). Based on the
average reading in Fig.5, the initial degradation factor at the
reference point A (Fig.1) was 22.89 that mean the signal
strength of ZigBee was high at point A (0m). However, it is
observed that there was a huge drop in the signal strength when
the receiving ZigBee device was moved to point B (Fig.1). The
sudden change in signal strength can be seen with a sharp rise
in the degradation value of 24.67. When the receiving ZigBee
device was placed at points C and D, the degradation value
decreased to a value 23.34 and 23.56 respectively, it is because
of line of sight and interference factors such as internal wiring,
reflection and absorption of signal by walls and WiFi
existence.
B. Indoor Environment – Experiment No. 2
Fig.6. Degradation Factor of ZigBee in Library
In this scenario the reference point A is in the middle and
selected points B, C and D are at same distance from reference
point A in different direction (Fig. 2). We can see from Fig. 6
that although the points of observation are equidistant from the
reference point A, there was a huge variation from one point to
another. At point B the degrading factor was 23 and point C it
was 22.67 which showed that the signal strength was quite low
at those points. However, at point D the degradation factor
reduce to 21 and at point E it was 20.45 that mean the signal
strength was better than the other points. During the
transmission of data from transmitting ZigBee device to the
receiving ZigBee device, it was observed that the signal
strength fluctuates a lot when students are walking by and the
line of sight between the devices is disturbed. However, due to
fast fluctuation and increase of signal strength, the average
signal strength reading was taken for each point.
C. Outdoor Environment – Experiment No. 1
Fig.7. Degradation Factor of ZigBee in Car Park
In this experiment the average degradation factor brought
some interesting results. We can observe from Fig. 7 that the
degradation factor was slowly increased till 24.34 from the
reference point A to the 30m distance, that mean signal
strength was dropping with increase of distance. However, the
degradation factor values started to drop down after 40 meter
distance that means signal strength was increasing even though
the distance is increasing. This was very interesting outcomes
and the result was consistent on multiple experimental
attempts.
Fig.8. Degradation Factor of ZigBee in Car Park
In this experiment, the Bluetooth and ZigBee were operated
at the same time to create a real interference on 2.4 GHz
spectrum. The Bluetooth signal was only detectable up to a
maximum distance of 80m. Therefore, the reading of signal
strength of ZigBee was only taken up to 80m. We can observe
the average reading in Fig. 8 which shows that the signal
strength of ZigBee dropped quicker than earlier scenario with
increase of distance. The degradation factor was noted to be 23
at 80 meter distance that is higher compare to earlier scenario.
D. Outdoor Experiment No. 2
Fig.9. Degradation Factor of ZigBee in Village with no obstacle
The Fig.9 shows that degradation factor of ZigBee increase
to 26.67 over 30 meter distance and keep increasing when
distance increases. In this scenario there was no big obstacle to
line of sight but there was knee length height of grass.
However, when this graph is being compared to the scenario
done in the empty car park, it is observed that there is an
increase in the value of degradation factor. This means that the
signal strength over the 30m of the village scenario decreases
by a great deal due to grass.
Fig.10. Degradation Factor of ZigBee in Village with Obstacle
In this experiment, we have added a cluster of banana tree
as a huge obstacle (Fig. 3) to break the line of sight between
ZigBee devices. We can observe from Fig. 10 that the
degradation factor increases slightly more than the one without
obstacle. When the receiving ZigBee device was placed right
behind the cluster of banana trees at 20m, the signal strength
was dropped drastically as degradation factor increased to
27.45. However, at 30m, the degradation factor readings as
compared to the one without obstacle were similar.
Fig.11. Degradation Factor of ZigBee in Village with no obstacle but
Interference
From the average reading in Fig. 11, it can be seen that the
degradation factor is slightly increased 23.67 to 26.34 from
reference point to 30m distance. This pattern is similar to the
average reading of the car park scenario (Fig. 8) which means
degradation factor increase with increase of distance.
Fig.12. Degradation Factor of ZigBee in Village with obstacle &
Interference
As the receiving ZigBee device was moved from no
obstruction to obstruction, there was a considerable increase in
the degradation factor. In comparison with the earlier scenario
without Bluetooth as interference, it can be seen that at point
20m, the average degradation factor was 24.34 and increases
higher to over 27 at 30m distance.
Fig.13. Degradation Factor of ZigBee in Jungle
In this scenario, ZigBee provides some interesting results as
well. We can observe the average reading of degradation factor
in Fig.13 which shows the degradation factor actually dropped
a great deal from 15m to 20m distance which indicates that at
20m the signal strength was even better than the reference
point. However, after the 20m distance it follow the same trend
of an increasing the degradation factor.
Fig.14. Degradation Factor of ZigBee in Jungle with Interference
The average reading of degradation factor in Fig. 14 shows
that ZigBee has a higher degradation factor as compared to the
previous scenario (Fig. 13). The degradation factor values were
consistent for the first 15m distance. However, after 15m
distance degradation value suddenly started to drop. This
pattern was consistent with all the previous outdoor
experiments results. The drop in both village and jungle
scenario start to occur at 20m distance, where as in car park the
drop was at 40m and another significant drop was over 60m
distance.
TABLE 1. Degradation Factor (dBm)
Distance Interference Without
Interference
Obstacle Obstacle &
Interference
Heavy Jungle
& Interference
0 23.12 23.34 20.34 23.67 23.89
10 - 23.12 23.23 24.12 24.67
20 23.89 24 27.45 24.89 20.45
30 - 24.34 26.78 27.67 -
40 23.45 24 - - -
50 - 22.12 - - -
60 22.12 22 - - -
80 23 21.45 - - -
90 - 21 - - -
100 - 21.45 - - -
120 - 21.67 - - -
We can observe from Table no.1 that in heavy shrubby
environment and with interference the ZigBee signal strength
drops faster over short distance compare to clean environment
and ZigBee signals are detectable until 30 meter distance as
compare to normal environment.
V. DISSCUSSION AND ANALYSIS
A. Indoor Environments
In an indoor setting there were lots of factors which effects
on wireless signal quality. Mostly cause of line of sight and
physical infrastructure such as internal wirings, reflection and
absorption by walls, physical objects, WiFi and other devices
signals. By considering all these factors, we can conclude that
all these factors are the obstacle to ZigBee wireless signals in
an indoor environment.
In the presence of WiFi, Bluetooth and human bodies, the
performance of ZigBee was greatly affected in a library.
Whenever students are passed by and it blocked the line of
sight of the communicating devices, there was a huge variation
in the readings of signal strength. This kind of interference
affects the performance of ZigBee more than wireless
technologies such as WiFi and Bluetooth. These factors reduce
the signal strength up to 15% – 20%. In indoor environment
we got averagely -66 dBm signal strength at 15 meter distance.
The closer the value is to 0 will show the stronger signal
strength.
B. Outdoor Experiments
In the empty car park scenario, there was no wireless
interference and no line of sight issue, therefore the degrading
factor graph showed ideal performance of ZigBee in an
outdoor environment. As the specification of the ZigBee USB
stick states, the dongles are able to transmit with distance of
more than 200m. Our results proved that ZigBee was able to
transmit about 200m with confirmation to the data sheet of the
device used. The degradation factor increased till 40 meter
distance but it started to drop consistently until 120 meter
distance. This mean signal strength was getting strong with
increase of distance. The cause was not identified due to
limited time and limited equipment.
When Bluetooth was added as interference, the pattern of
degradation factor was similar to pervious scenario. The value
of degradation factor was similar for all point except that it
started to increase again after 70m. ZigBee was only affected
slightly when the receiving ZigBee device was near to the
reference point. With the distance increase, the performance of
ZigBee was affected more. However, from 60m to 80m, it has
been seen that the degradation factor increases to a value of 23
in this scenario. It is unlike that previous scenario where the
80m point has a degradation value of less than 22. This shows
that Bluetooth does affects the performance of ZigBee at
further distance from the reference point.
In the presence of 2 – 3 meter high shrubs and clusters of
banana tree at the 20m distance served as physical interference
to ZigBee signals. From the observation of Fig. 9 and Fig. 10,
it can be seen that as the distance increases, the degradation
factor of ZigBee also increases when no obstruction is present
(line of sight). When only ZigBee was operating at line of
sight, the pattern of the degradation factor was increasing with
similar pattern to the one obtained from the car park scenario.
However, when there is no line of sight at 20m, the degradation
factor is much higher at 20m distance but at 30m the
degradation factor reduces slightly. This is due to ZigBee being
able to propagate better as the receiving device is places further
away behind an obstruction which proves that when ZigBee is
placed directly behind an obstruction, the degradation factor
increases a lot compared to the one without obstruction. As the
device was placed further behind an obstruction, the
degradation factor is similar to the one without obstruction.
When Bluetooth was used as an interference to ZigBee for
both scenarios with (Fig. 11) and without obstacle (Fig. 12), it
was observed that the range of degradation factor for both of
these graphs were higher than the ones from the previous
scenario. There is also a change in pattern for these graphs. At
0m and 10m, the degradation factor for both graphs increases,
this is similar to the ones when only ZigBee was in operation.
However, at 20m, both the readings of degradation factor
seemed to be slightly less than the 10m point. At 30m, the
value of degradation factor for both with and without obstacle
in this scenario is similar to the previous scenario. Due to the
lower degradation factor at 20m, it was observed that there is a
vast increase from 20m to 30m. The range of degradation
factor in this scenario is bigger compared to the scenario when
only ZigBee was in operation. From the huge range of
degradation factor, it simply means that the presence of shrubs
and Bluetooth does affect the performance of ZigBee signal.
The dense tree and jungle environment served huge
physical interference to the performance of ZigBee because of
no line of sight. The pattern of the degradation factor of ZigBee
was similar to the one obtained from the car park. However, in
this scenario, the degradation factor of ZigBee was increased
up to 25 on 10m distance. After this point, the degradation
factor decreases slightly at 15m and there was a sudden drop at
20m. At 20m, the degradation factor of ZigBee was even lower
than the one take at reference point. With the trees blocking the
line of sight of the communicating devices, it was observed
that the degradation factor drops faster from 15m to 20m
compared to the car park scenario.
With the presence of Bluetooth as interference, the pattern
of degradation factor differs slightly compared to previous
scenario. The degradation factor seems to be decreasing as the
distance increases, with reading at 20m and 25m being lower
than the reading at the reference point. The degradation factor
of this scenario is similar to the pattern of the graph from the
car park scenario. However, in this scenario, the degradation
factor seems to drop more in terms of value. The thick bushes
and trees create huge interferences to the ZigBee signals. When
ZigBee was operating alone, the unique pattern of the
degradation factor can be seen. The degradation factor was
slowly increasing until 15m then suffer a sudden drop at 20m.
It then slowly increases again. When Bluetooth was used as
interference, the graph of degradation factor shows that there
was an increase up to 5m. After that, the value of degradation
slowly decreases to 25m. When there is no line of sight
between the two ZigBee devices, the degradation factor
changes rapidly within a short distance.
VI. FUTURE WORK AND RECOMMENDATIONS
We can observe that the pattern of the degradation factor
was quite similar but the pattern of ZigBee signal strength was
quite unique in the sense that it was increasing to a certain
point and drops drastically after that. It will then slowly peak
up again after the drastic drop. This is quite an interesting
outcome as we were expecting that as the distance increase, the
signal strength should gradually decrease.
There is clear indication that whenever implementing a
wireless sensor networks some of parameter needs to be
considered such as line of sight, physical obstruction and signal
interference from other devices.
However, due to limitation of time and less equipment, we
were not able to identify what is the cause of this unique
pattern. It is suggested that more research and experimentation
should be done in order to identify variation in the signal
strength as distance increases. Latest spectrum analyzer
software needs to be used to improve the results. Further
experiment should be done by changing the data rate of the
ZigBee devices. With the variation of data delivery rate, the
performance of ZigBee in these conditions might vary from
one another.
This in turn, will help researcher to understand the
performance of ZigBee in different environmental conditions
as the distance increases and when there is no line of sight or
higher interference.
ACKNOWLEDGMENT
I would like to thanks Natalie Anak Lawrence Muda and
Suhail Ahmad from Swinburne University of Technology
Sarawak for their assistance and contribution to this research
work.
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