3C Tecnología. Glosas de innovación aplicadas a la pyme. ISSN: 2254 – 4143 Ed. 35 Vol. 9 N.º 3 Septiembre - Diciembre
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A NOVEL METHOD FOR IMPROVING BIT ERROR RATE IN
SENSOR NETWORKS BY USING ORTHOGONAL SPACE TIME
BLOCK CODE (OSTBC) CODING
Richa Tiwari
Assistant Professor, Department of ECE, Vishveshwarya Group of Institution.
Gr. Noida (U.P), (India).
E-mail: richavgi@gmail.com ORCID: https://orcid.org/0000-0001-6924-2217
Deepak Nagaria
Professor, Department of ECE, B.I.E.T,
Jhansi, (U.P), (India).
E-mail: deepaknagaria@bietjhs.ac.in ORCID: https://orcid.org/0000-0002-3043-9765
Rajesh Kumar
Associate Professor, Department of ECE, North Eastern Regional Institute of Science and Technology, Nirjuli, Itanagar,
Arunachal Pradesh, (India).
E-mail: rk@nerist.ac.in ORCID: https://orcid.org/0000-0001-9559-7329
Recepción:
12/05/2020
Aceptación:
08/07/2020
Publicación:
14/09/2020
Citación sugerida:
Tiwari, R. Nagaria, D., y Kumar, R. (2020). A novel method for improving Bit Error Rate in sensor networks by using
Orthogonal Space Time Block Code (OSTBC) coding. 3C Tecnología. Glosas de innovación aplicadas a la pyme, 9(3), 59-75.
https://doi.org/10.17993/3ctecno/2020.v9n3e35.59-75
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ABSTRACT
For the designing of any network, lifetime and size of the network are the most important parameters
in addition to that high data rate and low bit error rate also play an important role in the designing of
any sensor network. In this paper, new transmission techniques for the transmission of sensors data has
been proposed for sensor networks by combining various modulation and coding techniques into the
network transmission. The proposed technique is used to improve the Bit Error Rate performance of
the wireless sensor network, in most of the wireless sensor networks ,bits are converted into packets and
these packets are transmitted from source to destination during that transmission the quality of physical
layer is determined by the Bit Error Rate (BER) and the Packet Delivery Rate (PDR). The physical layer
deals with transmission of bits over wireless link the designing constraints of this layer is modulation,
diversity and coding. In this paper various modulation, coding and diversity techniques are incorporated
into sensor network for reducing Bit Error Rate (BER). The proposed system divides the network into
two types of nodes, rst one is the sensor nodes, equipped with short distance transmission capability and
another one is special nodes that are equipped with modulators and coders for transmitting data over
long distance. This proposed system also extended for providing the secured data transmission by the use
of various error detection and correction codes.
KEYWORDS
Bit Error Rate (BER), Orthogonal Space Time Block Code (OSTBC), Internet Of Things (IOT),
Orthogonal Transform Division Multiplexing (OTDM), Space Time Coding (STC), Singular Vector
Decomposition (SVD).
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1. INTRODUCTION
Wireless Sensor Networks (WSNs) are the combination of many tiny sensing elements for transferring
data from source to destination using multi-hop transmission. There are a number of applications in
which real time monitoring is required so a huge amount of data is collected after the collection of this
data various mathematical transformations are required to convert this raw data into useful information.
Some applications require security of the data whereas for some applications such as wireless multimedia
sensor network major concern is accuracy of the data and high data transfer rate. In agriculture, these
networks can provide the report about the growth rate of plants. This can reduce labor work and the
cost of production by Zhen, Hong, and Wang (2011) and Sun et al. (2011). However, sensor network has
tiny nodes with limited transmission capability and limited battery lifetime so long distance transmission
of data is also a challenging task in WSNs. According to an Article “Wireless Channel Propagation
Characteristics and modeling research in Rice eld sensor networks” by Gao et al. (2018), in wireless
sensor network the quality of communication depends upon the condition of the environment where the
sensor network is planned to operate for example the attenuation speed in wireless channel propagation is
directly related to the development of the rice plant. In this paper author observed that crop plants suer
from dierent wireless channels eects such as reection, scattering and diraction, So various diversity
techniques helps us to mitigate these eects in sensor networks. Farhang-Boroujeny and Moradi (2016)
showed that, Orthogonal Frequency Division Multiplexing (OFDM) modulation technique played an
important role in wireless communication systems due to its ability of high frequency selectivity and
achieving high data transfer rate without any Inter Symbol Interference (ISI).
When data travel a long distance then several multipath eects like fading and reection of signals are also
coming into consideration. Diversity techniques are also playing an important role in any communication
because these techniques mitigate the eect of multipath fading and shadowing from buildings and objects
(Alamouti, 1998). According to a special issue on codes and graphs, in the applications where secure
communication is required, the spread spectrum system plays an important role, for the applications
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where the error control is the major requirement then channel encoder and decoder plays an important
role because these codes automatically reduce the error in communication. In many applications where
size and cost of the antenna is a major limitation, the cooperative transmission method is considered as
better approach.
A Wireless sensor network can use generally cooperative relaying for increasing the lifetime of the sensor
network. In wireless medium long distance communication requires more power than the short distance
communication because after traveling long distance signals become weak.
In the proposed scheme, network nodes are divided into two categories: in rst category, nodes are
used for sensing and these sensing nodes are having limited transmission capability. In Second category
nodes are special modules which have long distance transmission capability where various modulation
and coding techniques are used in the designing of these special nodes for improving the Bit Error
Rate (BER) performance. If analysis is done on total power consumed, then most of the nodes power
are consumed during transmission, so the lifetime of rst category automatically increase by the use of
these special nodes so introducing these strategies inside the network increase the lifetime of whole
sensor network. Aly et al. (2019) proposed a Space-time coding Orthogonal Space Time Block Codes
(OSTBC) technique for enhancing the Bit Error Rate (BER) performance, security, increased diversity
gain and decrement in the fading eect. Hasna and Alouini (2003) demonstrated that Decode and
Forward (DF) protocols performes better at low SNR. Baek and Song (2008) designed and analyzed
the performance of cooperative diversity in MIMO-OFDMA system. Jing and Jaferkhani (2009) have
analyzed the performance of single and multiple relays and calculate their diversity order. Decode and
Forward (DF) protocols are generally used in WSNs where the information bits are detected, decoded
and sent forward. Lu, Nikookar and Xu (2010) demonstrate that decode and forward protocols for
reducing channel interference and additive noise at the relay.
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In this paper by using the multiple access techniques data from dierent sensors are combined together
and this data has been sent to the destination by the use of OSTBC encoding and modulation. System
becomes more complex in comparison to the normal sensor network at transmission level but the
advantage of this system is improvement in Bit Error Rate performance and transmission work is
handled by some specic modules so network life time does not depend on the complexity of transmission
protocols and all nodes power is not wasted in long distance transmission. Another advantage of using
this method of transmission is that the dependency on internet or requirement of replacing the sensor
nodes by the small IOT devices has been overcome by installing such type of communication networks
(Arroyo et al., 2019).
In Elhabyan and Yagoub (2014), the parameters for judging the performance of any sensor Network are
average consumed power, packet delivery rate, network coverage and number of nodes in a particular
area.
In WSNs, nodes perform two functions: rst sensing the information and second transferring that
information to destination. In Castanedo (2013), there are many topologies for arranging the sensor
nodes and routing protocols for transferring the sensed information. In Din et al. (2014) & Han et al.
(2014) has proposed many optimization technique for reducing the average consumed power.
The key contribution of this paper is modulation and coding technique are incorporated in the
transmission of sensed data. After that simulation has been carried out for dierent type of modulation
such as Frequency shift Keying (FSK) with diversity, Binary Phase shift keying (BPSK) with diversity,
BPSK with OSTBC coding and BPSK, BFSK and QAM for dierent diversity order. The simulation
results show the improvement in BER of the network by including the modulation and coding capability
in the special nodes on the place of using complex routing algorithms for load sharing.
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The rest paper is arranged as follows. In Section 2, detailed description of the proposed system. System
evaluation and simulation results are presented in Section 3. This is followed by the Section 4 that do
conclusion and showing the advantages of the proposed technique.
2. MATERIALS AND METHODS
The proposed network architecture is shown in Figure 1, which shows that data are coming from multiple
sensor nodes, these sensor nodes sensing the data and the data from each sensor node is received in the
special node at discrete time intervals. The special nodes perform the data acquisition, modulation and
coding. Data received at special node is of two types useful and useless data, useless data include the
noise signals and rest of the data is comes into the category of useful data and these are the observations
from the detected target. The special node performs data fusion. The techniques which are used for the
purpose of fusion are data association techniques (Akkaya & Younis, 2005), by using that technique data
from dierent sensor nodes are combined together after that special node do modulation and coding for
transmitting that data to the destination.
Figure 1. OSTBC coded data transmission from source to destination through Rayleigh fading channel. Source: authors’ own
elaboration.
The sensing range characteristics are depending on the type of the sensors being used for the purpose
of sensing. Such as for PIR sensor it is 20 feet’s and for Inductive proximity sensor it is 50mm since
these sensors are connected to radio transceiver board (Ex CC 2420), transmission range is determined
by the transmission power used by the module. The module CC2420 supports the choice of several
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power levels with 0dbm (eq. 1mw) being the maximum power which decides the transmission capability.
Transmission range also depends on the environmental condition, obstacles etc. For WSN standard
802.15.4 the communication range is from 20m to 30m for indoor applications and 75m to 100m for
outdoor applications. After that if we want to increase the communication range or speed of transmission
then there are two solutions, rst the use of special IOT devices connected to high speed Wi-Fi network,
second solution is modulation and coding of the signals.
The incoming data from dierent sensors are combined together and modulated by any digital modulation
techniques such as BPSK, BFSK or QAM etc. after that data is OSTBC encoded and transmitted via
fading channel.
The OSTBC Encoder block encodes an input signal sequence using Orthogonal Space Time Block
Code. In this case the input signal is sampled because fusion node inside the transmission module select
the data at discrete time interval so sampled version of data is ready for transmission on that stage. The
OSTBC encoder block supports many OSTBC encoding algorithms that are Depending on the rate and
number of transmitting antenna used. In this section, OSTBC codes with 3 transmitting antenna and
Rate3/4 is used here. In this paper, 3x2 MIMO is implemented using Alamouti algorithm. A complex
orthogonal space-time block code, three consecutive symbols S
1
, S
2
and S
3
are encoded with the following
space-time code word matrix:
(1)
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2.1. MATHEMATICAL MODELING OF OSTBC ENCODED SIGNAL
In this section, a brief description about the OSTBC encoding scheme for three transmit antennas and
two receiving antennas are given, we are using a Orthogonal Space Time Block Code with three transmit
antennas where the rate of this code is ¾.The input to the OSTBC encoder is a 3x1 vector signal and
the output is a 4x3 vector signal. A random binary signal is modulated by using Binary phase shift
keying (BPSK) after that this signal goes inside an OSTBC coder for transmission over a Rayleigh fading
channel. The fading channel model has six independent links due to the three transmitting antennas and
two receiving antennas. An additive white Gaussian noise (AWGN) is added at the receiver side and all
signals are combined into a single stream for demodulation by using OSTBC combiner.
In the rst time instant, antenna1transmits X1, antenna2 transmits X
2
and antenna3 transmits X
3
while
during second time instant, antenna1 transmits –X
2
*, antenna2 transmits X
1
*and antenna 3 transmits 0,
in third time instant antenna1 transmits X
3
*,antenna 2 transmits 0 and antenna3 transmits –X
1
*and in
fourth time instant antenna1 transmits 0,antenna2 transmits X
3
* and antenna3 transmits –X
2
*.
At the receiver side the received signal is given by the following equations:
Received signal at rst time slot:
(2)
(3)
Received signal at second time slot:
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(4)
(5)
Similarly, we can write down the received signals equation for third and fourth time slot where n(3) and
n(4) are AWGN ,that are added during these slots after that combiner combines all signals and estimate
the transmitted signal vector as:
(6)
Where
k
represents the k
th
symbol in the OSTBC code matrix G
i,j
represents the estimate for the channel
for i
th
transmitting antenna and j
th
receiving antenna. The values of i and j range from 1toN (the number
of transmitting antennas) and 1 to M (the number of receiving antennas).
Where
= summation of channel power per link.
2.2. BER ANALYSIS
The Bit Error Rate (BER) of the proposed scheme; the BER is dened as the number of bits in error
divided by the total number of transferred bits during the studied time interval so:
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When, we talk about the performance of any sensor network then packet delivery Rate (PDR) is dened
as the ratio of the number of packets successfully received by all cluster heads to the number of packets
generated so both PDR and BER are related to the information or the data transferred from source to
destination. These two parameters are related to the transmission capability of any sensor network so
if the BER performance of any network is improved then this improvement automatically reect in the
packet delivery rate or in other words reduction in the BER is the increment in the PDR.
3. SIMULATION RESULTS
In this section, the proposed scheme of transmission is compared to the conventional modulation
schemes such as BPSK, BFSK and QAM with diversity. Set of architectures are evaluated in terms of
modulation with OSTBC coding and modulation with diversity techniques. The performance of these
network architectures is discussed in the following subsections. A BPSK modulated system with diversity
of 6 is considered and compared this with OSTBC coding of rate ¾. After that the eect of changing
the modulation technique is studied. For simulation a random binary data is created. For the selected
OSTBC code the output signal power is 2.25 W and the channel symbol period for this simulation is 7.5
e
-4
sec due to the code rate ¾. All the parameters used in simulation are collected in Table 1.
Table 1. Simulation parameters.
Type of Channel Rayleigh Fading Channel
Type of modulation BPSK,BFSK,QAM
Diversity order 6
Number of Subcarriers 1024
Carrier Frequency 2Ghz
FFT size 64
Cyclic prex 0%
Number of Monte carlo simulation 2e6
E
b
/N
0
(dB) 0 to 30 dB
Source: authors’ own elaboration.
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3.1. EFFECT OF OSTBC CODING
Figure 2 shows the BER of the proposed technique in comparison to the BPSK with diversity order 6.
In OSTBC coded transmission of BPSK modulated signal out of 100000 received bits only 48 bits are
in error. The BER reaches about 0.0013 at 9dB, whereas in diversity transmission this value is 0.0009 at
9dB. These results showed that there is little bit dierent in the BER performance of both techniques.
Figure 2. BER of the OSTBC transmission in comparison with diversity transmission of order 6. Source: authors’ own elaboration.
3.2. EFFECT OF MODULATION TECHNIQUE AND DIVERSITY
Figure 3 shows the eect of changing the modulation technique on the proposed techniques if we use the
BFSK in place of BPSK then the performance of OSTBC transmission techniques does not improve the
performance of the network in comparison to the Diversity techniques. In the transmission of OSTBC
coded FSK, out of 240 received bits 101 bits are in error. BER is 0.0077 at 9dB, for coherent FSK with
diversity order 6. The BER is 0.0791 for non-coherent FSK with diversity order 6. For OSTBC coded
transmission of FSK modulated wave it is too large that is 0.4714 at 9 dB. The BER performance of
these technique is shown in Figure 3.
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Figure 3. BER of the OSTBC transmission of FSK signal in comparison to the FSK with diversity order 6. Source: authors’ own
elaboration.
The Performance Comparison of all the transmissions are collected in Table 2.
Table 2. Comparitive Performance.
Mode of transmission BER at 3dB BER at 6dB BER at 13 dB Performance
OSTBC coded BPSK 0.0306 0.0100 4x10
-5
Good
OSTBC coded BFSK 0.5104 0.4803 0.4782 Very Poor
Diversity transmission of Coherent
BPSK
0.0344 0.0077 1.92x10
-5
Good
Diversity transmission of Coherent
BFSK
0.0915 0.0346 3.84x10
-4
Comparatively Low
Diversity transmission of Non-
Coherent BFSK
0.3134 0.1952 0.0084 Moderate
3.3. EFFECT OF DIVERSITY ORDER FOR DIFFERENT MODULATION TECHNIQUES
For agriculture eld applications, diversity techniques play an important role to overcome the diculties
arise due to several multipath eects. In wireless sensor network transmission of signal inside the channel
depends upon the growth of plants so in such type of situations diversity techniques helps us in estimating
the original signal. In that section we also see the eect of using diversity order inside the system.
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For dierent diversity orders, the calculated BER for dierent modulation techniques such as Phase
shift keying (PSK), Frequency shift keying (FSK) and 4-Qudrature amplitude modulation (4-QAM) is
compared in this section which is given in Figures 4, 5, 6. These gure shows how we can improve the
BER of any modulation technique by increasing the diversity order. In the agriculture eld application,
a variable diversity schemes for dierent growth time will improve the performance of sensor networks.
Figure 4. BER of the PSK signal with changing diversity order. Source: authors’ own elaboration.
Figure 5. BER of the FSK signal with changing diversity order. Source: authors’ own elaboration.