Filter Bank Multi-Carrier Modulation Technique for
Vehicle-to-Vehicle Communication
Saif H. Alrubaee, Mahamod Ismail, Mohammed A. Altahrawi, and Bara B. Burhan Centre of Advanced Electronic and Communication Engineering (PAKET), Universiti Kebangsaan Malaysia, 43600
UKM Bangi Selangor, Malaysia
Email: [email protected]; [email protected]; [email protected]; [email protected]
Abstract—Modern wireless communication like 5G systems are
expected to serve a wider range of scenarios than current mobile
communications systems. One of the major network
applications related to 5G is Vehicle-to-Vehicle (V2V)
communication that improves vehicle road safety, enhances
traffic and travel efficiency, and provides convenience and
comfort for passengers and drivers. However, supporting high
mobility is a challenge on the air interface. Accordingly,
multicarrer modulation as a multiple access is used to enhance
the connection between vehicles and to overcome this challenge.
In this paper, two multicarrier modulations are simulated. The
first one is the Orthogonal Frequency Division Multiplexing
(OFDM) while the second one is the Filter Bank Multi-Carrier
with Offset Quadrature Amplitude Modulation (FBMC/OQAM)
which is called FBMC. Simulation results show that all
waveforms have comparable BER performance. The throughput
of the FBMC is greater than the OFDM and the spectral
efficiency is increased according to the use of the OQAM
modulation. The FBMC throughput reaches 5 Mbps while the
OFDM reaches 4 Mbps; these results are due to the higher
usable bandwidth and because of using filters in FBMC which
reduces the effect of Cyclic Prefix (CP) on the signal especially
when CP is large in OFDM. Index Terms— Multicarrier, V2V, 5G, OFDM, FBMC
I. INTRODUCTION
Governments are the only entities that are responsible
to give the license of using a spectrum band for such an
application or network [1]. It means that enhancing the
spectrum usage leads to pay more to use extra bandwidth
which in general not a preferable choice to do because of
less available bands to use [2]. Because of this, many
research aims to study a lot of techniques used to enhance
the spectrum usage in order to enhance the data rate of
the transmission for various high speed networks like
Wireless Local Area Network (WLAN) and Long-Term
Evolution (LTE) [3]. One of these techniques used is the
cooperative communication systems between two or
more networks to share their available spectrum between
them [4]. For example, a cognitive radio network permits
such access by enabling nodes to identify and use
spectrum that may be dynamically shared among multiple
nodes [5].
One of the cooperative communication systems is
Vehicle-to-Vehicle (V2V) as part of Intelligent
Manuscript received December 4, 2019; revised June 2, 2020.
Corresponding author email: [email protected]
doi:10.12720/jcm.15.7.566-571
Transportation Systems (ITS) [6]. The scope of ITS is
broader than V2V, as it encompasses railway, maritime,
and aeronautical transportation systems [7]. Motivations
for ITS include increased system efficiency, reduced
transportation delays, economic growth, passenger
entertainment, and the most important issue is the safety.
This is most acute in V2V, as automobile traffic accidents
still claim thousands of lives each year in large developed
nations [8].
V2V is used to study the communication between
vehicles in travelling road. The importance of V2V
comes from the benefits that it enhances the road safety,
knows the road conditions like accidents or traffic jams,
relays signals from one vehicle to another and/or lets
users communicate and exchange multimedia information
[9]. Fig. 1 shows the V2V communication network, it
consists of more than one vehicle on the road in the dame
travelling destination or opposite. The communication
between vehicles affected by the road conditions or area
surrounding the vehicles. The vehicle's speed also is an
important parameter that affects the communication link
and changes the channel characteristics during
communication.
Fig. 1. V2V communication [10]
The V2V channel is distinct from that of many typical
communication system channels. The closest comparison
may be to the cellular channel with some differences
between them such as the antenna heights of both
transmitter (Tx) and receiver (Rx) in V2V are low and
mobile [11]. In addition to this, V2V channels can have
the Line of Sight (LOS) between Tx and Rx obstructed
more frequently and scattering is often non-isotropic. Due
to the vehicle moving, the channel variation rates can also
be larger than in cellular, or in other words, the V2V
channel is statistically stationary for a shorter time period
than in cellular.
In addition, due to multiple scattering or rapid time
variation, in some cases amplitude fading may be more
severe than in the most common cellular fading model
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[12]. Because of this, there are three main parameters
affect the V2V channel and considered important to
optimized in order to have high performance of the
communication. These parameters are the path loss which
represents the power loss due to the distance between
transmitter and receiver and it used to calculate the link
budget of the network [13]. The second one is the Delay
Spread which is coming from the frequency selectivity
that is quantified as the coherence bandwidth. The last
parameter is the Doppler Spread which is reciprocally
related to the channel’s coherence [14].
This paper aims to study the BER and throughput
performances of the use of different Multicarrier
modulation like FBMC and OFDM in V2V channel
communication in order to overcome the aforementioned
challenges that V2V faces. The remainder of this paper is
organized as follows: Section II discusses the use of
Multicarrier modulation in V2V with some concentrate
on using FBMC due to the less Out-of-Band (OOB)
emission and Peak-to-Average Power Ratio (PAPR).
Section III shows the proposed system and methodology
used in this simulation. Section IV addresses BER
performance and throughput results for the use of FBMC
compared with to the results obtained from the use of
OFDM. Section V concludes the paper.
II. MULTICARRIER MODULATION USED IN V2V
Multicarrier modulation (MCM) techniques enable
transmission of a set of data over multiple narrow band
subcarriers simultaneously and they considers suitable
techniques to overcome the pathloss that affects the V2V
communication and the delay spread in the short range
communication [15]. Fig. 2 shows the general block
diagram of MCM transmitter and receiver. It consists of
generating Inverse Fast Fourier Transform (IFFT)
symbols with addition to adding CP to the MCM symbols
at the transmitter. The receiver section consists of the
opposite operations of the transmitter. The main example
of the MCM is the Orthogonal Frequency Division
Multiplexing (OFDM) which becomes the most widely
used baseband MCM waveform in modern wireless
communication systems. However, OFDM encounter
large side lobes that contributes to undesired Out-of-Band
(OOB) emission and large Peak-to-Average Power Ratio
(PAPR) [16]. Excessive OOB emissions partially results
from large side lobes at the baseband that leads to strong
Adjacent Channel Interference (ACI), especially in small
cell systems such as those proposed for use in TV white
space and heterogeneous networks [17].
Fig. 2. General multicarrier transmitter and receiver block diagram for
point to point [18]
Since OFDM is widely considered as a promising
candidate for such applications, Cheng, et al. [19]
simulates OFDM to improve spectral efficiency as well
as enhanced reliability in V2X channels with correlated
frequency-selective fading and inevitable Doppler effects.
Bazzi, et al. [20] investigates the radio resource
management problem for D2D-based V2V
communications by using multi-carrier concept. Matolak
[21] simulates the propagation channel of V2V network
by knowing the channel impulse response and its Fourier
transform in order to mitigate the interference during
transmission. The same is reported by Feteiha and
Hassanein [22] by discussing the performance of V2V
system when using LTE-Advanced (LTE-A) networks
where vehicles act as relaying cooperating terminals. The
simulation results of this study show significant diversity
gains are achievable, and that error rates can be greatly
reduced.
Filter Bank Multi-Carrier (FBMC) modulation is a
family of MCM techniques proposed as an alternative to
OFDM to overcome the aforementioned drawbacks [23].
Different from OFDM, the real and imaginary parts of the
QAM symbols are processed separately with 2×symbol
rate and the zero ISI and ICI with small amount of side
lobes are resulted from the use of filters at the transmitter
and receivers. This construction of FBMC leads to
enlarge the latency of the process, but with enhanced
spectral efficiency [24]. As shown in Fig. 2 at the
receiver, the sub bands do not overlap with each other,
and between sub bands, a small number of guards to are
left to accommodate asynchronous transmission [25]. The
required number of guard tones depends on the transition
region of the filters.
Fig. 3 shows how FBMC makes the waveforms more
flexible to use and coexistence because of the flexibility
of the time-frequency arrangement/allocation besides the
uniform distribution of the FBMC. Compared to OFDM,
the FBMC waveform in V2V communication has short
Transmission Time Interval (TTI) duration and enlarged
subcarrier spacing [26] which are suitable to overcome
the delay and Doppler spread of the channel.
Fig. 3. Flexibility and coexistence of waveforms enabled by FBMC [24]
N-
IFFT
CP
insertionf(n) h(n) + f *(-n)
CP
removal
N-
FFTEq.
TX RX
S*(n)
z(n)
Data r(n)Data
Received
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III. SYSTEM MODEL AND METHODOLOGY
Fig. 3 shows the proposed system model in this paper
in order to evaluate the throughput and BER of the
FBMC with comparison with OFDM. The figure shows
that there are two lines of the road, the first line consists
of vehicles that are travelling in the same direction with
the same speed of travelling. The communication
between them is affected by the channel response H. The
use of multicarrier in V2V communication is used here in
this simulation. The same road has another line of
travelling where vehicles travel in the opposite direction.
The simulation is performed for the two vehicles
travelling in the same direction.
This simulation considers the geometry of the highway
scenario with two vehicle travels along the road in one
direction towards the base station with 140 km/h speed
for both of them. All communication between vehicles
are assumed to be LoS communication to simplify the
process simulation.
Fig. 4. The system model
As mentioned before, the communication is assumed
to be LoS, the channel characteristics that are used in this
simulation scenario is obtained as:
( ) ( )
∑ ( )
∑ ( )
∑ ( )
where P, Q, and R are respectively the numbers of mobile
discrete scatters, static scatters, and diffuse scatters and τ,
τp, τq, and τr are excess delays, which can be
immediately computed by the geometry taking into
account only single bounce. After calculating the channel
response H, the comparison between using several types
of multicarrier waveforms are simulated in order to make
a full simulated overview about the advantages of using
FBMC as a modulation and multiple access techniques in
modern wireless communication. The modulation order is
changed and the BER and throughput as a performance
metric of this paper are obtained.
The simulation parameters which are used in this paper
are shown in Table I. The carrier frequency used is 2.8
GHz where the subcarrier spacing equals 15 kHz to
mitigate interference between sub-carriers. The FFT size
used for OFDM is 1024 with available bandwidth 10
MHz. The speed of vehicles is assumed to be the same
along the road which is equal to 140 km/h. The
modulation orders used are QPSK, 16-QAM, and 64-
QAM. The numbers of vehicles on the road are two in the
same direction of travelling.
TABLE I: THE SIMULATION PARAMETERS AND VALUES
Parameters Values
Carrier frequency 2.8 GHz
Subcarrier spacing 15 kHz
FFT size 1024
System bandwidth 10 MHz
Modulation QPSK, 16-QAM, 64-QAM
Cyclic prefix LTE normal cyclic prefix
Vehicles speed in the same direction 140 km/h
Number of vehicles to be simulated 2
Number of transmitters 1
Static scattering 10
Mobile scattering 10
Diffused scattering 200
The simulation starts from initializing the simulator
used with all simulation parameters required as
mentioned in Table I. The process starts to check what
the multicarrier waveform to be used is. The process
continues and the cyclic prefix is performed. The
throughput and BER performance are calculated and
graphed with respect to different values of SNR. The
modulation order of QAM changed to another value and
simulated with FBMC. The BER results of different
QAM modulation are compared together.
IV. SIMULATION RESULTS AND DISCUSSION
Fig. 5. Power spectral densities for OFDM and FBMC/OQAM
In Fig. 5, the spectral densities of both OFDM and
FBMC over the frequency have been shown. It is clear
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(1)
that the FBMC spectral density shows a considerable
reduction in the Out-Of-Band (OOB) leakage compared
to OFDM, which can gives enhancement of an
asynchronous transmission without the need of perfect
synchronization with efficient use of spectrum due to the
absence of the CP.
Modulation order in wireless communication is very
important to be simulated and estimated. The QAM
modulation is also one of the modulation schemes that is
used in modern wireless communication. QAM is also the
preferable modulation scheme for OFDM because of its
immunity to the interference. The study of changing the
order of QAM modulation is performed to study its effect
on the FBMC signal. Fig. 6 shows an acceptable result
with the original QAM BER curves. It shows that the
BER of the QPSK modulation is better than that obtained
from the 16-QAM and 64-QAM. This is because lower
adjacent symbol interference. The spectral efficiency of
the high order modulation is preferable. Because of this,
the combination between FBMC and high order
modulation is preferable in modern wireless
communication because of the high spectral efficiency
comes from the high order modulation and the immunity
to nose and OOB comes from the use of FBMC.
Fig. 6. BER response of FBMC with different QAM order
Fig. 7. BER performance for the FBMC compared to OFDM
In order to study the FBMC effects on the V2V
channel, the OFDM is applied to the proposed system and
the BER of both MCM is graphed in Fig. 7 which shows
the BER performance of FBMC compared to the OFDM.
The response of both multiple accesses is the same until
11 dB. This is logical because FBMC and OFDM are the
same in building except that the FBMC uses filter at the
end of transmitter and at the beginning of the receiver.
This enhancement appeared in Fig. 7 because FBMC in
general aims to overcome some of the shortcomings that
were encountered with OFDM which arises from the fact
that OFDM requires the use of CP that reduces the
throughput of the transmission and also wastes power. In
FBMC, the use of filter at transmitter and receiver
removes the side lobes from the signal which leads to a
much cleaner carrier signal.
The throughput of the FBMC is greater than the
throughput of the OFDM as shown in Fig. 8. FBMC has
higher throughput than OFDM due to higher usable
bandwidth and because of using filtering in FBMC which
reduces the effect of CP on the signal especially when CP
is large. Compared to the previous figures, OFDM and
FBMC have the same transmit power which leads to a
smaller SNR for FBMC compared to OFDM because the
power is spread over a larger bandwidth. Fig. 8 shows
that the throughput FBMC reaches 6.5 Mbit/s at 30 dB
SNR while it reaches only 5 Mbit/s at the same value of
SNR in case of OFDM.
Fig. 8. Throughput of the system compared between FBMC and CP-
OFDM
V. CONCLUSION
The goal of this paper is to make a full overview and a
practical simulation of the use of different types of
multicarrier waveforms used in modern wireless
communication especially for V2V communication. The
simulation results show that the response of all
multicarrier waveforms for low mobility V2V networks is
the same because FBMC and OFDM are the same in
building except that the FBMC uses filter at the end of
the transmitter and at the beginning of the receiver. The
throughput of the FBMC is greater than OFDM at high
SNR values and the BER performance of FBMC is more
-5 0 5 10 15 20 25 30 3510
-3
10-2
10-1
100
SBR (dB)
BE
R
QPSK
16-QAM
64-QAM
-5 0 5 10 15 20 25 30 35 4010
-3
10-2
10-1
100
SNR [dB]
BE
R
FBMC
OFDM
-10 -5 0 5 10 15 20 25 300
1
2
3
4
5
6
7
SNR (dB)
Thro
ughput
[Mbit/s
]
FBMC
OFDM
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enhanced than OFDM especially above 20 dB SNR.
There are several possible future works like an increasing
number of vehicles on the road, considering the effect of
interference between them and considering the effect of
packet size during transmission.
CONFLICT OF INTEREST
The authors declare no conflict of interest
AUTHOR CONTRIBUTIONS
Saif H. Alrubaee and Mohammed A. Altahrawi have
prepared and analyzed the data; Mahamod Ismail has
reviewed the research; Bara B. Burhan has modified the
paper organization and outline. All authors have
approved the final version.
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Saif Alrubaee was born in Baghdad,
Iraq, in 1993. He received the B.Eng.
degree in Communication and
Electronics Engineering from the
University of Almamoon University
College, Iraq, in 2015 and the M.Sc.
degree in Communication and Computer
Engineering from Universiti Kebangsaan
Malaysia (UKM), Bangi, Malaysia, in
2019. His research interests include mobile communications and
wireless networking with particular interest on the Internet of
Vehicles (IoV).
Mahamod Ismail was born in Selangor,
Malaysia, in 1959. He received the
B.Eng. degree in Electronics and
Electrical Engineering from the
University of Strathclyde, United
Kingdom, in 1985 and the M.Sc. degree
in Communications Engineering and
Digital Electronics from the University
of UMIST, Manchester, United Kingdom,
in 1987. He is currently a professor at the
Department of Electrical, Electronic and System Engineering.
His research interests include mobile communications and
wireless networking with particular interest on radio resource
management for 4G and beyond.
Mohammed Altahrawi was born in
Gaza Strip, Palestine, in 1981. He
received the B.Eng. degree in
Communication and Computer
Engineering from the Islamic University
of Gaza, Palestine, in 2003 and the M.Sc.
degree in Communication and Computer
Engineering from Universiti Kebangsaan
Malaysia (UKM), Bangi, Malaysia, in
2016. His research interests include Internet of Vehicles (IoV),
Multi-Radio access technology, and Software Defined
Vehicular Network (SDVN).
Bara Burhan was born in Baghdad, Iraq,
in 1993. He received the B.Eng. degree
in Communication and Electronics
Engineering from the University of
Almamoon University College, Iraq, in
2016 and the M.Sc. degree in
Communication and Computer
Engineering from Universiti Kebangsaan
Malaysia (UKM), Bangi, Malaysia, in
2019. His research interests include
mobile communications and wireless networking with particular
interest on the Internet of Vehicles (IoV).
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Journal of Communications Vol. 15, No. 7, July 2020
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