1. Abstract— The aim of this paper is to consider an encoding digital
technique concerning the use of orthogonal division multiplexing
(OFDM) and studied its properties, The primary advantage of
OFDM over single-carrier schemes is its ability to cope with severe
channel conditions (for example, attenuation of high frequencies in
a long copper wire, narrowband interference and
frequency-selective fading due to multipath) without complex
equalization filters, some of advantages and limitations. Also
considered underwater acoustic communications Underwater
Acoustic Sensor Networks will consist of sensors and vehicles
deployed underwater and networked via acoustic links to perform
collaborative monitoring tasks, The shallow water acoustic
communication channel exhibits a long delay spread because of
numerous multipath arrivals resulting from surface and bottom
interactions, also considered a direct sequence spread spectrum
(DSSS) as one of the methods used in underwater acoustic network
communications (UAN).
Index Terms— AUV; DFE; DMT; DSSS; HR; ICI; OFDM;
UAN; UAC.
I. INTRODUCTION
rthogonal frequency-division multiplexing (OFDM) is a
method of encoding digital data on multiple carrier
frequencies. OFDM has developed into a popular scheme for
wideband digital communication, whether wireless or over
copper wires, used in applications such as digital television and
audio broadcasting, DSL broadband internet access, wireless
networks, and 4G mobile communications [1].
OFDM is essentially identical to coded OFDM (COFDM),
discrete multi-tone modulation (DMT), and is a
frequency-division multiplexing (FDM) scheme used as a
digital multi-carrier modulation method. A large number of
closely spaced orthogonal sub-carrier signals are used to carry
data. The data is divided into several parallel data streams or
channels, one
for each sub-carrier. Each sub-carrier is modulated with a
conventional modulation scheme (such as quadrature amplitude
modulation or phase-shift keying) at a low symbol rate,
maintaining total data rates similar to conventional
single-carrier modulation schemes in the same bandwidth.
The use of direct sequence code division multiple access
(DS-CDMA) has some benefits such as multi-user access and
low probability of detection (LPD). In Stojanovic and Freitag
(2006), the authors explored the use of a DFE to combat ISI in
DS-CDMA systems. A symbol decisions feedback (SDF) DFE
uses the symbol decisions after de-spreading on the feedback
path. As the symbols in a DS-CDMA system are relatively long,
a DFE using SDF is not able to track rapidly varying channels.
For such channels, a chip hypothesis feedback (CHF) can help
track the channel at the chip rate rather than the symbol rate.
For M-ary signal constellations, the complexity of the CHF is at
least M times higher than the SFD as M different hypotheses
have to be tracked. However, the advantage of a CHF was
clearly demonstrated at high, spreading factors during a
shallow water experiment in Italy. The authors expect that the
performance difference would be more apparent in a mobile
environment as one would expect the channel to change more
rapidly. If the statistics of the errors in channel estimation are
known, DFE or linear equalizer performance can be estimated
(Preisig 2005).
0 100 200 300 400
-1
-0.5
0
0.5
1
OFDM Sy mbol Input Data
0 100 200 300 400
-1
-0.5
0
0.5
1
OFDM Recovered Sy mbols
0 2000 4000 6000 8000
-40
-20
0
20
40
Trans mitted OFDM
0 2000 4000 6000 8000
-40
-20
0
20
40
Received OFDM
Fig. 1. OFDM signal generation and recovering in Time and Frequency
domain respectively.
O
C
Orthogonal Frequency Division Multiplexing
(Underwater Acoustic Communications)
Dheyauldeen Najm Abdulameer1,a
, Prof. Dr. R. Badlishah Ahmad2,b
School of Computer and Communication Engineering (SCCE)
University Malaysia Perlis (UniMAP)
Kuala Perlis, Perlis, Malaysia
a
dhdena_70@yahoo.com
b
badli@unimap.edu.my

2. The primary advantage of OFDM over single-carrier schemes
is its ability to cope with severe channel conditions (for
example, attenuation of high frequencies in a long copper wire,
narrowband interference and frequency-selective fading due to
multipath) without complex equalization filters. Channel
equalization is simplified because OFDM may be viewed as
using many slowly modulated narrowband signals rather than
one rapidly modulated wideband signal. The low symbol rate
makes the use of a guard interval between symbols affordable,
making it possible to eliminate intersymbol interference (ISI)
and utilize echoes and time-spreading to achieve a diversity
gain, i.e., a signal-to-noise ratio improvement. This mechanism
also facilitates the design of single frequency networks (SFNs),
where several adjacent transmitters send the same signal
simultaneously at the same frequency, as the signals from
multiple distant transmitters may be combined constructively,
rather than interfering as would typically occur in a traditional
single-carrier system.
II. ORTHOGONALITY
In OFDM, the sub-carrier frequencies are chosen so that the
sub-carriers are orthogonal to each other, meaning that
crosstalk between the sub-channels is eliminated and
inter-carrier guard bands are not required. This greatly
simplifies the design of both the transmitter and the receiver;
unlike conventional FDM, a separate filter for each sub-channel
is not required.
The orthogonality requires that the sub-carrier spacing is line
spacing.
(1)
where TU seconds are the useful symbol duration (the receiver
side window size), and k is a positive integer, typically equal to
1. Therefore, with N sub-carriers, the total passband bandwidth
will be:
B≈N.Δf (Hz) (2)
The orthogonality also allows high spectral efficiency, with a
total symbol rate near the Nyquist rate for the equivalent
baseband signal (i.e. near half the Nyquist rate for the
double-side band physical passband signal). Almost the whole
available frequency band can be utilized. OFDM generally has
a nearly 'white' spectrum, giving it benign electromagnetic
interference properties with respect to other co-channel users.
-5 0 5 10 15 20
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Frequency (K Hz)
S(f)
OFDM spectrum which consists of N equivalent distant sinc function
Fig. 2. The spectrum of an OFDM signal that shows its subcarriers are
orthogonal to each other
OFDM requires very accurate frequency synchronization
between the receiver and the transmitter; with frequency
deviation the sub-carriers will no longer be orthogonal, causing
inter-carrier interference (ICI) (i.e., Crosstalk between the
sub-carriers). Frequency offsets are typically caused by
mismatched transmitter and receiver oscillators, or by Doppler
shift due to movement. While the Doppler shift alone may be
compensated for by the receiver, the situation is worsened
when combined with multipath, as reflections will appear at
various frequency offsets, which is much harder to correct. This
effect typically worsens as speed increases, and is an important
factor limiting the use of OFDM in high-speed vehicles.
Several techniques for ICI suppression are suggested, but they
may increase the receiver complexity.
III. UNDERWATER COMMUNICATIONS
High-speed communication in the underwater acoustic
channel has been challenging because of limited bandwidth,
extended multipath, refractive properties of the medium, severe
fading, rapid time variation and large Doppler shifts. In the
initial years, rapid progress was made in deep water
communication, but the shallow water channel was considered
difficult. In the past decade, significant advances have been
made in shallow water communication [2].
0 2 4 6 8 10 12 14
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Multipath Phenomenon in Underwater Acoustic Waves
Time (sec)
Amplitude(Volt)
Multipath in time domain
Fig. 3. Multipath Phenomenon in Underwater Acoustic Signals

3. The shallow water acoustic communication channel exhibits a
long delay spread because of numerous multipath arrivals
resulting from surface and bottom interactions. Movement of
transducers, ocean surface, internal waves lead to rapid time
variability and, consequently, a high Doppler spread in the
channel. Coherent modulation schemes such as phase shift
keying (PSK) along with adaptive decision feedback equalizers
(DFE) and spatial diversity combining have been shown to be
an effective way of communication in such channels
(Stojanovic et al., 1993). However, the long delay spread (often
hundreds of symbols) and rapid time variation of the channel
often makes this approach computationally too complex for
real-time implementations.
Fig. 4. Underwater Acoustic Network (UAN)
IV. Channel Equalization
The error estimate can be split into the minimum achievable
error and the excess error. The excess error component is
strongly affected by rough sea conditions. Through a scattering
function analysis, it was also shown that the rate of change of
the propagation path length of the surface bounced arrival is a
primary contributor to the error. This suggests that the ability to
effectively track the surface bounced arrival may provide an
improved equalizer performance.
0.5 1 1.5 2 2.5 3 3.5
0
2000
4000
6000
8000
10000
Original Audio Signal
Time
Frequency(Hz)
-140
-120
-100
-80
-60
-40
0.5 1 1.5 2 2.5 3 3.5
0
2000
4000
6000
8000
10000
Audio Signal with Flanging
Time
Frequency(Hz)
-140
-120
-100
-80
-60
-40
-20
Fig. 4. The Acoustic signal that shows the effect of signal with/without
Flanging
The demand for high quality underwater acoustic
communications (UAC) arises in many military, scientific and
civilian applications. Many of these involve the wireless
transmission of controlling signals and commands to
autonomous underwater vehicles (AUVs) and underwater
sensors. On the other hand, AUV and sensor receivers have the
limited signal processing capability and only a few
hydrophones due to the size and power limitations. All these
make reliable communications a challenging problem in the
naturally doubly-selective UAC channels. DSSS systems are
recently introduced to underwater communications because of
their capability of resolving multipath and enabling the
collection of delay diversity and channel energy. Similar to
these existing schemes, our proposed approach also has very
low receiver complexity requiring only matched filter operation.
However, different from them, we simultaneously transmit
multiple symbols during each sequence period. Compared with
existing underwater DSSS schemes, our proposed approach
requires shorter channel coherence time and is thus more robust
against moderate channel variation that is inevitable in
underwater scenarios. In addition, our high reliability (HR-)
DSSS scheme also facilitates higher and more flexible rates.
More importantly, the high reliability and high data rate are
achieved with negligible self- and co-channel interference [3].
The research on Underwater Acoustic Networks (UANs) is
attracting attention due to their important underwater
applications for military and commercial purposes. More and
more research interest and efforts are shifting to this area in
recent years. The broad applications of UANs include, but not
limited to [4]:
1. Information exchange among nodes that are within the
range of the network, or outside the network with the
help of, e.g., a gateway, or a switching center. The
primary design goal of communication networks is for
exchanging information. In an UAN, exchanging
information among nodes is one of its essential
applications. An example is that underwater Internet,
in which users can share information without a tether,
will become realistic instead of just a dream, if UANs
are deployed. Another important application is real
time communication with submarines and
autonomous underwater vehicles in network
configurations.
2. Information collection for oceans, lakes, and rivers. For
example, synoptic and cooperative adaptive sampling
of 3D coastal ocean environment was performed by
Odyssey-class AUVs. Such kind of activities could
improve the human ability to observe and predict the
characteristics of ocean/lake/river environment.
3. Surveillance. It includes surveillance, reconnaissance,
targeting, and intrusion detection. By using different
types of sensors, an UAN can achieve more accurate
and classification of low signature targets compared
with traditional surveillance systems.
4. Underwater explorations. Underwater explorations are
difficult for human beings due to the high water
pressure, unpredictable underwater activities and vast
size of unknown area. UANs can help us explore the
underwater world that we are not familiar with.

4. 5. Disaster prevention. By deploying Acoustic Sensor
Networks in remote locations to monitor undersea
activities, ocean-related disaster like a tsunami and
sequence can be warned to coastal areas in real time
when it happens.
6. Compared with the speed of electromagnetic waves,
acoustic signal travels much slower in salty water
(Approximately 1500 m/s, which is 2x105
lower than
the electromagnetic wave counterpart [5]). This
causes another big issue: very long propagation delay.
Additionally, Doppler shift has more significant
impacts subjects to the low velocity of acoustic
propagation in water [6].
V. HIGH RELIABILITY (HR) -DSSS SCHEME
A. Transmitted Signals
In traditional DSSS systems, a single symbol is modulated per
spreading sequence. In a vector form, the ith modulated signal
block is:
(3)
where s(i) represents the ith
transmitted symbol and c the
spreading sequence.
In such a DSSS system was introduced to underwater
communications, where the spreading code is the maximum
length sequence (m-sequence). Here we also employ the
m-sequence as the spreading code.
However, instead of transmitting one symbol per block as in (1),
our HR-DSSS scheme simultaneously modulates multiple
symbols on circularly shifted versions of a m-sequence during
each block. Define the circular shift matrix as:
which introduces a circular shift by 1 upon pre-multiplying an
(M × 1) vector. Accordingly, vector Tj
c is the circularly shifted
m-sequence of j chips. Note that a m-sequence and its circularly
shifted version have the following autocorrelation property:
(5)
Hence, in a flat-fading channel, distinct symbols riding on c and
Tm
c will induce negligible interferences among themselves, as
long as the circular shift m ≥ 1. However, UAC channels are
well known to have extensive multipath. Let τmax denote the
maximum delay spread and Tc as the chip duration.
The multipath essentially spreads over (L + 1) chips, where
In order to separate the delayed multipath components of
neighboring symbols, the circular shift between the sequences
conveying adjacent symbols should be at least (L+1) chips.
Hence, the transmitted signal block in our HRDSSS is given by:
c, (7)
where s(i; j) is the jth transmitted symbol during the ith block,
and the J is the number of superimposed sequences, at most
It is also worth mentioning that Jmax is the maximum number of
symbols that can be simultaneously transmitted when the
distribution and strength of the actual (and possibly sparse)
channel taps are not available at the transmitter. If this
information is also available, then it is possible to increase Jmax
by smartly scheduling the signals. In addition, in a very low rate
system, one can also choose to transmit J (2 ≤ J ≤ Jmax)
symbols to further reduce the inter-symbol interference. Note
that in this design, the only information about the channel
needed at the transmitter is the channel delay spread or an upper
bound on its.
The underwater environment differs from the terrestrial radio
environment, both in terms of its energy costs and channel
propagation phenomena. The underwater channel is
characterized by long propagation times and
frequency-dependent attenuation that is highly affected by the
distance between nodes as well as by the link orientation. Some
of other issues in which UWSNs differ from terrestrial are
limited bandwidth, constrained battery power, more failure of
sensors because of fouling and corrosion, etc. This paper
presents several fundamental key aspects and architectures of
UWSNs, emerging research issues of underwater sensor
networks and exposes the researchers into the networking of
underwater communication devices for exciting ocean
monitoring and exploration applications [7].
Multicarrier modulation: The idea of multicarrier modulation
is to divide the available bandwidth into a large number of
overlapping sub bands, so that the waveform duration for the
symbol at each sub band is long compared to the multipath
spread of the channel [8], [9]. Consequently, inter-symbol
interference may be neglected in each sub band, greatly
simplifying the receiver complexity of channel equalization.
Precisely due to this advantage, multicarrier modulation in the
form of orthogonal frequency division multiplexing (OFDM)
has prevailed in recent broadband wireless radio applications.
However, underwater channels entail large Doppler spread
which introduces significant interference among OFDM
subcarriers. Lacking effective techniques to suppress the
intercarrier interference (ICI), early attempts at applying
OFDM to underwater environments had a very limited success.
VI. Challenges in underwater acoustic sensor networks
Major challenges encountered in the design of underwater
acoustic networks are as follows:
1. The available bandwidth is severely limited.
2. The underwater channel is impaired because of multi-path
and fading.
3. Propagation delay in underwater is five orders of
magnitude higher than in Radio Frequency (RF) terrestrial
channels and variable.
4. High bit error rates and temporary losses of connectivity
(shadow zones) can be experienced.
5. Underwater sensors are characterized by high cost because
of extra protective sheaths needed for sensors and also

5. relatively small number of suppliers (i.e., not much economy of
scale) are available.
6. Battery power is limited and usually batteries cannot be
recharged as solar energy cannot be exploited.
7. Underwater sensors are more prone to failures because of
fouling and corrosion.
The differences between these are as follows:
1. Communication method: Terrestrial sensor networks
employ electromagnetic waves, but in underwater
networks because of the characteristic (large delay, the
long distance of communication) of the network, the
communication relies on physical means like acoustic
sounds to transmit the signal. Traditional RF networks
might not work efficiently in underwater networks.
2. Protocols: Due to distinct network dynamics, existing
communication protocols for pretrial networks are not
suitable for the underwater environment. Low
bandwidth and large latency result in long end to end
delays, and this brings in challenges in reliable data
transfer and traffic congestion control.
Cost: Terrestrial networks are becoming inexpensive due to
advancement in technology, but underwater sensors are still
expensive devices. This is due to the extra protection required
for underwater environment and more complex transceivers
needed.
VII. Differences between underwater sensor networks and
terrestrial networks
Underwater sensor networks are quite different from terrestrial
sensor networks.
Table (I)
Comparison of Acoustic, EM and Optical Waves in Sea Environment
Parameter Acoustic EM OPTICAL
Nominal
speed
1500 m/s 33,333,333 m/s 33,333,33
3 m/s
Power loss ˃0.1dB/m/Hz  28dB/1km/100M
Hz
Prop to
turbidity
Bandwidth KHz MHz 10-150
MHz
Frequency
band
KHz MHz 1014
-1013
Hz
Antenna
size
0.1m 0.5m 0.1m
Effective
range
Km 10m 10-100m
The table above represents the approximate values of nominal
speed, power loss, bandwidth, frequency band, antenna size
and effective range [10].
VIII. Conclusion
In this paper, we considered OFDM as one of the most
important applications for military, scientific and public use;
also we considered the underwater acoustic communications
which have high speed communication, but limited bandwidth,
extended multipath, refractive properties of the medium, rapid
time variation and large Doppler shifts also considered direct
sequence (DSSS) as one of the methods used in underwater
communication techniques. A brief comparison was given in a
table between underwater acoustic network and terrestrial
networks.
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