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Multicarrier Spread Spectrum Communication Scheme for Cruising Sensor Network in Confined Underwater Space

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A cruising sensor network works as an online monitoring system for industrial liquid environments such as oil tanks and nuclear storage ponds. The cruising sensor network consists of a few submerged nodes which can actuate themselves to execute tasks like “cruising.” This paper presents a multicarrier spread spectrum scheme, which is designed for communications between the nodes and the control station. Although underwater acoustic communication has been widely researched due to the growing demands from ocean development and marine research, communication in confined underwater space is an unexplored domain as most research focuses on communication in spacious water areas. The occasions that the cruising sensor network works in are confined. The main distinction in confined underwater spaces is the existence of strong multipath arrivals reflected by the boundaries, which can cause more severe intersymbol interference (ISI). We propose a communication scheme which applies spread spectrum in orthogonal frequency-division multiplexing (OFDM) to address severe frequency selective fading channels. This scheme can be robust in confined underwater channels when coupled with turbo code. The simulation and experimental results prove the feasibility and reliability of this scheme. It is demonstrated that significantly better performance is achieved than that of the conventional OFDM method.
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Research Article
Multicarrier Spread Spectrum Communication Scheme for
Cruising Sensor Network in Confined Underwater Space
Yuan Wang, Zhoumo Zeng, Yibo Li, Jinsheng Zhang, and Shijiu Jin
State Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China
Correspondence should be addressed to Yibo Li; slyb@tju.edu.cn
Received  February ; Revised  June ; Accepted  June ; Published  July 
Academic Editor: Tai hoon Kim
Copyright ©  Yuan Wang et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
A cruising sensor network works as an online monitoring system for industrial liquid environments such as oil tanks and nuclear
storage ponds. e cruising sensor network consists of a few submerged nodes which can actuate themselves to execute tasks like
“cruising.” is paper presents a multicarrier spread spectrum scheme, which is designed for communications between the nodes
and the control station. Although underwater acoustic communication has been widely researched due to the growing demands
from ocean development and marine research, communication in conned underwater space is an unexplored domain as most
research focuses on communication in spacious water areas. e occasions that the cruising sensor network works in are conned.
e main distinction in conned underwater spaces is the existence of strong multipath arrivals reected by the boundaries, which
can cause more severe intersymbol interference (ISI). We propose a communication scheme which applies spread spectrum in
orthogonal frequency-division multiplexing (OFDM) to address severe frequency selective fading channels. is scheme can be
robust in conned underwater channels when coupledwith turbo code. e simulation and experimental results prove the feasibility
and reliability of this scheme. It is demonstrated that signicantly better performance is achieved than that of the conventional
OFDM method.
1. Introduction
e research of this paper is based on cruising sensor network
which takes charge of large oil storage tank online detection.
Cruising sensor network consists of several actuated wireless
sensor nodes. ese wireless sensor nodes are ball-shaped,
carry various types of sensors, and could independently move
aboutinthelargeoilstoragetanks.eadvantageisthat
the sensors could get more detail messages by “cruising” to a
specied place when monitoring the industrial process. e
sketchmapoftheworkingcruisingsensornetworkisshown
in Figure . Cruising sensor network has promising applica-
tion in the online multiparameter detection and supervision
of industrial liquid environments such as oil tanks, industrial
ponds, and reservoirs.
Data exchange between the nodes and the control station
necessitates a reliable and high-speed underwater acoustic
(UWA) communication scheme. Underwater acoustic com-
munication has always been considered to be dicult but
research has made great progress in combating the negative
eects of the underwater channel []. Most existing research
concentrates on spacious environments such as seas and
lakes; however, many of the industrial reservoirs such as
large oil tanks and nuclear storage ponds are conned. e
main diculty to realize robust underwater communication
in such a limited space is the more severe multipath inuence
caused by numerous reections from the boundaries.
To deal with the multipath fading in UWA channels,
traditional methods resort to a decision-feedback equal-
izer (DFE) at the receiver. Although good performance
is achieved, it comes at the price of high computational
complexity,especiallywhenusedinchannelswithalong
delay spread and rapid time variation []. Passive phase
conjugation (PPC) has attracted much attention recently as
it alleviates the burden of computational complexity and
reduces intersymbol interference (ISI); however, it relies on
large arrays [,].Forthisreason,PPCisnotsuitableforour
application on account of power consumption limitationsand
simplicity of the nodes.
Hindawi Publishing Corporation
International Journal of Distributed Sensor Networks
Volume 2014, Article ID 165749, 8 pages
http://dx.doi.org/10.1155/2014/165749
International Journal of Distributed Sensor Networks
F : e sketch map of cruising sensor network working in the
oil tank.
Direct sequence spread spectrum (DSSS) technique has
been demonstrated to be reliable in UWA communication [
]. e DSSS technique not only features a low probability of
interception but also is immune to multipath interference. In
DSSS modulation, the spread spectrum process is achieved
by multiplying the information signal with a spreading
code. Due to the strong autocorrelation property of the
spreading sequence, multiple arrivals can be separated via
the despreading operation which suppresses the multipath
interference. Researchers have done a great deal of work
to enhance the performance of a DSSS system. Stojanovic
andFreitagappliedadaptivechannelequalizationtosuppress
ISI []. Sozer et al. applied a RAKE receiver to combine
multipath arrivals []. In T. C. Yang and W. Yang’s research,
DSSS was coupled with passive-phase conjugation to achieve
communication with low SNR input signals []. However,
due to the conict between the spread spectrum process and
a limited available bandwidth of UWA channels, the main
drawback of DSSS technique is the bandwidth eciency,
which is lower than . bit/s/Hz []. erefore, DSSS systems
aremostcommonlyusedinlow-speedUWAcommunication
where the data rates are oen in the order of hundreds of
bps.
Orthogonal frequency-division multiplexing (OFDM) is
a prevailing technique used in wireless communication [,
]. e main idea of OFDM is to divide the bandwidth
into many subchannels and transmit relatively low-speed data
streams in a parallel way over these subchannels, each of
which experiences frequency-at fading. erefore OFDM
performs robustly in multipath environments with a high
spectral eciency []. Another advantage of OFDM systems
is low complexity. OFDM modulation and demodulation can
be easily implemented using fast Fourier transforms (FFT).
In Frassati et al.’s research, an experiment was conducted to
compare the performances of OFDM and DSSS in shallow
waters of the Mediterranean Sea, and the result showed that
OFDM outperforms DSSS [].
In order to decrease ISI, one method is to split the
bandwidth into more subchannels in the OFDM system.
However, this method also introduces some negative eects,
for example, a larger implementation complexity and more
sensitivity to phase noise and frequency oset, as well as
an increased peak-to-average power ratio. Another method
is to insert a cyclic prex (CP) in front of each OFDM
block. Although using a cyclic prex (CP) can cancel out
most ISI and intercarrier interference (ICI), the cyclic prex
may be undesirably long where there is a long time spread
[]. In addition, the attenuation of multipath arrivals is
very weak in conned underwater space. e strong mul-
tipath interference calls for a more powerful antimultipath
scheme.
In this study, we propose an SS-OFDM scheme, which
combines spread spectrum and OFDM, to overcome the
severe interference of ISI in conned underwater channels.
In the proposed scheme, the data sequence undergoes the
procedure of spectrum spreading before OFDM modula-
tion; thus, the residual multipath interference is signi-
cantly suppressed. e working process and principle of SS-
OFDM are addressed. We compare the proposed scheme
with conventional OFDM schemes and demonstrate superior
antimultipath performance based on the simulation analysis
and experimental results.
is paper is organized as follows. Section introduces
the system model and the mathematical description of
the antimultipath performance of OFDM and SS-OFDM.
Section presents the simulation results. Section shows the
experimental design and results. Section summarizes the
paper.
2. System Description and Analysis
In this section, we develop an SS-OFDM system model for
communication in conned underwater channels. en, we
introduce the transmitter structure in detail and analyze the
antimultipath performance of an SS-OFDM system.
2.1. System Description. In our proposed scheme, turbo
code, which is known as a strong channel code, is adopted
to enhance the system performance. e basic principle
and procedure of SS-COFDM (coded OFDM) are given in
Figure .
e source signal is turbo-encoded, interleaved, and then
mapped into a QPSK constellation (the most commonly used
modulation mode in OFDM). e data sequence is then
converted into parallel data streams, as for conventional
OFDM systems. For SS-OFDM, the next step is to replicate
each stream to copies. e signal will enter the spread
spectrumprocesswhichisshowninFigure.is equal to the
length of the spreading code—a pseudonoise (PN) sequence,
which is multiplied with each of these copies. Now there are
×subcarriers; that is, the SS-OFDM symbol length is
×.efollowingprocedureisthesameasaconventional
OFDM system.
Let 𝑘=
𝑐+/𝑏for =0,...,×−1be the ×
subcarrier frequencies, where 𝑐is the carrier frequency and
𝑏is the SS-OFDM block duration.
International Journal of Distributed Sensor Networks
Encoded
source
signal
QPSK
mapping
Serial-to-
parallel Copier Spread
spectrum
Pilot
insert
Oversam
pling
IFFT
Cyclic
prefx
Parallel-
to-serial
Channel
decode
Sampling
and
decision
QPSK
demappi
ng
Parallel-
to-serial
Desprea
ding
Channel
estimation
Conned
UWA
channel
D/A
A/D
Carrier
modulati
on
Downsa
mpling
FFT
CP
removal
Serial-to-
parallel
Carrier
demodul
ation
F : e framework of the SS-COFDM communication system.
Source data Serial-to
-parallel
Copier
Copier
Copier c0
c0
cos(2𝜋f
N×(M−1)t) Σ
cN−1
cN−1
cos(2𝜋f
N×M−1t)
cos(2𝜋f
0t)
···
···
···
···
×
×
××
××
×
×
cos(2𝜋f
N−1 t)
x0
xM−1
F:ProcessofspreadspectruminSS-OFDMatthetransmitter.
e orthogonal basis functions are
𝑘()=
𝑗2𝜋𝑓𝑘𝑡0≤≤
𝑏,
0otherwise.()
And the time domain of the th block of an SS-OFDM signal
can be written as
()=𝑁−1
𝑘=0𝑟,0𝑘𝑘()+𝑁−1
𝑘=0𝑟,1𝑘𝑘+𝑁 ()
+⋅⋅⋅+𝑁−1
𝑘=0𝑟,𝑀−1𝑘𝑘+(𝑀−1)∗𝑁 (),()
International Journal of Distributed Sensor Networks
where {𝑟,0,...,𝑟,𝑀−1}are the QPSK symbols transmitted on
the th subcarrier in the th block and {0,...,𝑁−1}are the
symbols of the spread spectrum sequence.
In the demodulation process, based on the orthogonality
between the subcarriers, the result for the th subcarrier for
the th block (assuming 0≤≤−1)isasfollows:
𝑟,𝑙 =1
𝑏𝑇𝑏
0()
𝑙()
=1
𝑏𝑇𝑏
0−𝑗2𝜋𝑓𝑙𝑡𝑁−1
𝑘=0𝑟,0𝑘𝑗2𝜋𝑓𝑘𝑡
+⋅⋅⋅+1
𝑏𝑇𝑏
0−𝑗2𝜋𝑓𝑙𝑡𝑁−1
𝑘=0𝑟,𝑀−1𝑘𝑗2𝜋𝑓𝑘+(𝑀−1)∗𝑁𝑡
=1
𝑏𝑟,0
𝑁−1
𝑘=0𝑘𝑇𝑏
0𝑗2𝜋(𝑓𝑘−𝑓𝑙)𝑡
+⋅⋅⋅+1
𝑏𝑟,𝑀−1
𝑁−1
𝑘=0𝑘𝑇𝑏
0𝑗2𝜋(𝑓𝑘+(𝑀−1)∗𝑁−𝑓𝑙)𝑡
=𝑟,0𝑙.
()
e demodulation process in () can be extended to all
the subcarriers. Aer demodulation, the received array is
𝑟,00,𝑟,01,...,𝑟,0𝑁−1,
𝑟,10,𝑟,11,...,𝑟,1𝑁−1,
⋅⋅⋅
𝑟,𝑀−10,𝑟,𝑀−11,...,𝑟,𝑀−1𝑁−1
.()
en, aer the despreading process, we obtain the data
sequence {𝑟,1,𝑟,2,...,𝑟,𝑀}which is transmitted by the th
block of the SS-OFDM signal.
2.2. Antimultipath Performance Analysis. In this section,
we provide the antimultipath performance analysis of the
proposed SS-OFDM scheme. In (),withoutlossofgenerality,
we only consider the rst term. e transmitted symbol
sequence is 𝑟,0{0,1,...,𝑁−1}.etimedomainexpression
canbewrittenas
𝑟,0 ()=𝑟,0
𝑁−1
𝑘=0𝑘exp 2𝑘 0𝑏.()
We consider two types of possible multipath interferences
that the conventional OFDM system is not able to eliminate in
conned underwater space. e rst is interference caused by
echoes exceeding the guard time and the second is frequency
selective fading when the symbol duration of each subcarrier
is not long enough.
In order to facilitate this discussion, we consider the
transmission of the signal over a two-path channel. Ignoring
the Doppler shi, the received signal can be written as
()=𝑟,0 ()+𝑟,0 (−)+𝑟−1,0 +𝑏+𝑔−,
()
where ,,and𝑔are time delay, attenuation, and duration
of the guard interval, respectively. Consider the following:
()=𝑟,0
𝑁−1
𝑘=0𝑘exp 2𝑘
+𝑟,0
𝑁−1
𝑘=0𝑘exp 2𝑘(−)
+𝑟−1,0
𝑁−1
𝑘=0𝑘exp 2𝑘+𝑏+𝑔−.
()
In (), the latter two terms represent the two types of
multipath interferences mentioned above. In the receiver, the
output of the th subcarrier of the th block can be written as
𝑟,𝑙 =𝑟,0𝑙+𝑟,0
𝑁−1
𝑘=0𝑘−𝑗2𝜋𝑓𝑘𝜏𝑇
0𝑗2𝜋(𝑓𝑘−𝑓𝑙)𝑡
+𝑟−1,0
𝑁−1
𝑘=0𝑘𝑗2𝜋𝑓𝑘(𝑇𝑏+𝑇𝑔−𝜏) 𝑇
0𝑗2𝜋(𝑓𝑘−𝑓𝑙)𝑡. ()
In this case, orthogonality between the subcarriers is not
valid, so the latter two interference terms are included in the
expression of 𝑟,𝑙 which can be simplied to
𝑟,𝑙 =𝑟,0𝑙+𝑟,0
𝑁−1
𝑘=0𝑘𝑘,𝑙 ()+𝑟−1,0
𝑁−1
𝑘=0𝑘𝑘,𝑙 ()
=𝑟,0𝑙+𝑁−1
𝑘=0𝑘𝑘,𝑙 ().()
We obtain the received sequence
𝑟,00+𝑁−1
𝑘=0𝑘𝑘,𝑙 (),𝑟,01+𝑁−1
𝑘=0𝑘𝑘,𝑙 (),...,𝑟,0𝑁−1
+𝑁−1
𝑘=0𝑘𝑘,𝑙 ().
()
e receiver then multiplies the received sequence by the
spreading sequence {0,1,...,𝑁−1}andsincethereisgood
autocorrelation, the interference terms can be minimized.
By analyzing the antimultipath performance of SS-
OFDM, we can conclude that the spread spectrum process
eliminates the residual ISI that a conventional OFDM system
is not able to address.
3. Simulation Results
In this section, we present simulation results in order to
validate the performance of OFDM and SS-OFDM in the
theoretical analysis.
International Journal of Distributed Sensor Networks
T : e system parameters of OFDM and SS-OFDM in the simulation.
Communication mode Eective subcarrier number Length of PN sequence Guard interval Data rate (kbps)
OFDM  ×
𝑔=41ms .
OFDM  ×
𝑔=82ms .
OFDM  ×
𝑔=102.5ms .
SS-OFDM  𝑔=8.2ms .
SS-OFDM  𝑔=8.2ms .
3.1. Channel Model. Webeginbyestablishinganacoustic
channel suitable for conned underwater space. Usually,
UWA channel simulation studies are modeled on the sea. In
such a UWA channel, complex time-varying oceanographic
processes and ocean surface waves oen produce a channel
with short coherence time [], so channel variation is an
important issue which must be taken into account. However
in oil storage tanks, the liquid is in a stationary state. us we
refer to a time-invariant response acoustic channel proposed
in [].
In the model, each multipath acts as a low-pass lter. e
transfer function of the th propagation path is
𝑝= Γ𝑝
𝑝,,()
where Γ𝑝is the cumulative reection coecient along the th
path, 𝑝is the length of the th path, and is the frequency
of the signal. Consider
,=0𝑘𝑙,()
where 0is a scaling constant, is the spreading factor, and
()is the absorption coecient.
e overall channel response is
()=
𝑝𝑗(𝜃𝑝+2𝜋𝑓𝐷𝑝𝑡)𝑝𝑝, ()
where 𝑝()is the inverse Fourier transform of 𝑝()and 𝑝,
𝑝,and𝐷𝑝 are delay, phase rotation, and Doppler frequency
of each path, respectively.
3.2. Simulation Results. Our considered channel for the
simulation does not include the Doppler shi, and the lengths
andrelativedelaysofmultiplepropagationpathsinthemodel
arecalculatedfromthegeometryoftheoiltank.ereare
totally  paths in the channel. e maximum time delay of
the channel we propose is  ms.
We provide the BER analysis of OFDM and SS-OFDM
in the channel. We set the number of eective subcarriers to
 in OFDM, the carrier frequency is  kHz, and sample
frequencyiskHz.QPSKmodulationisusedoneach
carrier. e IFFT size is , the block duration is ms,
and each subcarrier is spaced by . Hz. In SS-OFDM,
thenumberofeectivesubcarriersdecreasesbecauseofthe
spread spectrum process. We adopt dierent lengths of cyclic
prexinOFDManddierentlengthsofPNsequenceinSS-
OFDM to analyze the system performance. e parameters
are shown in Table .
0 5 10 15 20
SNR (dB)
BER
SS-OFDM, PN length: 3
SS-OFDM, PN length: 7
OFDM, Ng = 102.5 ms
OFDM, Ng = 82 ms
OFDM, Ng = 41 ms
100
10−1
10−2
10−3
F : BER performance of SS-OFDM and OFDM.
Figure shows performance results of the SS-OFDM and
OFDM system. We can see the BER decreases as the cyclic
prex elongates in OFDM system. To address the long time
delay of the channel, the length of the cyclic prex could be
longer than  ms. Correspondingly, SS-OFDM shows better
performance in this multipath fading channel with the cyclic
prex length only . ms. e BER decreases as the length of
PN sequence increases in SS-OFDM; however, the data rate
also decreases.
4. The Experiment
4.1. Experimental Environment. e experiment was con-
ducted in the quadrate tank in the laboratory, and the
side length of the tank is .m. Since no sound absorption
measure is adopted, this is a typical conned underwater
channel with severe multipath fading. e transmitter and
receiver were deployed in opposite corners of the tank.
To test the channel, a sine signal of  kHz frequency
lasting  cycles was sent, and the received signal is shown
in Figure . e direct signal is enclosed by the rectangle
and the amplitude in the picture is a relative value. We can
see that the channel condition is particularly harsh in the
test, the multipath arrivals decay slightly in the rst  ms we
International Journal of Distributed Sensor Networks
0.24
0.238
0.236
0.234
0.232
0.23
0.228
0.226
0.224
Amplitude
Direct signal
0.558321 0.56 0.57 0.572 0.574 0.576
0.562 0.564 0.566 0.568
Time (s)
0.57888
F : Channel condition of the tank in the laboratory.
0.24
0.238
0.236
0.234
0.232
0.230
0.228
0.226
0.224
Amplitude
Direct signal
0.558967 0.56 0.561 0.562 0.563 0.564
Time (s)
0.565 0.566 0.566423
F : Front  ms received signal.
intercept, and the multipath signal next to the direct signal
nearly has the same amplitude with the direct signal. We can
see more details in Figure which displays a  ms capture.
e multipath arrivals are numerous and intensive with large
amplitudes.
en we measured the channel impulse response by
transmitting a  ms LFM signal with frequency swept
from  kHz to  kHz. By calculating the cross-correlation
functions between the received signal and the original LFM
signal, the measured channel response can be shown in
Figure .emaximumtimedelayismorethanms.
4.2. Experimental Results and Analysis. At the transmitter,
we set the sample frequency  KHz to make the carrier
frequencykHz,whichisalsotheresonantfrequencyofthe
transducers. e OFDM modulation is realized by an IFFT
with a size =2
14;thus,thesymboldurationofOFDMis
OFDM =32.8ms. e subcarrier spacing is  = 1/OFDM =
30.5Hz.enumberofeectivesubcarriersis,andthe
bandwidth of OFDM signal is =4.9kHz.
We evaluate the OFDM system performance with dif-
ferent lengths of cyclic prex and the results are shown in
Table . e BER reduces as the guard interval length is
increased, but the system performance is unsatisfactory even
with a guard interval of . ms, the same length as the symbol
duration of OFDM.
We can enhance the IFFT size of the OFDM system in
order to increase the time duration of each subcarrier. e
length of the guard interval 𝑔is always equal to OFDM.In
this set of experiments, the eective subcarrier is unchanged
becauseweareonlyconcernedabouttheperformanceof
multipath resistance and take no account of data rate. ree
0 10 20 30 40 50 60 70 80
0
20
40
60
80
100
Time (ms)
Relative amplitude
−20
−40
−60
−80
−100
F : Channel response in time domain.
sets of data are compared in Table .esystemperformance
improves when the bandwidth is split into more channels and
the length of cyclic prex is increased beyond the maximum
time delay. However, the transmission eciency is becoming
unacceptably low. Moreover, the sensitivity to Doppler shi
interference increases as the subcarrier spacing decreases.
e SS-OFDM scheme has similar parameters to the
experiments in Table . e dierence is that the bandwidth
iswidenedbythespreadspectrumsequence.Weuse
sequence with length of  as the spread spectrum sequence.
We compare the performance of the SS-OFDM with dierent
International Journal of Distributed Sensor Networks
T : Performance of OFDM scheme with dierent lengths of guard interval.
Communication mode Subcarrier number Guard interval Data rate (kbps) BER (%)
OFDM  𝑔=
OFDM/4=8.2ms . .
OFDM  𝑔=
OFDM/2=16.4ms . .
OFDM  𝑔=
OFDM =32.8ms . .
T : Performance of OFDM scheme with dierent IFFT sizes.
Communication mode IFFT size Guard interval Subcarrier spacing (Hz) BER (%)
OFDM 214 𝑔=
OFDM =32.8ms . .
OFDM 215 𝑔=
OFDM =65.6ms . .
OFDM 216 𝑔=
OFDM =131.2ms . .
T : Performance of SS-OFDM scheme with dierent lengths of guard interval.
Communication mode Subcarrier number Length of sequence Guard interval Data rate (kbps) BER (%)
SS-OFDM   𝑔=
OFDM/4=8.2ms . .
SS-OFDM   𝑔=
OFDM/2=16.4ms . .
SS-OFDM   𝑔=3
OFDM/4=24.6ms . .
SS-OFDM   𝑔=
OFDM =32.8ms . .
SS-OFDM  𝑔=
OFDM/2=16.4ms . .
SS-OFDM  𝑔=
OFDM/2=16.4ms . .
T : Performance of SS-COFDM scheme with dierent subcarrier numbers.
Communication mode Subcarrier number Guard interval Data rate (kbps) BER (%)
SS-COFDM  𝑔=
OFDM/2=16.4ms .
SS-COFDM  𝑔=
OFDM/2=16.4ms .
SS-COFDM  𝑔=
OFDM/2=16.4ms . .
lengths of cyclic prex. e experimental result is shown in
Table .
We can compare the experimental results with Table
and notice that much better performance is achieved with
the same parameter settings in the SS-OFDM system. When
𝑔is equal to OFDM/2,3OFDM/4,andOFDM,theBER
performance is nearly the same. We can consider that the
guard interval OFDM/2 is enough for SS-OFDM in the
experiment, which saves the transmission eciency greatly
compared to the OFDM scheme. At the end of Table ,the
SS-OFDM system performance degrades as the length of
sequence shortens and the number of eective subcarriers
increases.
In order to further improve the system performance,
turbo code, which is a strong channel coding method, is
adoptedtoconstructSS-COFDMschemeandcomparedwith
the last two schemes. In a turbo coding system, the data rate is
halved because the coding rate is 1/2. e IFFT size is 214,and
the length of sequence is . e experimental results are
shown in Table . e system is error-free when the data rates
are.and.kbps,althoughthelengthofcyclicprexis
only .ms which is much shorter than the maximum time
delay of the channel. An acceptably small BER around 10−4
emerges when data rate reaches .kbps.
5. Conclusions
In this paper, we focused on building a reliable and high-
speed communication scheme in conned underwater envi-
ronments due to the need for application of cruising sen-
sors network in online detection of oil tanks. Conventional
OFDM scheme performs inferiorly in this environment, and
we investigated SS-OFDM, the combination of DSSS and
OFDM, and better performance was achieved when turbo
code was employed simultaneously. We were able to demon-
strate error-free transmission at data rate up to . kbps
and low BER at .kbps in the experiment. In addition,
this scheme oers convenient method for multiple users to
access the channel simultaneously and asynchronously, an
important research direction for the future.
Conflict of Interests
e authors declare that they do not have any commercial
or associative interest that represents a conict of interests in
connection with the paper they submitted.
Acknowledgment
is work has been supported by the National Natural
Science Foundation of China under Grant no.  and
International Journal of Distributed Sensor Networks
Tianjin Research Program of Application Foundation and
Advanced Technology (JCYBJC).
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The past 30 years have seen a growing interest in underwater acoustic communications because of its applications in marine research, oceanography, marine commercial operations, the offshore oil industry and defense. Continued research over the years has resulted in improved performance and robustness as compared to the initial communication systems. In this paper, we aim to provide an overview of the key developments in point-to-point communication techniques as well as underwater networking protocols since the beginning of this decade. We also provide an insight into some of the open problems and challenges facing researchers in this field in the near future.
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In this paper we propose a novel method for communication over underwater acoustic channels that exhibit simultaneously large delay spread and Doppler spread, such as those found in the surf zone. In particular, we propose a coded pulse-shaped multicarrier scheme that converts the doubly dispersive channel into an inter-carrier interference (ICI) channel with small ICI spread. The resulting ICI is mitigated using a soft noncoherent equalizer that leverages sparsity in the delay-power profile to generate near-optimal bit estimates with low complexity. The noncoherent equalizer uses a delay-power-profile estimate (rather than a channel estimate) which is obtained from pilots. Numerical simulations with surf-zone-like channels demonstrate performance close to genie-aided bounds.