IEEE Communications Magazine - June 2017 - page 200

IEEE Communications Magazine • June 2017
198
0163-6804/17/$25.00 © 2017 IEEE
A
bstract
In warm shallow waters, the ambient noise
process is found to be impulsive. This phenom-
enon is attributed to the collective snaps creat-
ed by snapping shrimp colonies inhabiting such
regions. Each snap essentially creates a pressure
wave, and the resulting noise process dominates
the acoustic spectrum at medium-to-high fre-
quencies. Consequently, if not addressed,
snap-
ping shrimp noise
is severely detrimental to the
performance of an
acoustic
communication sys-
tem operating nearby. This article briefly summa-
rizes and addresses the problems faced during
acoustic communication in snapping shrimp
noise. We discuss how the noise process can be
characterized by a certain statistical model based
on the symmetric
a
-stable (S
a
S) family of distri-
butions. Within the framework of this model,
we highlight problems and the corresponding
solutions faced in
various stages
of digital com-
munication system design. Both single and multi-
carrier systems are commented on. The resulting
schemes are robust to outliers and offer excel-
lent error performance in comparison to conven-
tional methods in impulsive noise.
I
ntroduction
The snapping shrimp inhabits warm shallow
underwater regions around the world. These
small critters live in large populations and are
immediately distinguishable due to their asym-
metrical front claws [1]. This physical attribute
allows them to generate snaps (sudden surges
in acoustic pressure) which are used for hunting
prey and communicating. A typical snap, inclu-
sive of the reverberations that follow, tends to
last over a few milliseconds with peak-to-peak
source levels recorded to be as high as 190 dB
re 1
m
Pa at 1 m [1, 2]. The collective snaps of
a snapping shrimp colony prove to be a chal-
lenge for underwater acoustic system designers
[3]. In fact, for frequencies over 2 kHz, snapping
shrimp noise is known to dominate the acoustic
spectrum [4]. A noise process that depicts sud-
den snaps (or impulses) is rightly termed impul-
sive noise.
In this article, we highlight the quandary a
communication system designer faces in the pres-
ence of snapping shrimp noise. We cover recent
advances in the understanding of the noise pro-
cess and summarize new techniques for robust
digital communication in such scenarios.
A
mplitude
S
tatistics of
S
napping
S
hrimp
N
oise
In Fig. 1, recorded samples of dynamic pressure for
a snapping shrimp colony are presented. This data
set was recorded by the Acoustic Research Lab-
oratory (ARL) in Singapore. The snaps are clearly
visible, and therefore the noise process is indeed
impulsive. A first step for any communications
engineer is to find a suitable model that depicts the
statistics of the ambient noise process in question.
In the literature, impulsive noise models are typical-
ly based on heavy-tailed distributions as they assign
large probability to outliers (or extreme values). To
highlight this, we present the empirical
amplitude
distribution
of the noise realization in Fig. 1. We
also show the fits offered by the Gaussian and sym-
metric
a
-stable (S
a
S) probability density functions
(PDFs) under maximum-likelihood (ML) parame-
ter estimation [5]. The well-known Gaussian PDF
has light (exponential) tails and is clearly
unable
to track the empirical PDF efficiently. As observed
in Fig. 1, the tails of the Gaussian curve fall rather
quickly. On the other hand, the heavy-tailed S
a
S
PDF tracks the empirical distribution fairly well. This
observation is substantiated further in the literature
via formal statistical tests [2, 3].
PDFs belonging to the S
a
S family are unimodal
and symmetric (around zero). They also exhib-
it interesting limiting and stability properties [6].
In fact, the zero-mean Gaussian distribution is a
member of the S
a
S family. It is well known that
for a Gaussian input, the output distribution is also
Gaussian under any linear transformation [7]. This
result extends to S
a
S inputs as well and is essen-
tially the
stability property
that is uniquely associ-
ated with this class of distributions. An S
a
S PDF
depends on two parameters: the
characteristic
exponent
a 
(0, 2], which controls the heaviness
of the tails, and the
scale
d 
R
+
[6]. Consequent-
ly, the distribution can be denoted by the abridged
notation
S
(
a
,
d
) [8]. The lower the value of
a
, the
heavier the tails of the distribution. Moreover, for
a
= 2, the S
a
S distribution is zero-mean Gauss-
ian with variance 2
d
2
, that is,
S
(2,
d
)
d
=
N
(0, 2
d
2
),
where
d
= implies equality in distribution. With the
exception of the Gaussian case, all members of
the S
a
S family are heavy-tailed (algebraic-tailed)
distributions [6]. Going back to Fig. 1, the zero-
mean Gaussian and S
a
S fits correspond to
N
(0,
2(24.76)
2
)and
S
(1.51, 12.09), respectively. Note
that the Gaussian distribution tries to compensate
for heavier tails by increasing the scale.
Ambient Noise in Warm Shallow Waters:
A Communications Perspective
Ahmed Mahmood and Mandar Chitre
A
ccepted
from
O
pen
C
all
The authors summarize
and address the problems
faced during acoustic
communication in snap-
ping shrimp noise. They
discuss how the noise
process can be character-
ized by a certain statistical
model based on the
symmetric
a
-stable (S
a
S)
family of distributions.
Within the framework of
this model, they highlight
problems and the corre-
sponding solutions faced
in various stages of digital
communication system
design.
The authors are with the National University of Singapore.
Digital Object Identifier:
10.1109/MCOM.2017.1500617
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