Channel Characterization of EM Waves Propagation at MHz Frequency through SeaWater

Introduction Related Work and Motivation Contribution-I Contribution-II Concluding Remarks
Z14040024
PhD Thesis Defense
Channel Characterization of EM Waves
Propagation at MHz Frequency through SeaWater
Muhammad Tahir
School of Electronics and Information Engineering,
Changchun University of Science and Technology,
Changchun,P.R.China.
Advisor Dr.Piao Yan Underwater Communication Using EM Waves PhD Thesis Defense 1 / 45

Outline
1 Introduction
2 Related Work and Motivation
3 Contribution-I
4 Contribution-II
5 Concluding Remarks

Section 1
Introduction

Background Perspective
On June 1, 2015, China faced deadliest maritime disaster in its
history when a ship was traveling with 454 people on-board in
Yangtze river
About 442 people died and only 12 had been rescued. After
facing gusts over 118 km/h, ship sank approximately 15 meters in
deep waters
It took about 12 hours to provide full-sized rescue support to ship
and even 30 days to identify accurate number of rescued people
Reason:
Delay in notiﬁcation of thunderstorm to technical staff of ship
Require:
Short range (R) and high bandwidth (MHz) minimum latency
underwater EM communication system

Multiple Communication Technologies in Underwater
Acoustic:Suitable
for deep waters
with maximum
latency
Optical: Not
suitable for dirty
water and
requires LOS
EM: Suitable for
shallow/deep
and can cross
Sea/Air Image taken from NTNU work

Underwater EM Communication
Underwater EM were investigated with passionate intensity in last
century up until 1970s
Range restricted by α (dB/m) were not helpful for signiﬁcant
breakthrough along with absence of digital revolution
Communicating using EM waves ( 3 ∗ 107m/s) in SeaWater
(Underwater)at higher data rate (High Bandwidth)for short range
(R) has many applications like pinpointing submerged targets
during naval operations

EM Waves in Underwater(SeaWater)
Conduction
current and
Near-Field
region
Displacement
current and
Far-Field region
Image taken from Al-Shammaa work

Mathematical Representation of EM Waves
Propagation in SeaWater
Maxwell’s equations can predict propagation of EM waves
travelling in conducting medium(SeaWater); described in terms of
electric ﬁeld strength Ex (V/m) and magnetic ﬁeld strength Hy
(C/m) as:
Ex = Eoe(jωt−γz)
(1)
Hy = Hoe(jωt−γz)
(2)
Propagation constant (γ) expressed in terms of permittivity (F/m)
, permeability µ (H/m) and conductivity σ (S/m):
γ = jω µ − j(σµ/ω) = α + jβ (3)

Wireless Underwater Sensor Networks:An Overview
(I)
WUSNs consists of
devices; such as sink
nodes deployed above
SeaWater
Hence,communication
between underwater
sensors (Static or
Mobile),AUV and above
water sinks should also be
considered.

Wireless Underwater Sensor Networks:An Overview
(II)
Hostile SeaWater environments prevent direct use of most, if not
all, existing wireless communication and networking solutions, due
to extremely high PLdB and small R (meters)
WUSNs have number of promising applications includes:
(1) Environmental monitoring
(2) Infrastructure monitoring
(3) Location determination

Section 2
Related Work and Motivation

WUSNs:Communication Perspective
Efﬁcient communication among nodes in WUSNs; most
fundamental and critical issue
ACOMM most versatile and widely used technique in SeaWater
due to lower α(dB/m)
Using EM waves in RF range does not work well in SeaWater due
to conducting nature
However, EM can work in SeaWater for short R (m)with much faster
Vp (m/Sec)
FSO generally limited to very short R (m) because of severe
SeaWater α(dB/m) and strong back-scatter from suspending
particles
Even clearest water has 1000 times α(dB/m) of clear air

Categories of WUSNs:Application and Deployment
Perspective
Applications:
WUSNs for long-term non-time critical aquatic monitoring
applications (such as oceanographic data collection, pollution
monitoring/detection, and offshore oil/gas ﬁeld monitoring)
WUSNs for short term time-critical aquatic exploration applications
(such as submarine detection, loss treasure discovery, and
hurricane disaster recovery)
Deployment:
Mobile UWSNs for long-term non-time critical applications
(M-LT-UWSNs)
Static UWSNs for long term non-time critical applications
(S-LT-UWSNs)
mobile UWSNs for short-term time-critical applications
(M-ST-UWSNs)

Acoustic Communication in SeaWater
Propagation velocity
Multipath
Ambient noise
Path Loss
Geometric spreading
Absorptive loss
Scattering loss

EM Communication in SeaWater
α (dB/m)for EM
propagation in freshwater
α = σ/2( (µ/ )) (4)
α (dB/m)for SeaWater
about two orders higher
than that of freshwater
α = (π ∗ f/µ ∗ σ) (5)

Optical Communication in SeaWater
Using OCOMM obviously has a big advantage in C (bps);can
potentially exceed 1 Gbps
Couple of disadvantages for OCOMM in SeaWater
1:Firstly, optical signals rapidly absorb in SeaWater
2:Secondly, optical scattering caused by suspending particles
3:Thirdly, high level of ambient light in upper part of SeaWater
column is another adverse effect for using OCOMM

SeaWater Surveillance and Target Tracking
ACOMM for WUSNs based Surveillance Techniques
EM-Based WUSNs Surveillance Techniques
Target Detection Considerations
Target Classiﬁcation Considerations
Target Tracking Considerations
EM-Based Node Topology Design Considerations
EM-Based Submarine Communication

Generic WUSNs 3-D Architecture
Image taken from Ian F Akyildiz work
Advantages of using EM
communication in
SeaWater:
EM signals can be used
for coastal monitoring
applications
Smooth transition
through Sea/Air
EM waves can tolerate
tidal waves, ambient
noise, man-made noise
EM signals can work in
dirty water
High B (MHz) can be
achieved

Interesting experimental work by Al-Shammaa and
J.Lucas
Image taken from Al-Shammaa work
Far-ﬁeld behavior of EM
waves in SeaWater;for
MHz range has been
published
Results show large signal
reduction at distances less
than 5 m; with relatively
less additional α
(dB/m)from there on to 100
(m)

Motivation:E-Navigation Revolution
E-navigation;bringing existing and new technologies together to
improve safety of navigation
Challenge for international maritime organization (IMO) will be to
produce uniﬁed strategy for integration
Develop systems to meet requirements through S-mode
Concept of S-mode is default setting to bring all inputs like
radar,charts,positioning to bring on one platform
E-navigation will be used for monitoring all kinds of activities in
ocean’s

Section 3
Contribution-I

Summary of Contribution-I
In this section we present characteristics of EM(TEM) waves
propagation at (1-20)MHz frequency through SeaWater based on
real time data of SeaWater T (Co) and S (ppt) for averaged
decades from (1955-2012) up to 5500m
We also estimated SeaWater σ (S/m), r (F/m) (using Stogrynâs
Model),α (Np/m) (using Helmholtz Model),Z (Ohms),fT (Hz),vp
(m/Sec),τ (Sec) and Pr (dBm) (using Max-well’s
Equations,Lambert’s Law and Friis Law)
Analysis of these parameters against multiple depths of SeaWater
and frequencies shows that we can not assume constant σ (S/m)
(4), r (F/m) (81),fT (Hz) (888MHz),vp (m/Sec) (3.33*107) and τ
(Sec) (8.2*10−12) for SeaWater

Mathematical Modeling of SeaWater PLEM
For SeaWater PR(dBm) includes both PLo and PLEMuw; represents
absorption loss
PR(dBm) = PT(dBm) + GT(dB) + GR(dB) − PLEM(dB) (6)
PLEM(dB) = PLo(dB) + PLEMuw(dB) (7)
PLEMuw(dB) = PLα(dB) + PLβ(dB) (8)
PLα(dB) = 20log(eαR
) (9)
PLβ(dB) = 20log(λo/λ) (10)

Device for Propagation of EM Waves in
SeaWater:drayleigh (m) Paradox
Relationship between Ps (dBm) and
PT (dBm) for SeaWater given as:
PT = Ps(σD/σw + σD) (11)
Tx encapsulated in insulator that
contains freshwater with σ
=0.000001 S/m
Length of insulation box
approximately equals to drayleigh (m)

Conductivity for EM Signals vs SeaWater Depth
While reading
literature we
discovered that
whether it is
experimental or
theoretical; σ
(S/m) lies
approximately
near to 4S/m
Image taken from IJCS

Real Permittivity for EM Signals vs SeaWater Depth
Similarly in
literature ; r
contributes in
absorbing
energy is
approximately
81

Simulation Parameters
Table: Simulation Parameters
T(Co) and S(ppt) 1955 − 2012 Averaged data (Averaged Decades)
Oceans 5 Indian,Paciﬁc,Southern,Atlantic, Arctic
OceanDepth upto ≈ 5500m Average depth 3500m and 101 Depth Points
Latitude 0 − ±90 North or South of Equator
Longitude 0 − ±180 East or West of Greenwich
VerticalPoints 1 − 101 Seawater Depth up to 5500m divided into 101 depth points
HorizentalPoints 1 − 41088 Seawater Latitude and Longitude divided into 41088 points
σdw ≈ 0.000001 S/m Conductivity of Deionised Water
Tdw 20 Co Temperature of Deionised Water
Sdw ≈ 0 ppt Salinity of Deionised Water
τdw 8.2 ∗ (10)(−12)sec Relaxation Time for Deionised Water
o 81 Permittivity of Deionised Water at Low Frequencies
∞ 4 Permittivity of Deionised Water at High Frequencies
vdw 3.33 ∗ (10)7 m/sec Velocity of Propagation for Deionised Water
f (1-20) MHz Frequency Range for Transmission
Ps (-60 -30) dBm Source Power for Transmission
Gt,r (dipole) (1-10) dB Gain for Both Transmitter and Receiver
drayleigh ≤ 5 meters Rayleigh Distance
Zo ≈ 377Ohms Free Space Characteristics Impedance
fT ≈ 888MHz Transition Frequency

Attenuation for EM Signals vs SeaWater Depth
α (dB/m) helps
to estimate Lα
(dB); based on
Helmholtz
Model for real
time data of
( ,σ)

Propagation Velocity for EM Signals vs SeaWater
Depth
While reading
literature we
discovered that
vp ≈ 3 ∗ 107
(m/Sec)

Estimated Parameters
Table: Estimated Parameters for 100m Depth @Multiple Frequencies
Parameters 1MHz 5MHz 10MHz 15MHz 20MHz
α(Np/m) 3.8890 8.6795 12.2453 14.9815 17.2348
Z(Ohms) 0.6620 1.4830 2.0935 2.5640 2.9606
β(rad/m) 3.8928 8.7213 12.3634 15.1784 17.5687
Vp(m/sec) 1.6132 ∗ 106 3.6004 ∗ 106 5.0795 ∗ 106 6.2062 ∗ 106 7.1491 ∗ 106
dp ≈ 1/α(m) 0.2571 0.1152 0.0877 0.0668 0.0580
τ(sec) 1.2303 ∗ 10−11 1.2304 ∗ 10−11 1.2304 ∗ 10−11 1.2304 ∗ 10−11 1.2304 ∗ 10−11
fT(Hz) 1.041 ∗ 109 1.041 ∗ 109 1.041 ∗ 109 1.041 ∗ 109 1.041 ∗ 109
eim 6.9069 ∗ 104 1.3814 ∗ 104 6.9069 ∗ 103 4.6047 ∗ 103 3.4535 ∗ 103
ere 66.2674 66.2674 66.2674 66.2673 66.2673
tanδ 1.0423 ∗ 103 204.4548 104.2280 69.4860 52.1152

Received Power for EM Signals vs SeaWater Depth
We can see that
for lower f and
for lower σ
(S/m); PR (dBm)
decays
linearly.While for
higher f and for
higher σ (S/m);
PR (dBm) faces
sudden
exponential
decay Image taken from IJCS

Received Power (Novel Approach)for EM Signals vs
SeaWater Depth
If insulated
encapsulation
length is 5
meters (≈
dRayleigh);then for
that much
distance PR
(dBm) remains
constant.Overall
range R (m) is
50 − 300
(meters) Image taken from IJCS

Section 4
Contribution-II

Summary of Contribution-II
We estimated Lα and Lo for EM waves propagation considering
multiple SeaWater depths from surface to 5500m
Computed loss due to polarization (Lφ) for EM ﬁelds between Tx
and Rx
Lφ along with Lα (dB)and Lo (dB)helps us to predict achievable Rest
By ﬁtting Non-Linear Least Square (NLLS)approximation
Lambert Transformation for non-linear exponential decaying Lα
Predicted Rest (m)helps to minimize mean(e(t)) by adapting to R
(m) using NLLS approach

Mathematical Modeling of Rest based on EM
Propagation in SeaWater
In far-ﬁeld, tangential component Eθ radiated by eclectic dipole
determine EM ﬁeld as
Eθ = Eoe−αz
e−jβz
(12)
Lφ loss and antenna properties i.e GT and GR determine total LUW
PR = PT ∗ GT ∗ GR ∗ (λ/4πR)2
∗ e−2αR
∗ cos2
(φ) (13)

NLLS approximation for Rest based on Attenuation of
EM Waves-I
Least Square (LS) approach minimizes squared difference
between x(t) (in our case Rest (meters)) and y(t) (R(meters))
In our case, x(t) represents summation of perturbed version
(Model Inaccuracies) like (Lα, Lo, Lφ)
x(t) further based on θ accounts for input f,PT,GT and used
modulation schemes (BPSK,QPSK or FSK)
Input y(t) represents actual distance between Tx and Rx; while x(t)
described as perturbation on y(t)
J(θ) =
N−1
n=0
[x(t) − y(t)]2
(14)

EM Waves-II
Here observational interval assumed between n = 0, 1, ......, N − 1
and dependence of J (Jacobin matrix) is on θ via y(t)
Performance also depends on noise corruption No or Pn and
modeling errors
Computation of y(t) = H θ leads to simple linear problem; however
y(t) rather considered as a non linear N-dimensional matrix in
general scenarios
First one-to-one transformation produces linear model:
A = g(θ). (15)

EM Waves-III
g is p-dimensional matrix whose inverse can lead easily to
compute linear LSE of A and thus, NLLS of θ as follows
y(g−1
(A)) = HA. (16)
θ = g−1
(A) (17)
A = (HT
H)−1
(HT
x) (18)
URSM describes LUW (dB) as a function of R (m)as :
RSS(dBm) = −20log10(R) − 20log10(Rαlog10e) + γoffsetfactor (19)
γoffsetfactor (dBm)represents antennas and environmental inﬂuences
as:
γoffsetfactor = (GT + GR + 20 × log(λ/4 × π) + Lφ) + 30 (20)
Rest = (1/(α×log10e∗ln10))×W[α×log10e×lnee−ln10/20(PR−PT )−γln10/20
]

Lambert W-Transformation for Non-Linear exponential
decaying Lα
Lambert W-
function;known
as omega
function or
product of
logarithm set of
functions
f−1
(x) = y = W(y)
(21) Image taken from IJCS

Mean Estimated Offset Factor
Mean Estimated
Offset Factor

Mean Rest versus Number of Occurrences
Mean Estimated
Range

Mean e(t) versus Number of Occurrences
Mean Estimated
Error

Estimated Parameters at Multiple SeaWater Depths
Table:Estimated Parameters at Multiple SeaWater Depths
Parameter 0m 50m 100m 350m 700m 1200m 1700m 2400m 3400m 4400m 5500m
T(Co) 13.838 12.957 11.451 7.548 4.880 3.067 2.285 1.756 1.422 1.456 3.070
S(ppt) 34.083 34.515 34.735 34.762 34.630 34.694 34.771 34.831 34.866 34.988 34.337
α(dB/m) 10.645 10.619 10.546 10.312 10.143 10.033 9.987 9.955 9.929 9.921 9.936
σ(S/m) 4.145 4.097 3.963 3.562 3.299 3.139 3.074 3.028 2.994 2.982 3.003
r 1.342 ∗ 104 1.327 ∗ 104 1.283 ∗ 104 1.154 ∗ 104 1.068 ∗ 104 1.017 ∗ 104 9.958 ∗ 103 9.812 ∗ 103 9.201 ∗ 103 9.662 ∗ 103 9.732 ∗ 103
r 68.223 68.174 68.479 69.645 70.394 70.737 70.838 70.903 70.970 71.004 70.976
γ(dBm) 22.606 22.644 22.784 23.223 23.550 23.784 23.881 23.944 23.955 24.017 23.986
Z(Ohms) 1.916 1.932 2.008 2.252 2.445 2.576 2.633 2.673 2.705 2.716 2.697
β(rad/m) 12.542 12.471 12.267 11.648 11.209 10.938 10.825 10.747 10.687 10.666 10.703
Vpm/Sec(∗106) 5.759 4.780 4.866 5.123 5.326 5.458 5.519 5.555 5.586 5.597 5.577
τ(Sec)(∗10−11) 1.181 1.206 1.243 1.348 1.458 1.544 1.584 1.613 1.633 1.639 1.625
fT(Hz) 1.093 ∗ 109 1.081 ∗ 109 1.041 ∗ 109 9.207 ∗ 108 8.436 ∗ 108 7.988 ∗ 108 7.811 ∗ 108 7.689 ∗ 108 7.595 ∗ 108 7.561 ∗ 108 7.617 ∗ 108
T 1.989 1.986 1.989 1.988 1.987 1.986 1.986 1.985 1.985 1.985 1.985

Pe versus Number of Occurrences
Mean
Probability of
Error
20 40 60 80 100 120 140 160 180 200
Mean Estimated Range (R) meters
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Pe
BPSK/QPSK (Coherent)
FSK (Non-Coherent)
FSK (Coherent)

Concluding Remarks
In this thesis, we used real time data for all oceans at different
latitudes (0o to ±90o) and longitudes (0o to ±180o); data averaged
between (1955-2012) for T (Co) and S (ppt) up to 5500m depth
Estimated Pr (dBm) helped us to analyze that for lower f (means
higher r )and for lower σ (S/m); Pr (dBm) decays linearly.While
for higherf (means lower r )and for higher σ (S/m); Pr (dBm)
faces sudden exponential decay
Computed parameters Lα (dB),Lo (dB) and Lφ (dB) used to
estimate LUW (dB) at multiple depths of oceans for (1-20)MHz
range
LUW (dB) also helps us in Rest)(m) by applying lambert-W
considering NL exponential problem and minimizing mean(e(t))
using NLLS approach
Rest (meters)using EM waves in SeaWater shows that maximum
achievable depth is 200m with mean(e(t)) =400m)

THANKS FOR THE ATTENTION

Channel Characterization of EM Waves Propagation at MHz Frequency through SeaWater

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