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Science
Vo
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21
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2
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Feb
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p
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886
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cs.v
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.
pp
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9
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886
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m
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rica
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e
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a
m
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e
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e
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e
h
a
v
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o
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th
e
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ste
m
.
F
in
a
ll
y
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w
e
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e
ri
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th
e
v
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li
d
it
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o
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o
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r
a
n
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l
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sin
g
th
e
m
o
n
te
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c
a
rlo
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n
.
K
ey
w
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r
d
s
:
Am
p
li
f
y
-
a
n
d
-
f
o
r
w
ar
d
B
est
s
en
s
o
r
n
o
d
e
s
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tio
n
NOM
A
Ou
ta
g
e
p
r
o
b
ab
ilit
y
T
h
r
o
u
g
h
p
u
t
W
SN
T
h
is
is
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Dac
-
B
in
h
Ha
Facu
lt
y
o
f
E
lectr
ical
-
E
lectr
o
n
i
c
E
n
g
i
n
ee
r
in
g
Du
y
T
an
U
n
iv
er
s
it
y
,
Da
Na
n
g
,
Vietn
a
m
E
m
ail:
h
ad
ac
b
in
h
@
d
u
y
ta
n
.
ed
u
.
v
n
1.
I
NT
RO
D
UCT
I
O
N
I
n
th
e
last
d
ec
ad
es,
w
ir
ele
s
s
s
en
s
o
r
n
e
t
w
o
r
k
s
(
W
SN)
h
a
v
e
b
ee
n
w
id
el
y
ap
p
lied
in
m
a
n
y
f
i
eld
s
,
s
u
c
h
as
m
o
n
ito
r
in
g
en
v
ir
o
n
m
e
n
tal
p
ar
am
eter
s
in
i
n
d
u
s
tr
y
a
n
d
ag
r
icu
lt
u
r
e,
s
m
ar
t
tr
a
n
s
p
o
r
t,
s
m
ar
t
g
r
id
s
,
w
ea
r
ab
le
m
ed
ical
ca
r
e
d
ev
ices
[
1
-
3
]
.
T
h
e
m
ai
n
ad
v
an
ta
g
e
o
f
w
ir
e
less
s
e
n
s
o
r
n
et
w
o
r
k
s
is
th
at
th
e
u
s
e
o
f
e
x
is
ti
n
g
in
f
r
astru
ct
u
r
e
m
a
y
n
o
t
i
n
c
u
r
a
d
d
itio
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al
co
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o
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w
ir
i
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g
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n
d
eq
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ip
m
e
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t,
an
d
f
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r
th
er
,
t
h
e
cl
o
u
d
av
ailab
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a
n
d
I
o
T
p
r
o
to
co
l
f
o
r
a
f
ast
co
n
n
ec
tio
n
.
Ho
w
e
v
er
,
W
SN
also
co
n
tai
n
s
m
an
y
p
r
o
b
le
m
s
t
h
at
n
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ed
to
b
e
a
d
d
r
ess
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,
t
y
p
icall
y
d
ata
tr
an
s
m
i
s
s
io
n
b
et
w
ee
n
d
e
v
ices
in
t
h
e
n
et
w
o
r
k
w
h
e
n
t
h
e
s
ca
le
o
f
t
h
e
n
et
w
o
r
k
b
ec
o
m
e
s
v
er
y
lar
g
e
w
it
h
a
m
as
s
i
v
e
a
m
o
u
n
t
o
f
d
at
a
[
4
]
.
T
h
e
n
o
n
-
o
r
th
o
g
o
n
al
m
u
ltip
le
ac
ce
s
s
(
NOM
A
)
tec
h
n
iq
u
e
w
as
p
r
o
p
o
s
ed
as
th
e
b
est
s
o
l
u
tio
n
to
s
o
l
v
e
th
e
a
b
o
v
e
p
r
o
b
lem
w
h
e
n
s
ati
s
f
y
i
n
g
th
e
v
er
y
h
i
g
h
d
ata
r
ate
an
d
m
ass
i
v
e
co
n
n
ec
tiv
it
y
d
em
a
n
d
b
o
th
in
u
p
li
n
k
a
n
d
d
o
w
n
li
n
k
tr
an
s
m
is
s
io
n
s
[
5
-
7
]
.
NOM
A
ca
n
s
u
p
p
o
r
t
m
u
l
tip
le
u
s
er
s
at
th
e
s
a
m
e
ti
m
e
an
d
th
e
s
a
m
e
f
r
eq
u
en
c
y
r
eso
u
r
ce
.
I
n
W
SN,
th
e
u
p
lin
k
ch
a
n
n
el
p
la
y
s
a
cr
itica
l
r
o
le,
as
th
is
is
th
e
p
ath
th
at
t
h
e
s
en
s
o
r
s
u
s
ed
to
p
er
f
o
r
m
th
e
t
ask
o
f
tr
an
s
m
itti
n
g
th
e
d
ata
t
h
e
y
co
llect
to
th
e
s
in
k
n
o
d
e.
Ho
w
e
v
er
,
s
t
u
d
ies
o
n
W
SN
u
s
i
n
g
u
p
li
n
k
N
OM
A
a
r
e
s
till
r
elativ
el
y
s
m
all
[
8
-
1
2
]
.
I
n
[
8
]
,
th
e
au
th
o
r
s
p
r
o
p
o
s
ed
W
SN
to
u
s
e
th
e
u
p
lin
k
NO
M
A
ap
p
licatio
n
to
m
ea
s
u
r
e
p
ar
a
m
eter
s
i
n
ag
r
ic
u
l
tu
r
e.
T
h
e
s
en
s
o
r
s
ar
e
d
iv
id
ed
in
to
clu
s
ter
s
an
d
u
s
e
s
h
o
r
t
-
r
a
n
g
e
m
u
l
ti
-
h
o
p
co
m
m
u
n
icatio
n
tec
h
n
o
lo
g
y
to
tr
an
s
f
e
r
d
ata
to
th
e
s
i
n
k
n
o
d
e.
T
h
e
a
u
th
o
r
s
u
s
ed
t
h
e
s
u
m
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
C
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p
Sci
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N:
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4752
P
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ma
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ce
me
n
t o
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w
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s
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s
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etw
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k
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s
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g
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-
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r
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l m
u
ltip
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(
Du
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Ha
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887
d
ata
r
ate
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d
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tag
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p
r
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ab
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f
o
r
m
an
ce
o
f
t
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s
y
s
te
m
.
I
n
[
9
]
,
th
e
u
p
li
n
k
NOM
A
m
u
lti
u
s
er
m
o
d
el
w
as p
r
o
p
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ed
.
T
h
e
b
ase
s
tatio
n
i
s
eq
u
ip
p
ed
w
it
h
N
a
n
te
n
n
as,
a
n
d
ea
ch
u
s
e
r
eq
u
ip
m
en
t u
n
it
h
as
a
s
i
n
g
le
a
n
ten
n
a,
t
h
e
u
s
er
s
ar
e
d
iv
id
ed
in
to
t
w
o
g
r
o
u
p
s
:
r
o
b
u
s
t
s
et
a
n
d
w
ea
k
s
et
d
ep
en
d
in
g
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n
th
e
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h
a
n
n
el
s
tatu
s
.
T
h
e
p
ap
er
p
r
o
p
o
s
es
th
at
t
h
e
p
o
w
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co
n
tr
o
l
s
ch
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m
e
ca
n
m
a
x
i
m
ize
t
h
e
s
u
m
ca
p
ac
it
y
w
it
h
a
m
i
n
i
m
u
m
tar
g
et
r
ate.
An
o
th
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co
m
m
o
n
p
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it
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is
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ta
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th
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et
w
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k
.
T
h
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s
en
s
o
r
n
o
d
es
lo
ca
ted
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e
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et
w
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e
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n
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l
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m
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icate
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it
h
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b
o
r
in
g
n
o
d
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d
n
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d
s
u
p
p
o
r
t
f
r
o
m
th
e
r
ela
y
to
co
m
m
u
n
icate
w
i
th
t
h
e
s
i
n
k
n
o
d
e.
T
r
an
s
itio
n
tec
h
n
iq
u
e
s
co
m
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in
ed
w
i
th
NOM
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h
elp
s
s
o
lv
e
t
h
i
s
p
r
o
b
le
m
i
n
W
SN
[
1
3
-
2
5
]
.
I
n
[
1
3
]
,
th
e
au
t
h
o
r
s
p
r
o
p
o
s
ed
th
e
u
p
lin
k
NO
MA
m
o
d
el
f
o
r
t
w
o
u
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er
s
w
it
h
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e
s
u
p
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ase
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to
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o
v
id
in
g
f
o
r
m
u
las
f
o
r
s
y
s
te
m
p
r
o
b
a
b
ilit
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d
t
h
r
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g
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t
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ased
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cr
itical
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ar
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eter
s
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ig
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al
to
n
o
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e
r
atio
,
tr
an
s
m
i
s
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io
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p
o
w
er
.
I
n
[
1
6
]
,
tw
o
u
s
er
s
co
m
m
u
n
icate
d
w
it
h
t
h
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b
ase
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ex
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lex
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el
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m
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lo
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i
n
g
th
e
d
ec
o
d
e
-
an
d
-
f
o
r
w
ar
d
s
ch
e
m
e
to
ass
is
t
t
h
e
f
ar
u
s
er
.
W
ith
th
e
g
iv
e
n
tar
g
et
d
ata
r
ates,
th
e
a
u
th
o
r
s
p
r
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ed
th
e
m
et
h
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to
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eter
m
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e
t
h
e
m
o
s
t
o
p
ti
m
al
p
o
w
er
allo
ca
tio
n
f
ac
to
r
s
.
Dif
f
er
en
t
f
r
o
m
p
r
ev
io
u
s
s
t
u
d
ies,
in
t
h
is
s
t
u
d
y
,
w
e
p
r
o
p
o
s
e
a
NOM
A
s
ce
n
ar
io
f
o
r
th
e
u
p
l
in
k
o
f
t
w
o
s
en
s
o
r
n
o
d
e
clu
s
ter
s
,
i
n
w
h
ich
th
e
t
w
o
s
e
n
s
o
r
s
ap
p
l
y
t
h
e
u
p
l
in
k
NOM
A
s
c
h
e
m
e
to
tr
an
s
m
i
t
th
eir
in
f
o
r
m
a
tio
n
to
th
e
s
in
k
v
ia
t
h
e
AF
r
ela
y
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
u
s
es
th
e
b
est
co
m
b
i
n
atio
n
o
f
d
ir
ec
t
li
n
k
an
d
f
o
r
w
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d
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li
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k
s
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tio
n
m
ec
h
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i
s
m
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ased
o
n
th
e
m
ax
i
m
u
m
s
i
g
n
al
to
en
d
-
to
-
en
d
n
o
i
s
e
r
atio
.
T
o
an
aly
ze
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
is
s
y
s
te
m
,
w
e
d
er
i
v
e
e
x
p
r
ess
io
n
s
o
f
t
h
e
o
u
ta
g
e
p
r
o
b
ab
il
it
y
a
n
d
t
h
r
o
u
g
h
p
u
t
b
y
u
s
in
g
t
h
e
Ga
u
s
s
ia
n
-
C
h
eb
y
s
h
ev
q
u
ad
r
atic.
T
h
e
n
u
m
er
ical
r
es
u
lt
s
w
ill
b
e
ca
lcu
lated
ac
co
r
d
in
g
to
t
h
e
m
ai
n
p
ar
a
m
eter
s
:
tr
an
s
m
is
s
io
n
p
o
w
er
,
th
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es to
f
i
n
d
w
a
y
s
to
i
m
p
r
o
v
e
th
e
p
er
f
o
r
m
an
ce
o
f
th
i
s
s
y
s
te
m
.
T
h
e
r
em
ai
n
d
er
o
f
th
is
r
esear
c
h
ca
n
b
e
f
o
r
m
u
lated
as
f
o
llo
ws.
Sectio
n
2
p
r
esen
ts
th
e
s
y
s
te
m
m
o
d
el.
Sectio
n
3
an
al
y
ze
s
t
h
e
s
y
s
te
m
p
er
f
o
r
m
a
n
ce
.
Sectio
n
4
s
h
o
w
s
t
h
e
n
u
m
er
ical
r
esu
lts
w
i
t
h
s
o
m
e
d
is
c
u
s
s
io
n
s
.
Fin
all
y
,
Sectio
n
5
co
n
clu
d
es t
h
e
s
t
u
d
y
.
2.
SYST
E
M
M
O
DE
L
W
e
co
n
s
id
er
an
u
p
lin
k
NOM
A
r
ela
y
in
g
s
y
s
te
m
f
o
r
W
SN
as
Fig
u
r
e
1
.
T
h
is
s
y
s
te
m
co
n
s
i
s
ts
o
f
t
w
o
s
en
s
o
r
clu
s
ter
s
P
w
it
h
N
s
e
n
s
o
r
n
o
d
es a
n
d
Q
w
i
th
M
s
e
n
s
o
r
n
o
d
es,
a
r
ela
y
n
o
d
e,
an
d
a
s
in
k
.
T
w
o
s
en
s
o
r
n
o
d
es
s
elec
ted
r
esp
ec
ti
v
el
y
f
r
o
m
P
a
n
d
Q
tr
a
n
s
m
it
th
e
ir
m
ess
a
g
es
to
th
e
s
i
n
k
n
o
d
e
(
S)
w
i
th
th
e
h
elp
o
f
a
s
i
n
g
le
AF
R
.
A
s
s
u
m
in
g
t
h
at
t
h
e
s
e
n
s
in
g
d
ata,
i.e
.
,
co
n
f
id
e
n
tial
d
ata,
v
i
d
eo
d
ata,
f
r
o
m
P
i
s
m
o
r
e
i
m
p
o
r
tan
t
t
h
an
t
h
e
d
ata,
i.e
.
,
h
u
m
id
it
y
,
te
m
p
er
atu
r
e,
f
r
o
m
Q.
T
h
er
ef
o
r
e,
t
h
e
b
est
s
e
n
s
o
r
n
o
d
e
is
s
e
lecte
d
f
r
o
m
P
(
S
NP
*
)
,
m
ea
n
ti
m
e,
t
h
e
s
en
s
o
r
n
o
d
e
o
f
Q
(
SN
Q)
is
r
an
d
o
m
l
y
c
h
o
s
en
to
tr
a
n
s
m
it
th
eir
d
ata
to
S
v
ia
R
.
All
s
en
s
o
r
n
o
d
es,
r
ela
y
,
an
d
s
in
k
h
a
v
e
s
in
g
le
-
an
ten
n
a
a
n
d
w
o
r
k
in
h
a
lf
-
d
u
p
le
x
m
o
d
e.
S
u
p
p
o
s
e
R
h
a
s
s
u
f
f
icie
n
t
c
h
a
n
n
e
l
in
f
o
r
m
at
io
n
f
r
o
m
th
e
s
e
n
s
o
r
cl
u
s
ter
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t
h
u
s
ac
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r
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g
to
t
h
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m
ax
i
m
u
m
c
h
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n
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ai
n
,
R
a
s
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est
n
o
d
e
SNP
*
f
r
o
m
P
to
s
en
d
s
e
n
s
in
g
d
ata
to
it.
Fig
u
r
e
1
.
S
y
s
te
m
m
o
d
el
T
h
e
p
r
o
p
o
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p
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atin
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p
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co
l f
o
r
th
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s
y
s
te
m
i
s
g
i
v
e
n
as
f
o
llo
w
s
:
P
ha
s
e
1
:
SNP
*
a
n
d
SNQ
s
i
m
u
lta
n
eo
u
s
l
y
tr
an
s
m
i
t t
h
eir
s
i
g
n
als (
s
1
,
s
2
)
to
R
d
u
r
in
g
t
h
e
p
er
io
d
o
f
T
/2
,
w
h
er
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T
d
en
o
tes as tr
an
s
m
is
s
io
n
b
lo
ck
ti
m
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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Sci,
Vo
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21
,
No
.
2
,
Feb
r
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ar
y
2
0
2
1
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8
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8
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4
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P
ha
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Du
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p
er
io
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,
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a
m
p
li
f
ie
s
a
n
d
f
o
r
w
ar
d
s
t
h
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s
ig
n
al
r
ec
eiv
ed
f
r
o
m
SNP
*
a
n
d
SNQ
to
S.
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n
all
y
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S
u
s
es
t
h
e
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ter
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d
etail
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at
h
e
m
atica
ll
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as
f
o
llo
w
s
.
P
ha
s
e
1
:
A
p
p
l
y
NOM
A
s
c
h
e
m
e,
SN
P*,
an
d
S
N
Q
s
i
m
u
lta
n
eo
u
s
l
y
to
tr
a
n
s
m
it
th
e
ir
s
i
g
n
als
(
s
1
,
s
2
)
to
R
b
y
u
s
i
n
g
th
eir
tr
an
s
m
it p
o
w
er
o
n
t
h
e
s
a
m
e
f
r
eq
u
e
n
c
y
in
t
h
e
s
a
m
e
p
er
i
o
d
T
/2
.
T
h
e
s
ig
n
al
r
ec
ei
v
ed
at
R
h
a
s
t
h
e
f
o
llo
w
i
n
g
f
o
r
m
:
12
1
1
1
2
2
1
12
,
PP
y
h
s
h
s
n
dd
(
1
)
w
h
er
e
h
k
(
k
=
{1
,
2
})
ar
e
R
ay
l
eig
h
f
ad
i
n
g
c
h
a
n
n
el
co
e
f
f
icie
n
ts
o
f
li
n
k
s
f
r
o
m
S
N
P*
an
d
S
N
Q
to
R
,
r
esp
ec
tiv
el
y
,
n
1
is
A
W
GN
w
i
th
ze
r
o
m
ea
n
an
d
th
e
v
ar
ia
n
ce
o
f
2
,
2
2
~
(
0
,
)
n
CN
,
d
1
an
d
d
2
ar
e
th
e
E
u
clid
ea
n
d
is
ta
n
ce
s
o
f
SN
P*
an
d
SN
Q
to
R
,
r
esp
ec
ti
v
e
l
y
,
an
d
r
ep
r
esen
ts
th
e
p
ath
-
lo
s
s
ex
p
o
n
e
n
t.
P
ha
s
e
2
:
A
p
p
l
y
in
g
t
h
e
AF
s
ch
e
m
e,
th
e
tr
an
s
m
i
s
s
io
n
s
i
g
n
al
at
R
h
as
th
e
tr
an
s
m
i
s
s
io
n
p
o
w
er
P
R
ca
n
b
e
f
o
r
m
u
lated
b
y
,
1
.
R
y
G
y
(
2
)
I
n
p
ar
ticu
lar
,
G
is
t
h
e
r
ela
y
i
n
g
g
ai
n
o
f
t
h
e
A
F
r
ela
y
R
,
w
h
ic
h
is
d
ef
in
ed
b
y
t
h
e
f
ac
t
th
at
t
h
e
P
3
b
o
u
n
d
s
th
e
tr
a
n
s
f
er
p
o
w
er
o
f
t
h
e
r
ela
y
.
T
h
er
ef
o
r
e,
G
is
g
i
v
en
b
y
,
3
2
2
2
1
1
1
2
2
2
.
|
|
/
|
|
/
P
G
P
h
d
P
h
d
(
3
)
T
h
er
ef
o
r
e,
th
e
s
ig
n
al
r
ec
eiv
ed
at
S is
w
r
itte
n
as,
3
1
2
2
1
1
2
2
1
2
22
3
,
G
h
P
P
y
h
s
h
s
n
n
dd
d
(
4
)
w
h
er
e
h
3
an
d
d
3
ar
e
th
e
R
a
y
le
ig
h
f
ad
i
n
g
ch
a
n
n
el
co
ef
f
icie
n
t
an
d
E
u
clid
ea
n
d
is
ta
n
ce
o
f
R
an
d
S,
r
esp
ec
tiv
e
l
y
2
2
~
(
0
,
)
n
CN
.
Fin
all
y
,
S
ap
p
lies
SIC
to
d
ete
ct
th
e
s
i
g
n
a
ls
o
f
S
N
P*
a
n
d
SN
Q
.
T
h
e
p
r
o
ce
s
s
is
a
s
f
o
llo
w
s
:
s
1
w
ill
b
e
d
etec
ted
f
ir
s
t
d
u
e
to
b
etter
ch
an
n
e
l
co
n
d
it
io
n
,
th
e
n
s
ep
ar
a
tio
n
o
f
s
ig
n
al
s
2
b
y
s
u
b
tr
ac
ti
n
g
s
1
f
r
o
m
y
2
.
T
h
e
in
s
ta
n
ta
n
eo
u
s
SIN
R
f
o
r
d
etec
tin
g
s
1
at
S is
g
i
v
en
b
y
,
1
22
2
1
1
3
1
3
22
2
2
2
2
2
2
3
3
22
1
3
1
3
2
2
2
2
2
2
3
2
3
1
1
2
2
3
3
/
//
,
1
s
P
G
h
h
d
d
G
P
h
d
h
d
hh
h
h
h
h
h
(
5
)
w
h
er
e
1
2
3
1
2
3
2
2
2
1
2
3
,
,
.
P
P
P
d
d
d
Af
ter
s
u
b
tr
ac
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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AL
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
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4752
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E
S
[1
]
A
la
m
,
M
.
M
.
,
Ha
m
id
a
,
E.
B.
,
Re
h
m
a
n
i,
M
.
,
&
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a
th
a
n
,
A
.
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Wea
ra
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le
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ies
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5
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]
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rt,
S
.
,
Yild
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it
,
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.
,
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li
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,
&
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u
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.
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rid
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ra
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[3
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&
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e
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ta,
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tru
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lt
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it
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sin
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n
so
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t
w
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s:
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siv
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”
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mm
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.
[4
]
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rb
,
H.,
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b
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,
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a
k
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l,
A
.
,
Zah
w
e
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O.,
&
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m
,
M
.
A
.
“
W
irele
s
s
se
n
so
r
n
e
t
w
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s:
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b
ig
d
a
ta
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rc
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in
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n
tern
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h
in
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ter
n
a
ti
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l
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a
n
g
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n
,
a
n
d
R.
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Hu
,
“
Do
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.
S
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l.
Are
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s Co
mm
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n
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Da
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a
n
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a
n
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.
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n
,
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,
a
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d
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,
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c
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r
5
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:
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ll
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rt
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it
ies
,
a
n
d
f
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tu
re
re
se
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rc
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tren
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s,”
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Co
mm
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n
.
M
a
g
.
,
v
o
l.
5
3
,
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o
.
9
,
p
p
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8
1
,
2
0
1
5
.
[7
]
Z.
Din
g
,
M
.
P
e
n
g
,
a
n
d
H.
V
.
P
o
o
r,
“
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o
p
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l
m
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lt
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c
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ss
in
5
G
s
y
ste
m
s,”
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mm
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n
.
L
e
tt
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,
v
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l.
1
9
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o
.
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p
.
1
4
6
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-
1
4
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5
,
2
0
1
5
.
[8
]
Hu
,
Z.
,
Xu
,
L
.
,
Ca
o
,
L
.
,
L
iu
,
S
.
,
Lu
o
,
Z.
,
W
a
n
g
,
J.,
&
W
a
n
g
,
L
.
“
Ap
p
li
c
a
ti
o
n
o
f
No
n
-
Orth
o
g
o
n
a
l
M
u
lt
ip
le A
c
c
e
ss
in
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irel
e
ss
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e
n
so
r
Ne
t
w
o
rk
s f
o
r
S
m
a
rt
Ag
ricu
lt
u
re
.
”
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E
Acc
e
ss
,
v
o
l.
7
,
p
p
.
8
7
5
8
2
-
8
7
5
9
2
,
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0
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[9
]
Kim
,
B.
,
Ch
u
n
g
,
W
.
,
L
i
m
,
S
.
,
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u
h
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.
,
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u
n
,
J.,
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o
i,
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.
,
&
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n
g
,
D.
“
Up
li
n
k
NO
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A
w
it
h
m
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lt
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-
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te
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n
a
.
”
In
2
0
1
5
IE
EE
8
1
st ve
h
ic
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(V
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g
),
p
p
.
1
-
5
,
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0
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9
.
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0
]
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o
u
a
p
i,
A
.
;
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k
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m
,
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A
Ne
w
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p
p
ro
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h
to
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n
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1
1
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