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IS
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1693
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i
on
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.
S
o
m
e
num
e
ri
c
a
l
r
e
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ul
t
s
a
r
e
s
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n
i
n
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e
c
t
i
on
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a
nd
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on
c
l
us
i
ons
a
r
e
f
i
na
l
l
y
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w
n
i
n
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e
c
t
i
on
V
.
T
hrough
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h
e
p
a
pe
r,
(
)
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r
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de
not
e
s
a
s
out
a
ge
pro
ba
bi
l
i
t
y,
(
)
(
)
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,
.
XX
Ff
a
re
r
e
pr
e
s
e
n
t
e
d
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t
he
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u
m
ul
a
t
i
ve
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s
t
ri
b
ut
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on
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nc
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i
on
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F
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nd
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h
e
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roba
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l
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t
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t
y
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t
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D
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n
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c
h
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i
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nd
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va
ri
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e
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i
s
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h
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xpe
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t
a
t
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on
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e
ra
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or.
2.
S
Y
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TEM
M
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EL
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uppos
e
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ha
t
t
h
e
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M
A
s
ys
t
e
m
a
s
i
n
F
i
gure
1
c
o
-
ope
r
a
t
e
s
a
t
t
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s
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gn
a
l
t
r
a
ns
m
i
t
t
e
d
fro
m
a
BS
t
o
t
ra
ns
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i
t
s
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gna
l
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o
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h
e
d
e
v
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c
e
n
e
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r
t
he
BS
,
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nd
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o
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e
vi
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e
l
oc
a
t
e
d
a
t
t
h
e
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e
l
l
bou
nda
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y,
a
l
s
o
k
now
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a
s
t
w
o
N
O
M
A
us
e
rs
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e
a
r
de
v
i
c
e
s
1
D
a
n
d
fa
r
de
v
i
c
e
2
D
).
P
a
rt
i
c
u
l
a
r
l
y
m
a
ny
t
r
a
di
t
i
on
a
l
m
ob
i
l
e
us
e
rs
(CU
s
)
i
n
t
he
ro
l
e
o
f
i
n
t
e
r
m
e
d
i
a
t
e
n
ode
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or
t
r
a
ns
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r
ri
ng
t
o
2
D
.
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ore
s
p
e
c
i
fi
c
a
l
l
y
,
t
h
e
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di
r
e
c
t
l
y
t
ra
ns
m
i
t
s
t
h
e
s
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gn
a
l
t
o
t
h
e
us
e
r
1
D
,
w
hi
l
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us
e
r
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D
n
e
e
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e
l
p
of
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h
e
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s
t
re
l
a
y
re
l
a
y.
I
t
w
ort
h
not
i
ng
t
ha
t
t
h
e
w
e
a
k
s
i
gn
a
l
oc
c
urs
i
n
t
he
l
i
nk
fro
m
t
h
e
BS
t
o
2
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du
e
t
o
obs
t
a
c
l
e
of
t
he
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g
h
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i
l
d
i
ng
.
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e
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a
us
e
t
he
h
a
l
f
-
d
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e
x
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od
e
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s
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p
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s
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n
t
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s
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ui
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h
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m
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l
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n
d
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rd
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F
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s
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pe
r
a
t
e
d
i
n
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h
p
a
t
t
e
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n.
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t
h
i
s
m
od
e
l
,
t
w
o
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ons
e
c
u
t
i
v
e
t
i
m
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l
o
t
s
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re
re
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r
e
d
i
n
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h
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ol
l
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ra
t
i
v
e
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O
M
A
.
F
i
gure
1
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S
ys
t
e
m
m
od
e
l
of
re
l
a
y
s
e
l
e
c
t
i
o
n
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or
t
he
f
a
r
us
e
rs
a
n
d
di
r
e
c
t
l
i
nk
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or
t
he
n
e
a
r
us
e
r
M
ore
s
p
e
c
i
fi
c
a
l
l
y
,
t
h
e
be
s
t
r
e
l
a
y
i
n
K
A
F
r
e
l
a
ys
(
)
1
,
.
.
.
,
,
1
K
R
R
K
i
s
s
e
l
e
c
t
e
d
t
o
s
up
port
a
b
a
s
e
s
t
a
t
i
on
(
BS
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w
hi
c
h
i
s
e
xpe
c
t
e
d
t
o
forw
a
r
d
t
he
s
i
gn
a
l
t
o
t
h
e
f
a
r
us
e
r
2
D
.
N
or
m
a
l
l
y
,
s
e
l
e
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t
i
on
c
r
i
t
e
ri
a
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de
t
e
rm
i
ni
ng
s
i
gn
a
l
w
h
i
c
h
ne
e
d
b
e
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rde
d
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n
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ud
i
ng
m
a
x
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m
i
n
s
e
l
e
c
t
i
on
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b
e
s
t
r
e
l
a
y
s
e
l
e
c
t
i
on
a
n
d
pa
r
t
i
a
l
re
l
a
y
s
e
l
e
c
t
i
on
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u
c
h
de
c
i
s
i
ons
a
re
prov
i
de
d
t
o
s
e
l
e
c
t
t
he
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rd
i
ng
node
i
n
t
he
c
e
nt
ra
l
c
ont
r
ol
uni
t
i
n
c
ons
i
d
e
re
d
n
e
t
w
o
rk.
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e
re
,
a
s
t
he
s
i
m
p
l
i
s
t
i
c
m
ode
l
c
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n
b
e
a
p
pl
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e
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i
n
pra
c
t
i
c
e
t
h
e
pa
r
t
i
a
l
re
l
a
y
s
e
l
e
c
t
i
on
opt
i
on
w
hi
c
h
i
s
s
t
udi
e
d
a
s
i
n
t
h
i
s
pa
p
e
r
.
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i
s
p
os
s
i
bl
e
t
h
a
t
a
ddi
t
i
ona
l
ga
us
s
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a
n
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h
i
t
e
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s
e
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W
G
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t
e
r
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s
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r
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a
ppl
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n
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ode
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nd
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s
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um
i
ng
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h
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t
Ra
yl
e
i
gh
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e
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r
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a
ny
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i
nk
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n
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ork
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c
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n
b
e
de
not
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d
(
0
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)
kk
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h
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s
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h
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o
m
p
l
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h
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nne
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oe
ff
i
c
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k
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e
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2
2
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S
S
S
x
a
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x
a
P
x
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W
he
r
e
1
D
a
nd
2
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c
e
i
ve
s
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x
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nd
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re
s
p
e
c
t
i
v
e
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d
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h
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l
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e
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ra
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gn
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l
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t
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h
e
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r
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e
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s
e
d
by
:
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1
1
11
1
1
1
2
2
.
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M
A
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O
M
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S
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S
D
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h
x
w
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x
a
P
x
w
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=
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T
he
re
c
e
i
v
e
d
s
i
gna
l
a
t
K
R
i
s
g
i
v
e
n
by:
(
)
1
1
2
2
.
kk
kk
N
O
M
A
N
O
M
A
S
R
K
S
R
S
R
S
R
S
S
R
y
h
x
w
h
a
P
x
a
P
x
w
=+
=
+
+
(3)
T
he
s
i
gn
a
l
c
a
n
be
r
e
c
e
i
v
e
d
a
t
2
D
i
s
:
2
2
2
2
.
k
NO
M
A
S
R
KD
R
D
R
D
y
g
P
x
w
=+
(4)
W
e
ob
t
a
i
n
S
N
R
t
o
d
e
t
e
c
t
s
i
g
na
l
1
x
a
t
d
e
s
t
i
na
t
i
on
1
D
a
s
:
22
1
1
1
1
1
22
2
1
0
2
1
,
1
S
S
D
S
S
D
N
O
M
A
SD
S
S
D
S
S
D
a
P
h
a
h
a
P
h
N
a
h
==
++
(5)
w
he
re
0
.
S
S
P
N
=
W
e
p
e
rfor
m
S
N
R
t
o
f
i
rs
t
de
t
e
c
t
1
x
a
nd
t
he
n
de
pl
oy
i
ng
S
IC
t
o
d
e
t
e
c
t
2
x
a
s
be
l
ow
:
2
1
,1
2
2
,
1
k
k
S
S
R
N
O
M
A
S
R
K
x
S
S
R
ah
ah
=
+
(6)
2
,
2
2
.
k
N
O
M
A
S
R
K
x
S
S
R
ah
=
(7)
A
t
d
e
s
t
i
n
a
t
i
on
2
D
,
w
e
c
a
l
c
ul
a
t
e
S
N
R
t
o
d
e
t
e
c
t
2
x
a
s
i
t
i
s
forw
a
rd
i
n
g
fro
m
t
he
r
e
l
a
y
t
o
2
D
.
2
2
2
2
2
,
2
0
,
k
k
R
R
D
N
O
M
A
R
K
D
x
R
R
D
Pg
g
N
==
(8)
w
he
re
0
R
R
P
N
=
,
R
P
de
no
t
e
s
t
he
t
ra
ns
m
i
t
p
ow
e
r
of
t
he
th
k
r
e
l
a
y
a
nd
t
h
i
s
pow
e
r
i
s
a
s
s
u
m
e
d
s
a
m
e
for
a
l
l
r
e
l
a
y.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
1693
-
6930
T
E
L
K
O
M
N
IK
A
T
e
l
e
c
om
m
un
Co
m
put
E
l
Con
t
rol
,
V
ol
.
18
,
N
o.
2
,
A
pri
l
2
020:
587
-
5
94
590
3.
O
U
TA
G
E
P
ER
F
O
R
M
A
N
C
E
A
N
A
LY
S
I
S
3.
1
.
O
u
ta
ge
p
r
ob
ab
i
l
i
t
y
at
th
e
n
e
ar
u
s
e
r
1
D
W
e
fi
rs
t
d
e
t
e
rm
i
n
e
t
he
out
a
g
e
pr
oba
b
i
l
i
t
y
a
t
n
e
a
r
d
e
vi
c
e
1
D
re
l
a
t
e
d
t
o
d
e
t
e
c
t
i
ng
t
he
s
i
gn
a
l
12
,
xx
,
w
he
re
1
2
1
21
R
=−
a
s
:
(
)
(
)
1
11
11
1
12
P
r
1
e
x
p
,
N
O
M
N
O
M
A
SD
A
S
SD
OP
aa
−
=
=
−
−
−
(9)
3.
2
.
O
u
ta
ge
p
r
ob
ab
i
l
i
t
y
at
2
D
for
d
e
t
e
c
ti
n
g
1
x
In
D
F
m
od
e
,
t
h
e
r
e
l
a
y
fi
rs
t
d
e
c
od
e
1
x
a
nd
t
he
n
fo
rw
a
rd
2
x
t
o
de
s
t
i
na
t
i
o
n
2
D
.
T
he
S
N
R
f
or
d
e
t
e
c
t
s
i
gna
l
a
t
2
D
c
a
n
b
e
f
orm
u
l
a
t
e
d
by
:
(
)
,
1
,
2
2
,
2
m
in
,
,.
NO
M
A
NO
M
A
NO
M
A
S
R
K
x
S
R
K
x
R
K
NM
D
A
k
x
O
=
(10)
i
t
i
s
n
ot
e
d
t
ha
t
t
he
b
e
s
t
re
l
a
y
nod
e
i
n
K
re
l
a
y
nod
e
s
i
s
s
e
l
e
c
t
e
d
by
t
he
fol
l
ow
i
n
g
c
ri
t
e
r
i
on
:
(
)
*
1
m
a
x
.
N
O
M
A
N
O
M
A
kk
kK
=
=
(11)
t
he
r
e
for
e
,
t
h
e
out
a
ge
pr
oba
b
i
l
i
t
y
a
t
2
D
c
a
n
be
c
a
l
c
u
l
a
t
e
d
by:
(
)
(
)
*
,
1
*
,
2
*
2
,
2
,1
2
1
2
2
1
2
2
1
,
2
2
,
2
Pr
1
P
r
,
.
,
N
O
M
A
N
O
M
A
N
O
M
A
S
R
K
x
S
R
K
x
R
K
D
x
N
O
M
A
N
O
M
A
N
O
M
A
S
R
K
x
S
R
K
x
N
O
M
A
K
k
R
K
x
A
D
OP
−
=
=
=
−
(12)
i
t
ne
e
d
be
furt
he
r
c
om
pu
t
e
d
A
a
s
be
l
ow
:
(
)
(
)
1
2
2
1
1
2
2
2
1
1
2
1
2
2
2
22
1
2
12
1
2
2
Pr
,
Pr
,
m
a
x
,.
,
S
R
S
R
R
KD
S
S
R
S
R
R
KD
S
S
R
h
h
g
a
a
a
h
A
g
a
a
a
=
=
−
−
(13)
i
t
i
s
r
e
w
ri
t
t
e
n
a
s
:
22
2
2
2
2
2
1
2
1
2
12
1
P
r
,
P
r
m
i
n
,
e
xp
.
1
1
1
1
R
S
R
R
K
D
S
R
R
K
D
S
R
R
R
K
D
h
g
h
g
A
=
=
−
=−
(14)
t
he
r
e
for
e
,
w
e
ob
t
a
i
n
f
i
n
a
l
e
xp
re
s
s
i
on
for
2
D
’
s
out
a
ge
e
ve
n
t
:
2
2
1
12
1
e
x
p
,
SR
K
N
O
M
A
R
K
D
k
R
OP
−
=
−
=
−
−
(15)
w
he
re
(
)
12
12
1
2
m
a
x
,
SS
a
a
a
=
−
,
2
2
2
21
R
=−
.
In
a
d
di
t
i
on
,
w
e
a
l
s
o
e
v
a
l
u
a
t
e
ove
r
a
l
l
o
ut
a
ge
e
v
e
n
t
of
ove
ra
l
l
N
O
M
A
s
ys
t
e
m
a
s
:
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
K
O
M
N
IK
A
T
e
l
e
c
om
m
un
Co
m
put
E
l
Con
t
rol
E
nabl
i
ng
r
e
l
ay
s
e
l
e
c
t
i
on
i
n
non
-
or
t
hogon
al
m
ul
t
i
p
l
e
ac
c
e
s
s
n
e
t
wor
k
s
:
d
i
r
e
c
t
and
…
(
D
i
nh
-
T
huan
D
o
)
591
(
)
(
)
(
)
(
)
(
)
2
1
1
*
,
1
*
,
2
*
2
,
2
1
1
*
,
1
*
1
,
2
*
2
2
,
1
2
2
2
12
Pr
1
P
r
P
r
1
1
1
.
N
O
M
A
N
O
M
A
N
O
M
A
N
O
M
A
S
D
S
R
K
x
S
R
K
x
R
K
D
x
N
O
M
A
N
O
M
A
N
O
M
A
N
O
M
A
S
D
S
R
K
x
S
R
K
x
R
K
D
x
N
O
M
A
N
O
M
A
N
O
M
A
OP
O
P
O
P
−−
=
=
−
−−
−
=
(16)
3.
3
.
O
u
ta
ge
p
r
ob
ab
i
l
i
t
y
i
n
O
M
A
s
c
e
n
ar
i
o
A
s
be
n
c
hm
a
rk
of
N
O
M
A
,
w
e
c
o
m
pu
t
e
d
s
i
gn
a
l
a
t
1
D
i
n
O
M
A
m
ode
a
s
:
1
1
1
1
.
O
M
A
S
D
S
D
S
D
y
h
P
x
w
=+
(17)
T
he
re
c
e
i
v
e
d
s
i
gna
l
a
t
r
e
l
a
y
i
s
g
i
ve
n
by
:
12
.
O
M
A
S
R
K
S
R
S
R
K
y
h
P
x
w
=+
(18)
T
he
s
i
gn
a
l
c
a
n
be
c
om
p
ut
e
d
a
t
2
D
a
s
:
22
22
.
OMA
R
KD
R
KD
R
R
KD
y
g
P
x
w
=+
(19)
W
e
c
o
nt
i
nue
c
om
p
ut
e
S
N
R
t
o
de
t
e
c
t
s
i
gn
a
l
1
x
w
hi
c
h
i
s
t
ra
ns
m
i
t
t
e
d
fr
om
BS
t
o
1
D
:
2
11
.
O
M
A
S
D
S
S
D
h
=
(20)
T
o
c
ons
i
de
r
S
N
R
t
o
de
t
e
c
t
2
x
a
t
t
h
e
re
l
a
y
K
,
w
e
c
om
p
ut
e
fo
l
l
ow
i
ng
e
qua
t
i
on
:
2
,
2
1
.
O
MA
SR
K
x
S
SR
h
=
(21)
Si
m
i
l
a
r
l
y
,
S
N
R
t
o
d
e
t
e
c
t
2
x
fro
m
r
e
l
a
y
t
o
2
D
c
a
n
b
e
e
xpr
e
s
s
e
d
by
:
2
2
,
2
2
.
OMA
R
KD
x
R
R
KD
g
=
(22)
W
e
c
o
nt
i
nue
t
o
c
om
put
e
o
ut
a
ge
e
v
e
n
t
fo
r
1
D
i
n
c
a
s
e
of
O
M
A
:
(
)
1
1
1
1
1
P
r
1
e
x
p
,
OMA
O
M
A
SD
SD
S
OP
−
=
=
−
−
(23)
w
he
re
1
2
1
21
R
=−
.
In
O
M
A
m
od
e
,
t
h
e
be
s
t
r
e
l
a
y
node
i
s
s
e
l
e
c
t
e
d
b
y
t
he
fo
l
l
ow
i
ng
c
ri
t
e
ri
on:
(
)
(
)
,
2
2
,
*
1
2
m
i
n
,
,
m
a
x
.
O
M
A
O
M
A
S
R
K
x
R
KD
x
OMA
k
O
M
A
O
M
A
kk
kK
=
=
=
(24)
T
he
ou
t
a
g
e
prob
a
bi
l
i
t
y
a
t
2
D
i
n
O
M
A
c
a
s
e
i
s
e
x
a
m
i
ne
d
by
:
(
)
(
)
(
)
22
22
22
1
2
2
*
1
1
12
1
Pr
1
Pr
1
Pr
,
1
e
x
p
,
S
R
R
K
D
SR
S
R
R
K
O
M
A
O
M
A
O
M
A
k
k
k
K
K
k
KD
k
OP
hg
−
=
=
=
=
=
−
=
−
=
−
−
−
(25)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
1693
-
6930
T
E
L
K
O
M
N
IK
A
T
e
l
e
c
om
m
un
Co
m
put
E
l
Con
t
rol
,
V
ol
.
18
,
N
o.
2
,
A
pri
l
2
020:
587
-
5
94
592
w
he
re
2
4
2
21
R
=−
,
2
S
=
,
2
R
=
.
fi
na
l
,
ov
e
ra
l
l
ou
t
a
g
e
e
ve
nt
i
n
O
M
A
c
a
s
e
i
s
g
i
ve
n
by
:
(
)
(
)
(
)
(
)
(
)
(
)
(
)
12
1
1
*
,
2
*
2
,
2
2
1
1
*
,
2
*
2
,
2
2
P
r
m
i
n
,
1
P
r
P
r
m
i
n
,
1
1
1
.
O
M
A
O
M
A
O
M
A
O
M
A
O
M
A
S
D
S
R
K
x
R
K
D
x
O
M
A
O
M
A
O
M
A
S
D
S
R
K
x
R
K
D
x
OMA
O
P
O
P
OP
−−
=
=
−
−
=
−
−
(26)
4.
N
U
M
ER
I
C
A
L
R
ES
U
LT
In
t
h
e
s
e
s
i
m
ul
a
t
i
on
r
e
s
ul
t
s
,
t
he
propos
e
d
re
l
a
y
s
e
l
e
c
t
i
o
n
s
t
ra
t
e
gy
for
N
O
M
A
t
r
a
ns
m
i
s
s
i
on
i
s
pe
rfor
m
e
d
t
o
de
t
e
rm
i
ne
t
he
ou
t
a
ge
p
e
rfor
m
a
n
c
e
,
a
nd
s
e
ve
ra
l
c
or
re
s
pon
di
ng
p
a
ra
m
e
t
e
rs
a
re
c
ondu
c
t
e
d
.
In
F
i
gure
2,
t
he
p
e
rfor
m
a
nc
e
of
prop
os
e
d
s
c
h
e
m
e
i
s
i
l
l
us
t
ra
t
e
d
a
s
c
om
p
a
ri
ng
t
h
e
out
a
g
e
pe
rf
orm
a
n
c
e
v
e
rs
us
t
he
t
r
a
ns
m
i
t
S
N
R
i
n
c
a
s
e
of
v
a
ry
i
ng
num
be
r
of
re
l
a
y
no
de
.
T
he
r
e
l
a
y
i
s
be
f
i
t
t
e
d
by
s
e
l
e
c
t
i
o
n
m
od
e
fo
r
t
he
f
a
r
us
e
r
w
h
i
l
e
ne
a
r
de
v
i
c
e
do
not
n
e
e
d
a
ny
re
l
a
y
.
F
ro
m
F
i
gu
re
2,
hi
gh
num
be
r
of
r
e
l
a
y
node
c
ont
ri
bu
t
e
t
o
i
nc
r
e
a
s
e
pe
r
form
a
n
c
e
s
i
gni
f
i
c
a
nt
l
y
.
M
ore
s
p
e
c
i
fi
c
a
l
l
y
,
t
he
p
e
rfor
m
a
n
c
e
ga
p
c
a
n
be
s
e
e
n
c
l
e
a
r
l
y
a
t
h
i
gh
S
N
R
re
gi
m
e
.
U
nfor
t
un
a
t
e
l
y
,
t
he
pr
opos
e
d
re
l
a
y
s
e
l
e
c
t
i
on
s
c
he
m
e
ha
s
t
he
s
i
m
i
l
a
r
pe
r
form
a
n
c
e
a
t
s
o
m
e
s
p
e
c
i
fi
c
va
l
u
e
s
,
i
.
e
.
t
he
nu
m
be
r
of
re
l
a
y
i
s
5
or
10,
a
n
d
t
hi
s
s
i
t
u
a
t
i
on
c
onfi
r
m
e
d
t
h
a
t
t
h
e
l
i
m
i
t
e
d
num
be
r
of
r
e
l
a
y
c
a
n
b
e
pe
rfor
m
e
d
t
o
a
ppro
a
c
h
p
e
rfor
m
a
nc
e
f
l
oor
.
A
s
c
a
n
be
s
e
e
n
fro
m
F
i
gur
e
3,
t
he
ou
t
a
ge
p
e
rfor
m
a
n
c
e
fo
r
de
t
e
c
t
i
n
g
s
i
gna
l
of
2
x
ve
rs
us
t
he
t
r
a
ns
m
i
t
S
N
R.
S
i
m
i
l
a
rl
y
a
s
i
n
F
i
g
ure
2,
t
he
p
e
rfor
m
a
nc
e
ga
p
pro
vi
de
s
t
he
e
nha
nc
e
d
pe
rfor
m
a
n
c
e
a
s
re
a
s
ona
bl
e
s
e
l
e
c
t
i
on
of
nu
m
b
e
r
of
r
e
l
a
y.
T
o
i
m
pr
ove
t
h
e
r
e
l
i
a
b
i
l
i
t
y
of
t
h
e
c
oop
e
ra
t
i
v
e
n
e
t
w
o
rks
,
t
h
e
h
i
gh
e
r
d
i
ve
rs
i
t
y
ga
i
ns
i
s
re
q
ui
r
e
d
a
nd
s
uc
h
m
ode
l
s
a
t
i
s
fi
e
s
ba
s
i
c
r
e
qu
i
re
m
e
n
t
.
I
t
i
s
n
ot
e
d
t
h
a
t
t
h
e
dow
nw
a
rd
t
re
n
d
i
s
s
e
e
n
i
n
t
he
c
o
ns
i
de
re
d
N
O
M
A
fo
r
ou
t
a
ge
be
ha
v
i
or.
It
c
a
n
be
s
how
n
out
a
g
e
p
e
rfor
m
a
nc
e
of
d
e
t
e
c
t
i
ng
s
i
gn
a
l
of
1
x
a
s
c
ha
ngi
n
g
pow
e
r
a
l
l
oc
a
t
i
on
fra
c
t
i
ons
a
s
i
n
F
i
gur
e
4
a
n
d
v
a
ryi
ng
t
he
t
hr
e
s
hol
d
S
N
R
a
s
i
n
F
i
gu
re
5.
It
i
s
pr
e
c
i
ous
l
y
s
e
e
n
t
ha
t
a
s
t
h
e
a
na
l
ys
i
s
l
i
n
e
s
of
m
a
t
c
h
t
i
g
ht
l
y
w
i
t
h
t
h
e
s
i
m
ul
a
t
i
on
c
urv
e
s
.
T
h
e
ot
he
r
a
s
pe
c
t
i
s
t
ha
t
m
o
re
a
l
l
oc
a
t
e
d
pow
e
r
a
s
s
i
gne
d
t
o
us
e
r
l
e
a
ds
t
o
b
e
t
t
e
r
p
e
rfor
m
a
n
c
e
.
In
ot
h
e
r
ha
n
d,
t
h
e
hi
g
he
r
t
hr
e
s
ho
l
d
S
N
R
re
qui
r
e
s
h
i
gh
e
r
da
t
a
ra
t
e
,
a
nd
h
e
nc
e
d
e
c
l
i
ni
ng
out
a
g
e
pe
rfor
m
a
n
c
e
s
e
e
n
i
n
F
i
gur
e
5.
S
i
m
i
l
a
r
t
re
nd
c
a
n
be
s
e
e
n
i
n
F
i
gure
6
f
or
c
or
re
s
pond
i
ng
s
i
g
na
l
2
x
.
N
e
xt
,
F
i
gur
e
6
c
om
pa
r
e
s
out
a
ge
p
e
rfor
m
a
nc
e
f
or
de
t
e
c
t
i
n
g
bo
t
h
s
i
gn
a
l
s
.
T
he
d
i
ff
e
re
n
t
pow
e
r
a
l
l
oc
a
t
i
on
fa
c
t
ors
a
n
d
di
ff
e
r
e
nt
t
ra
ns
m
i
s
s
i
on
l
i
nks
a
r
e
m
a
i
n
r
e
a
s
o
n
t
o
s
how
d
i
ff
e
re
n
t
ou
t
a
g
e
pe
rfor
m
a
n
c
e
.
A
no
t
he
r
obs
e
rva
t
i
o
n
i
s
t
ha
t
t
he
p
e
rfor
m
a
nc
e
of
N
O
M
A
i
s
be
t
t
e
r
O
M
A
a
t
s
e
ve
r
a
l
poi
n
t
s
of
t
ra
ns
m
i
t
S
N
R
t
o
h
i
ghl
i
ght
i
m
pro
ve
m
e
n
t
of
c
ons
i
de
r
e
d
N
O
M
A
.
F
i
gure
2
.
O
ut
a
g
e
pr
oba
bi
l
i
t
y f
or
1
x
O
P
1
(
1
0
.
8
a
=
,
1
1
SD
=
)
F
i
gure
3
.
O
u
t
a
g
e
prob
a
bi
l
i
t
y
f
or
d
e
t
e
c
t
i
n
g
2
x
(
1
0
.
8
a
=
,
12
1
S
R
R
K
D
==
,
1
0
.
5
R
=
,
2
2
R
=
)
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
K
O
M
N
IK
A
T
e
l
e
c
om
m
un
Co
m
put
E
l
Con
t
rol
E
nabl
i
ng
r
e
l
ay
s
e
l
e
c
t
i
on
i
n
non
-
or
t
hogon
al
m
ul
t
i
p
l
e
ac
c
e
s
s
n
e
t
wor
k
s
:
d
i
r
e
c
t
and
…
(
D
i
nh
-
T
huan
D
o
)
593
F
i
gure
4
.
O
u
t
a
g
e
prob
a
bi
l
i
t
y
o
f
1
x
a
s
va
r
yi
ng
c
ha
n
ne
l
g
a
i
ns
(
1
0
.
8
a
=
,
1
0
.
5
R
=
)
F
i
gure
5
.
O
u
t
a
g
e
prob
a
bi
l
i
t
y
o
f
2
x
a
s
va
r
yi
ng
c
ha
n
ne
l
g
a
i
ns
(
1
0
.
8
a
=
,
2
1
R
K
D
=
,
1
0
.
5
R
=
,
2
2
R
=
)
F
i
gure
6
.
O
ut
a
g
e
pr
oba
bi
l
i
t
y
c
om
pa
r
i
son f
or
1
x
a
nd
2
x
(
1
0
.
8
a
=
,
1
1
2
1
S
R
S
D
R
K
D
=
=
=
,
1
0
.
5
R
=
,
2
2
R
=
,
5
K
=
)
5.
C
O
N
C
LU
S
I
O
N
In
t
hi
s
s
t
udy
,
t
h
e
ou
t
a
g
e
pr
oba
b
i
l
i
t
y
of
N
O
M
A
ne
t
w
orks
t
og
e
t
h
e
r
w
i
t
h
op
t
i
m
a
l
s
e
l
e
c
t
i
on
s
c
h
e
m
e
w
a
s
pre
s
e
n
t
e
d
t
o
e
n
ha
n
c
e
s
ys
t
e
m
p
e
rfor
m
a
nc
e
i
n
t
w
o
re
a
l
s
c
e
n
a
ri
os
a
t
ne
a
r
a
nd
fa
r
di
s
t
a
n
c
e
be
t
w
e
e
n
us
e
r
a
nd
t
he
BS
.
In
s
uc
h
m
od
e
l
,
t
he
s
e
l
e
c
t
e
d
c
ri
t
e
ri
a
i
s
w
i
t
h
j
oi
n
t
l
o
c
a
t
i
on
of
us
e
r
a
n
d
re
l
a
y
s
e
l
e
c
t
i
o
n.
I
n
p
a
rt
i
c
u
l
a
r
,
t
he
c
l
os
e
d
-
f
orm
a
n
a
l
yt
i
c
a
l
e
xpr
e
s
s
i
ons
i
s
p
rovi
d
e
d
t
o
s
ys
t
e
m
p
e
rfor
m
a
nc
e
.
It
c
a
n
be
de
t
e
r
m
i
ne
how
n
um
b
e
r
of
r
e
l
a
ys
a
nd
t
h
e
t
a
rge
t
da
t
a
ra
t
e
h
a
ve
e
ffe
c
t
s
on
s
ys
t
e
m
p
e
rfor
m
a
n
c
e
.
T
h
e
s
e
c
ond
re
a
s
on
t
o
c
hoos
e
s
uc
h
m
ode
l
t
h
a
t
t
h
e
n
um
b
e
r
of
us
e
rs
i
s
r
e
a
s
o
na
b
l
e
c
h
os
e
n
t
o
i
m
pro
ve
t
he
t
ra
ns
m
i
s
s
i
on
qu
a
l
i
t
y
i
n
N
O
M
A
.
R
EF
ER
EN
C
ES
[
1]
L
.
Z
h
a
ng
,
J
.
L
i
u,
M
.
X
i
a
o
,
G
.
W
u
,
Y
.
L
i
a
ng
,
a
n
d
S
.
L
i
,
“
P
e
r
f
or
m
a
n
c
e
a
na
l
ys
i
s
a
nd
o
pt
i
m
i
z
a
t
i
o
n
i
n
dow
n
l
i
nk
N
O
M
A
s
y
s
t
e
m
s
w
i
t
h
c
oo
pe
r
a
t
i
v
e
f
u
l
l
-
d
upl
e
x
r
e
l
a
y
i
ng
,
”
I
E
E
E
J
.
S
e
l
e
c
t
.
A
r
e
as
C
om
m
u
n.
,
v
ol
.
35
,
n
o.
10
,
pp.
23
98
-
2412
,
201
7.
[
2]
Z
.
Y
a
ng
,
Z
.
D
i
ng
,
Y
.
W
u
,
a
nd
P
.
F
a
n
,
“
N
ov
e
l
r
e
l
a
y
s
e
l
e
c
t
i
o
n
s
t
r
a
t
e
gi
e
s
f
o
r
c
oop
e
r
a
t
i
ve
N
O
M
A
,
”
I
E
E
E
T
r
a
ns
.
V
e
h
.
T
e
c
hn
ol
.
,
v
ol
.
66
,
n
o.
11
,
pp
.
1011
4
-
1
012
3,
20
1
7.
[
3]
Z
.
D
i
n
g,
M
.
P
e
n
g,
a
nd
H
.
V
.
P
oo
r
,
“
C
oop
e
r
a
t
i
ve
non
-
or
t
ho
gon
a
l
m
u
l
t
i
p
l
e
a
c
c
e
s
s
i
n
5G
s
ys
t
e
m
s
,
”
I
E
E
E
C
om
m
un
.
L
e
t
t
.
,
vo
l
.
19
,
no
.
8,
pp
.
146
2
-
1
465
,
2015
.
[
4]
J
.
K
i
m
a
nd
I
.
L
e
e
,
“
C
a
pa
c
i
t
y
a
na
l
y
s
i
s
o
f
c
oop
e
r
a
t
i
ve
r
e
l
a
yi
n
g
s
ys
t
e
m
s
u
s
i
ng
non
-
or
t
h
ogon
a
l
m
ul
t
i
pl
e
a
c
c
e
s
s
,
”
I
E
E
E
C
om
m
un
.
L
e
t
t
.
,
vo
l
.
1
9,
no
.
11
,
pp
.
1
949
-
195
2,
2
015
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
1693
-
6930
T
E
L
K
O
M
N
IK
A
T
e
l
e
c
om
m
un
Co
m
put
E
l
Con
t
rol
,
V
ol
.
18
,
N
o.
2
,
A
pri
l
2
020:
587
-
5
94
594
[
5]
D
.
W
a
n
,
M
.
W
e
n
,
H
.
Y
u
,
Y
.
L
i
u
,
F
.
J
i
,
a
nd
F
.
C
he
n
,
“
N
on
-
o
r
t
hogo
na
l
m
u
l
t
i
p
l
e
a
c
c
e
s
s
f
or
dua
l
-
hop
de
c
od
e
-
a
nd
-
f
o
r
w
a
r
d
r
e
l
a
yi
ng,
”
i
n
P
r
oc
.
I
E
E
E
G
l
o
ba
l
C
om
m
uni
c
a
t
i
on
C
o
nf
e
r
e
nc
e
,
W
a
s
h
i
ng
t
on
,
U
S
A
,
D
e
c
.
20
16.
[
6]
J
.
M
e
n,
J
.
G
e
,
a
n
d
C
.
Z
h
a
ng
,
“
P
e
r
f
or
m
a
nc
e
a
n
a
l
ys
i
s
of
non
-
o
r
t
h
o
gona
l
m
u
l
t
i
p
l
e
a
c
c
e
s
s
f
o
r
r
e
l
a
y
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ng
ne
t
w
o
r
ks
ov
e
r
N
a
ka
g
a
m
i
-
m
F
a
di
n
g
c
ha
nne
l
s
,
”
I
E
E
E
T
r
an
s
.
V
e
h.
T
e
c
hn
ol
.
,
v
ol
.
66,
no
.
2,
pp
.
120
0
-
1
208
,
2016
.
[
7]
D
i
nh
-
T
hua
n
D
o,
“
P
ow
e
r
s
w
i
t
c
h
i
ng
p
r
o
t
o
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ol
f
or
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r
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l
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yi
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g
ne
t
w
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k
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r
ha
r
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a
r
e
i
m
p
a
i
r
m
e
n
t
s
,
”
R
adi
o
e
ng
i
ne
e
r
i
ng
,
vo
l
.
24
,
no
.
3,
pp
.
765
-
7
71,
2
015
.
[
8]
D
i
nh
-
T
hua
n
D
o
,
H
.
-
S
.
N
guy
e
n
,
M
V
oz
n
a
k
a
nd
T
.
-
S
.
N
g
uye
n
,
"
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i
r
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l
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s
s
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ow
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r
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d
r
e
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y
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t
w
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ks
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nde
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m
pe
r
f
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c
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l
s
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n
f
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m
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t
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ne
ous
r
a
t
e
,
"
R
adi
oe
n
gi
n
e
e
r
i
n
g
,
vol
.
26,
n
o.
3
,
pp.
8
69
-
877
,
2017
.
[
9]
X.
-
X
.
N
gu
ye
n
,
D
i
nh
-
T
hu
a
n
D
o,
"
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a
xi
m
u
m
H
a
r
v
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gy
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ol
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k
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S
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,
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nt
e
r
n
at
i
on
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o
ur
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al
o
f
C
om
m
uni
c
a
t
i
o
n
Sy
s
t
e
m
s
(
W
i
l
e
y
)
,
v
ol
.
30
,
n
o.
17
,
J
u
l
y
2017
.
D
O
I
:
10
.
100
2/
da
c
.
33
59
[
10]
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-
X
.
N
guy
e
n
,
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i
nh
-
T
hu
a
n
D
o
,
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p
t
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m
a
l
pow
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r
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l
l
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pe
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l
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U
R
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S
I
P
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r
na
l
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r
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l
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s
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om
m
un
i
c
a
t
i
on
s
and
N
e
t
w
o
r
k
i
ng
,
vol
.
152
,
no
.
2017
,
pp
.
1
-
1
6,
20
17
.
[
11]
T.
-
L
.
N
guy
e
n
,
D
i
n
h
-
T
h
ua
n
D
o,
“
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ne
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l
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t
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t
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l
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e
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:
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ne
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gy
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ve
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i
ng
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l
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,
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nn
al
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l
e
c
om
m
un
i
c
a
t
i
ons
,
vol
.
72,
n
o.
11
,
pp
.
669
-
678
,
J
u
ne
201
7.
[
12]
D
i
n
h
-
T
hua
n
D
o,
H
.
-
S
.
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guy
e
n
,
“
A
T
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c
t
a
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l
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nc
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ne
l
i
nt
e
r
f
e
r
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n
c
e
,
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U
R
A
SI
P
J
o
ur
n
al
on
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i
r
e
l
e
s
s
C
om
m
uni
c
a
t
i
o
ns
and
N
e
t
w
or
k
i
n
g
,
vo
l
.
27
1,
no.
20
16
,
p
p.
1
-
10
,
2016
.
[
13]
T
.
A
.
Z
e
w
de
a
n
d
M
.
C
.
G
u
r
s
oy,
“
N
O
M
A
-
b
a
s
e
d
e
n
e
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gy
-
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f
f
i
c
i
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nt
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i
r
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l
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o
m
m
un
i
c
a
t
i
on
s
,
”
I
E
E
E
T
r
ans
.
G
r
e
e
n
C
om
m
u
n.
an
d
N
e
t
.
,
vo
l
.
2,
no
.
3,
p
p
.
67
9
-
69
2,
20
18
.
[
14]
J
.
G
o
ng
a
nd
X
.
C
he
n
,
“
A
c
h
i
e
v
a
b
l
e
r
a
t
e
r
e
g
i
on
o
f
non
-
or
t
ho
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a
l
m
ul
t
i
pl
e
a
c
c
e
s
s
s
ys
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m
s
w
i
t
h
w
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r
e
l
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s
s
pow
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r
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d
de
c
od
e
r
,
”
I
E
E
E
J
.
S
e
l
.
A
r
e
as
C
om
m
un
.
,
v
ol
.
35
,
n
o.
12
,
pp
.
2846
–
2
859,
D
e
c
2017
.
[
15]
Y
.
L
i
u
,
Z
.
D
i
n
g,
M
.
E
l
ka
s
hl
a
n
,
a
n
d
H
.
V
.
P
oo
r
,
“
C
o
ope
r
a
t
i
v
e
no
n
-
o
r
t
h
ogon
a
l
m
u
l
t
i
p
l
e
a
c
c
e
s
s
w
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t
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s
i
m
u
l
t
a
ne
ous
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i
r
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l
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s
s
i
nf
o
r
m
a
t
i
o
n
a
nd
pow
e
r
t
r
a
n
s
f
e
r
,
”
I
E
E
E
J
.
S
e
l
.
A
r
e
as
C
om
m
un.
,
vol
.
34
,
no
.
4
,
pp
.
938
–
953
,
A
pr
20
16.
[
16]
D
i
n
h
-
T
hua
n
D
o
a
nd
M
.
-
S
.
V
a
n
N
g
uye
n,
"
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e
v
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c
e
-
to
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e
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c
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t
r
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ns
m
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s
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r
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om
pu
t
e
r
C
om
m
un
i
c
a
t
i
ons
,
vo
l
.
13
9,
pp
.
67
-
77
,
M
a
y
2019
.
[
17]
D.
-
T
.
D
o
,
M
.
V
a
e
z
i
a
nd
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.
-
L
.
N
g
uye
n
,
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o
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l
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om
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,
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bu
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i
,
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A
E
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p
p.
1
-
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,
2
018
.
[
18]
D.
-
T
.
D
o
a
nd
A
.
-
T
.
L
e
,
“
N
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M
A
ba
s
e
d
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ogn
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v
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g:
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s
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om
p
ut
e
r
C
om
m
un
i
c
at
i
on
s
,
vo
l
.
146
,
pp.
1
44
-
154
,
O
c
t
o
be
r
2
019
.
[
19]
S
.
L
e
e
,
D
.
B
.
da
C
os
t
a
,
Q
.
-
T
.
V
i
e
n,
T
.
Q
.
D
uo
ng,
a
n
d
R
.
T
.
de
S
ous
a
,
‘
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on
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on
,
’
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E
T
C
om
m
u
ni
c
at
i
on
.
,
vol
.
11
,
no.
6
,
p
p.
846
–
854
,
201
7.
[
20]
S
.
L
e
e
,
D
.
B
.
d
a
C
os
t
a
,
T
.
Q
.
D
uo
ng
,
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t
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o
n,
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i
n
P
r
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c
.
I
E
E
E
P
I
M
R
C
,
p
p.
1
–
6,
2
016
.
[
21]
D
-
T
.
D
o
e
t
a
l
.
“
W
i
r
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l
e
s
s
pow
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r
t
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a
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r
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on,
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l
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om
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om
pu
t
E
l
C
on
t
r
ol
,
vo
l
.
17,
no
.
6
,
pp
.
2
697
-
270
3,
20
19
.
[
22]
D
i
n
h
-
T
hua
n
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o
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C
hi
-
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o
L
e
,
A
.
-
T
.
L
e
,
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l
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og
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on
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r
o
l
,
vo
l
.
1
7,
no.
5
,
pp.
2
147
-
215
4,
20
19.
[
23]
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i
nh
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hua
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o
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l
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,
no.
5
,
pp.
1
966
-
197
3,
20
18.
[
24]
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i
nh
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T
hua
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o
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C
.
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om
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l
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,
p
p.
19
07
-
1917
,
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obe
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2
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.
[
25]
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A
.
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819
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1
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2
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20
19.
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