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iti
o
n
,
to
r
ed
u
ce
th
e
co
n
s
u
m
ed
en
er
g
y
i
n
A
D
C
.
T
h
u
s
,
th
e
C
OM
P
SS
tech
n
iq
u
e
in
v
o
l
v
es
d
ec
r
ea
s
in
g
t
h
e
s
a
m
p
lin
g
r
ate
lo
w
er
th
a
n
th
e
N
y
q
u
i
s
t
r
ate.
T
h
is
p
ap
er
d
ev
elo
p
s
a
h
y
b
r
id
C
OM
P
SS
s
ch
e
m
e
i
n
d
etails
b
y
p
r
o
p
o
s
in
g
a
co
n
s
ta
n
t
lo
ca
l
a
n
d
g
lo
b
al
f
alse
a
lar
m
r
atio
s
(
C
L
F
A
R
)
a
n
d
(
C
GF
AR
)
e
x
p
r
ess
io
n
s
,
a
n
d
t
h
eir
e
f
f
ec
ts
o
n
d
etec
tio
n
p
er
f
o
r
m
a
n
ce
,
co
m
p
r
ess
io
n
r
atio
,
SNR
w
all,
an
d
co
m
p
u
tat
io
n
al
co
m
p
lex
it
y
tr
ad
e
-
o
f
f
s
in
s
e
n
s
in
g
th
e
OFD
M
s
ig
n
al
[
1
1
-
1
4
]
.
T
h
e
r
est
o
f
th
is
p
ap
er
is
o
u
tlin
ed
as
f
o
llo
w
s
:
T
h
e
alg
o
r
ith
m
o
f
t
h
e
co
n
s
id
er
ed
C
OM
P
SS
s
ch
e
m
e
an
d
its
f
o
r
m
u
lated
p
r
o
b
le
m
ar
e
d
escr
ib
ed
in
s
ec
tio
n
2
.
I
n
s
ec
tio
n
3
,
th
e
p
r
o
p
o
s
ed
C
OM
P
SS
tech
n
iq
u
e
s
ce
n
ar
io
s
ar
e
clar
if
ied
an
d
an
al
y
ze
d
.
N
u
m
er
ical
an
d
g
r
ap
h
ical
r
es
u
lt
s
an
d
t
h
eir
an
a
l
y
s
es
ar
e
g
iv
e
n
i
n
s
ec
t
io
n
4
.
C
o
n
c
lu
s
io
n
s
o
f
t
h
is
p
ap
er
ar
e
d
ep
icted
in
s
ec
tio
n
5
.
2.
T
H
E
B
ACK
G
RO
UND
M
O
DE
L
O
F
CO
M
P
SS
T
E
CH
N
I
Q
U
E
T
h
e
C
OM
P
SS
tec
h
n
iq
u
e
s
h
o
w
h
o
w
to
s
a
m
p
le
t
h
e
s
ig
n
al
less
t
h
a
n
t
h
e
N
y
q
u
i
s
t
r
ate
to
r
ed
u
ce
th
e
A
DC
co
s
t
w
h
ile
th
e
r
a
w
a
p
p
r
o
ac
h
es
w
er
e
s
a
m
p
led
at
th
e
Ny
q
u
is
t
r
ate.
T
h
e
C
OM
P
SS
alg
o
r
ith
m
ca
n
o
f
te
n
b
e
p
er
f
o
r
m
ed
v
ia
t
h
r
ee
s
er
ie
s
s
tep
s
,
a
s
d
ep
icted
in
Fig
u
r
e
1
[
1
5
,
1
6
]
:
s
p
r
ea
d
d
escr
i
p
tio
n
,
s
u
b
-
N
y
q
u
i
s
t
s
a
m
p
li
n
g
,
an
d
r
ec
o
n
s
tr
u
ct
io
n
.
T
h
e
f
u
n
ctio
n
s
o
f
t
h
e
s
e
s
tep
s
ar
e:
(
1
)
to
s
p
r
ea
d
th
e
s
i
g
n
al
o
v
er
r
ec
o
n
s
tr
u
ctab
le
b
ases
,
(
2
)
to
s
am
p
le
t
h
e
s
p
r
ea
d
in
g
s
i
g
n
al
at
a
s
u
b
-
N
y
q
u
is
t r
atio
,
(
3
)
t
o
r
ec
o
n
s
tr
u
ct
th
e
s
a
m
p
l
in
g
s
i
g
n
al
[
1
7
]
.
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
a
m
o
f
C
OM
P
SS
s
tep
s
Fro
m
th
e
v
ie
w
p
o
i
n
t
o
f
s
p
ec
tr
u
m
s
e
n
s
i
n
g
(
SS
)
,
th
e
s
en
s
i
n
g
d
etec
to
r
s
s
en
s
e
t
h
e
v
ar
io
u
s
s
ig
n
a
ls
t
h
a
t
h
av
e
lo
w
er
p
o
w
er
co
m
p
ar
ed
to
th
e
w
id
eb
an
d
s
i
g
n
als.
Ho
w
e
v
er
,
th
er
e
a
r
e
s
o
m
e
d
r
a
w
b
ac
k
s
s
u
c
h
as
u
s
in
g
a
n
u
m
b
er
o
f
R
F
f
r
o
n
te
n
d
s
as
t
h
e
n
u
m
b
er
o
f
b
an
d
s
th
a
t
s
h
o
u
l
d
b
e
s
en
s
ed
,
co
m
p
u
tat
io
n
al
co
m
p
lex
i
t
y
,
an
d
h
ig
h
co
n
s
u
m
p
tio
n
o
f
en
er
g
y
,
w
h
i
ch
r
esu
l
ts
i
n
air
p
o
llu
tio
n
.
T
h
e
C
OM
P
SS
co
n
ce
p
t
is
m
o
r
e
o
r
less
r
ec
o
v
er
s
th
e
s
e
n
s
ed
s
i
g
n
al
th
a
t
is
s
a
m
p
led
at
th
e
s
u
b
-
N
y
q
u
i
s
t
r
ate
to
m
ee
t
t
h
e
A
DC
d
e
m
an
d
s
a
n
d
d
ea
l
w
it
h
is
s
u
e
s
o
f
w
id
eb
an
d
s
i
g
n
als
s
en
s
i
n
g
[
1
8
]
.
T
o
d
escr
ib
e
th
e
m
at
h
e
m
a
tical
m
o
d
el
o
f
C
O
MP
SS
,
s
u
p
p
o
s
e
th
at
N
ew
i
s
a
s
p
r
ea
d
s
am
p
le
s
n
u
m
b
er
w
it
h
≪
,
an
d
N
d
en
o
tes
th
e
o
r
ig
in
a
l
len
g
th
s
i
g
n
al
.
I
n
ad
d
itio
n
,
s
u
p
p
o
s
e
th
at
ψ
is
a
s
p
r
ea
d
b
ases
(
m
atr
ix
)
s
u
c
h
as DFT
o
r
DW
T
w
it
h
s
ize
o
f
(
N
×
N
)
.
T
h
u
s
,
th
e
s
p
r
ea
d
s
ig
n
al
ca
n
b
e
m
o
d
elle
d
as f
o
llo
w
s
:
=
×
(
1
)
w
h
er
e
x
COM
P
d
en
o
tes
th
e
s
p
r
ea
d
s
ig
n
al
a
n
d
s
is
th
e
ex
ten
s
io
n
o
f
s
i
g
n
al
w
h
er
e
‖
‖
0
=
≪
.
Su
p
p
o
s
e
t
h
at
Φ
is
a
s
en
s
in
g
m
atr
i
x
w
it
h
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ize
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(
N
e
w
×N
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to
co
m
p
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ess
th
e
s
ig
n
al
w
i
th
ess
e
n
tia
l
i
n
f
o
r
m
at
io
n
o
f
x
COM
P
,
as d
ep
icted
in
Fig
u
r
e
2
.
Fig
u
r
e
2
.
Stru
ct
u
r
e
o
f
co
m
p
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s
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u
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g
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g
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s
ch
eme
fo
r
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i
tive
r
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etw
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ks (
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n
ta
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r
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b
a
s
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h
er)
5901
T
h
e
co
m
p
r
es
s
ed
s
i
g
n
al,
y
COM
P
,
r
ep
r
esen
ts
th
e
s
i
g
n
al
m
ea
s
u
r
e
m
en
ts
o
f
s
i
g
n
al
w
it
h
N
ew
s
a
m
p
les
a
n
d
ca
n
b
e
m
o
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elled
as:
=
Φ
×
(
2
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T
o
r
ec
o
v
er
th
e
o
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ig
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al
s
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al
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th
e
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e
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at
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l
s
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o
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e
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m
th
e
s
m
a
l
l
n
u
m
b
er
(
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ew
)
,
th
e
b
ig
n
u
m
b
er
(
N
)
ca
n
b
e
p
r
e
d
icted
d
u
e
to
th
e
s
p
r
ea
d
in
g
ass
u
m
p
t
i
o
n
.
T
h
is
eq
u
atio
n
i
s
co
n
s
id
er
ed
an
o
p
ti
m
is
ed
p
r
o
b
le
m
to
ad
d
r
ess
th
is
p
r
o
b
le
m
,
as
f
o
llo
w
s
:
̃
=
a
r
g
min
=
Φ
×
‖
‖
1
=
Φ
×
(
3
)
w
h
er
e
̃
is
t
h
e
r
ec
o
n
s
tr
u
c
ted
s
ig
n
al
an
d
‖
‖
=
√
∑
|
|
is
th
e
ℒ
n
o
r
m
o
f
x
COM
P
[
1
7
]
.
3.
T
H
E
P
RO
P
O
SE
D
H
YB
RID
CO
M
P
SS
SCH
E
M
E
B
asicall
y
,
t
h
e
C
OM
P
SS
i
s
ap
p
lied
to
ca
p
tu
r
e
u
s
ef
u
l
d
ata
(
in
ti
m
e
o
r
f
r
eq
u
en
c
y
d
o
m
ain
s
)
,
s
o
th
ese
d
ata
ar
e
co
m
p
r
ess
ed
to
co
u
n
t
er
th
e
s
h
o
r
tco
m
i
n
g
s
o
f
t
h
e
b
an
d
w
id
th
.
T
h
u
s
,
it
s
h
o
u
ld
b
e
co
m
p
r
es
s
ed
b
y
b
ase
s
w
it
h
s
u
p
er
io
r
r
eso
lu
tio
n
th
at
k
ee
p
th
e
n
ec
es
s
ar
y
m
ea
s
u
r
em
en
ts
in
o
r
d
er
to
r
ed
u
ce
th
e
co
s
t.
T
h
e
p
r
o
p
o
s
ed
C
OM
P
SS
s
y
s
te
m
h
as
b
ee
n
ac
h
iev
ed
t
h
r
o
u
g
h
t
w
o
ca
s
ca
d
ed
s
tag
e
s
:
DDW
T
f
o
llo
w
ed
b
y
C
DC
T
f
o
r
o
n
e
SU
(
n
o
n
-
co
o
p
er
ativ
e
s
y
s
te
m
)
a
n
d
DDW
T
f
o
llo
w
ed
b
y
MCD
C
T
f
o
r
m
u
lti
SU
s
(
co
o
p
er
ativ
e
s
y
s
te
m
)
,
a
s
s
h
o
w
n
i
n
Fig
u
r
es 3
an
d
4
,
r
esp
ec
tiv
el
y
.
Fig
u
r
e
3
.
H
y
b
r
id
C
OM
P
SS
f
o
r
o
n
e
SU b
lo
ck
d
iag
r
a
m
Fig
u
r
e
4
.
H
y
b
r
id
C
OM
P
SS
f
o
r
m
u
lti SU
s
b
lo
ck
d
iag
r
a
m
T
h
e
f
ir
s
t
s
tag
e
e
s
s
e
n
tiall
y
d
e
p
en
d
s
o
n
W
T
,
s
in
ce
it
ca
n
a
n
al
y
s
e
t
h
e
s
i
g
n
al
to
co
ef
f
icie
n
ts
a
s
t
h
eir
f
r
eq
u
en
c
ies.
Fo
r
in
s
tan
ce
,
th
e
f
ir
s
t
d
ec
o
m
p
o
s
itio
n
le
v
el
c
an
ca
te
g
o
r
is
e
t
h
e
s
ig
n
al
in
to
t
w
o
co
m
p
o
n
e
n
ts
:
lo
w
f
r
eq
u
e
n
c
y
t
h
at
co
n
tain
s
t
h
e
tr
a
f
f
ic,
an
d
h
i
g
h
f
r
eq
u
en
c
y
t
h
at
co
n
tai
n
s
t
h
e
n
o
is
e
[
1
9
]
.
T
h
e
Dau
b
ec
h
ie
s
w
a
v
elet
s
t
y
p
e
is
a
h
i
g
h
er
b
ase
w
a
v
elet
o
r
d
er
r
ath
er
th
an
it
is
o
r
th
o
g
o
n
al.
I
t
is
s
m
o
o
th
er
an
d
h
as
b
etter
f
r
eq
u
en
c
y
lo
ca
lis
atio
n
t
h
an
o
t
h
er
s
[
2
0
]
.
T
h
e
Dau
b
ec
h
ies
b
ases
w
er
e
e
x
tr
ac
ted
u
s
i
n
g
th
e
p
y
r
a
m
id
al
g
o
r
ith
m
,
w
h
ic
h
w
a
s
i
n
v
esti
g
ated
b
y
Ha
n
s
e
n
,
[
2
1
]
an
d
o
t
h
er
s
.
T
h
e
p
y
r
a
m
id
al
g
o
r
ith
m
g
e
n
er
ates
th
e
b
ases
ac
co
r
d
in
g
to
th
e
r
eq
u
ir
ed
o
r
d
er
n
u
m
b
er
f
r
o
m
th
e
b
ase
s
d
1
,
d
2
,
d
3
,
an
d
d
4
.
Nex
t,
th
e
n
e
w
b
ases
w
er
e
cr
ea
ted
f
r
o
m
av
er
ag
in
g
(
as
d
1
+
d
2
/2
)
,
an
d
th
e
n
e
w
b
ase
is
th
en
m
o
v
ed
u
p
to
a
n
e
w
le
v
el
to
w
ar
d
s
th
e
to
p
o
f
th
e
p
y
r
a
m
id
.
F
r
o
m
d
if
f
er
e
n
cin
g
(
as
d
1
-
d
2
/
2
)
,
th
e
n
e
w
b
a
s
e
is
m
o
v
ed
d
o
w
n
to
a
n
e
w
le
v
el
to
w
a
r
d
s
th
e
b
o
tto
m
o
f
th
e
p
y
r
a
m
id
,
an
d
s
o
o
n
in
o
r
d
er
to
b
u
ild
th
e
p
y
r
a
m
id
[
2
1
]
.
T
o
b
u
ild
th
e
DDW
T
m
atr
i
x
,
Φ
1
,
as
s
tated
in
th
e
p
y
r
a
m
id
alg
o
r
ith
m
,
th
e
n
u
m
b
er
o
f
b
ases
is
r
eq
u
ir
ed
to
b
e
th
e
s
am
e
as
t
h
e
n
u
m
b
er
o
f
eq
u
atio
n
s
i
n
o
r
d
er
t
o
o
b
tain
th
eir
r
ates.
T
h
e
b
asis
v
ec
to
r
s
o
f
th
e
p
r
o
p
o
s
e
d
m
atr
i
x
s
h
o
u
ld
b
e
p
er
p
en
d
icu
lar
,
i.e
.
,
th
e
r
esu
lt
o
f
th
e
i
n
n
er
p
r
o
d
u
ct
b
et
w
ee
n
e
v
er
y
t
w
o
v
ec
to
r
s
eq
u
als
to
ze
r
o
.
T
h
e
m
ain
f
o
u
r
b
ases
r
ate
s
w
e
r
e
o
b
tain
ed
in
[
2
2
]
b
y
I
.
Dau
b
ec
h
ies,
as
f
o
llo
w
s
;
d
1
=
(
1
+
√
3
)
/4
,
d
2
=
(3
+
√
3
)
/4
,
d
3
=
(
3
-
√
3
)
/4
an
d
d
4
=
(
1
-
√
3
)
/4
.
T
o
co
m
p
lete
th
e
DDW
T
m
atr
i
x
f
o
r
1
0
2
4
×1
0
2
4
v
ec
to
r
s
,
th
e
o
th
er
b
ases
ca
n
b
e
co
n
s
tr
u
cted
ac
co
r
d
in
g
to
th
e
p
y
r
a
m
id
al
g
o
r
ith
m
.
T
h
e
s
ca
lin
g
f
u
n
c
tio
n
an
d
t
h
e
th
r
ee
w
a
v
elet
co
ef
f
icie
n
t
s
ca
n
b
e
f
o
r
m
u
lated
as f
o
llo
w
s
:
1
=
(
∑
4
=
1
+
2
∑
3
4
=
(
4
)
+
1
+
∑
=
(
3
/
4
)
+
1
)
/
(
5
2
⁄
)
(
4
)
1
=
(
2
∑
4
=
1
−
∑
3
4
=
(
4
)
+
1
+
2
∑
=
(
3
/
4
)
+
1
)
/
(
5
2
⁄
)
(
5
)
2
=
(
−
∑
/
4
=
1
+
∑
=
(
3
/
4
)
+
1
)
/
(
6
)
C
o
m
p
a
r
i
n
g
&
D
e
c
i
s
i
o
n
D
D
W
T
P
S
D
P
r
e
d
e
f
i
n
e
d
T
h
r
e
s
h
o
l
d
E
s
t
i
m
a
t
i
o
n
F
i
l
t
e
r
e
d
R
e
c
e
i
v
e
d
S
i
g
n
a
l
C
D
C
T
C
o
m
p
a
r
i
n
g
&
D
e
c
i
s
i
o
n
D
D
W
T
P
S
D
P
r
e
d
e
f
i
n
e
d
T
h
r
e
s
h
o
l
d
E
s
t
i
m
a
t
i
o
n
F
i
l
t
e
r
e
d
R
e
c
e
i
v
e
d
S
i
g
n
a
l
M
C
D
C
T
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
6
,
Dec
em
b
er
2
0
2
0
:
5
8
9
9
-
5
9
0
8
5902
3
=
(
−
∑
/
2
=
(
/
4
)
+
1
+
∑
3
/
4
=
(
/
2
)
+
1
)
/
(
7
)
I
n
g
e
n
er
al,
th
e
f
o
llo
w
in
g
m
o
d
el
ca
n
b
e
ap
p
lied
f
o
r
v
ar
io
u
s
s
i
g
n
al
le
n
g
t
h
s
:
2
(
2
)
=
(
2
)
=
(
−
∑
=
1
+
∑
2
/
=
/
+
1
)
/
(
/
2
⁄
)
(
8
)
T
h
e
n
e
w
f
as
h
io
n
o
f
r
ec
ei
v
ed
P
U
s
ig
n
al,
Y
,
co
n
tai
n
s
o
n
l
y
tr
af
f
ic
w
i
th
h
al
f
o
f
th
e
le
n
g
th
,
N
COM
P
,
o
f
th
e
o
r
ig
i
n
al
r
ec
ei
v
ed
P
U
s
ig
n
al
u
s
i
n
g
o
n
e
le
v
el,
as
f
o
llo
w
s
:
=
(
9
)
=
2
(
1
0
)
T
h
e
p
r
ev
io
u
s
s
tag
e
o
f
s
p
ec
tr
u
m
co
m
p
r
ess
io
n
r
ed
u
ce
s
t
h
e
co
n
s
u
m
ed
p
o
w
er
in
th
e
f
r
o
n
t
en
d
u
p
to
5
0
%.
I
n
ad
d
itio
n
,
t
h
e
co
m
p
r
e
s
s
ed
s
p
ec
tr
u
m
co
n
tai
n
s
a
b
ig
a
m
o
u
n
t
o
f
tr
a
f
f
ic
p
o
w
er
w
i
th
a
litt
le
a
m
o
u
n
t
o
f
n
o
is
e
p
o
w
er
s
i
n
ce
t
h
e
r
es
u
lta
n
t
s
p
ec
tr
u
m
co
n
s
er
v
es
th
e
s
i
g
n
al
m
ea
s
u
r
e
m
e
n
ts
.
C
o
n
s
eq
u
en
tl
y
,
its
d
etec
tio
n
p
er
f
o
r
m
a
n
ce
g
ets b
etter
in
lo
w
SNR
.
On
t
h
e
o
t
h
er
h
an
d
,
u
s
i
n
g
t
h
e
C
DC
T
alg
o
r
it
h
m
as
t
h
e
s
ec
o
n
d
co
m
p
r
ess
io
n
s
ta
g
e
o
m
its
c
o
ef
f
icie
n
t
s
th
at
h
a
v
e
ze
r
o
th
r
es
h
o
ld
r
ate.
T
h
is
s
tag
e
ca
n
s
i
g
n
if
ican
t
l
y
r
e
d
u
ce
th
e
n
o
i
s
e
v
ar
ia
n
ce
an
d
p
o
w
er
co
n
s
u
m
p
tio
n
w
it
h
o
u
t
s
i
g
n
al
r
eso
l
u
tio
n
,
s
p
ec
if
icatio
n
s
a
n
d
m
ea
s
u
r
e
m
en
ts
d
eter
io
r
atio
n
[
2
3
]
.
Mo
r
eo
v
er
,
it
en
h
a
n
ce
s
th
e
d
etec
tio
n
p
er
f
o
r
m
an
ce
i
n
lo
w
er
SNR
.
T
h
u
s
,
ap
p
l
y
i
n
g
t
h
e
s
ec
o
n
d
co
m
p
r
es
s
io
n
s
ta
g
e
o
n
t
h
e
co
m
p
r
es
s
ed
s
p
ec
tr
u
m
,
w
h
ic
h
is
a
r
es
u
lt
o
f
th
e
f
ir
s
t
co
m
p
r
es
s
io
n
s
ta
g
e
(
DDW
T
)
,
to
o
b
tain
a
b
ig
co
m
p
r
ess
io
n
r
atio
w
ith
n
e
w
len
g
t
h
,
N
e
w
,
as
f
o
llo
w
s
:
[
]
=
(
(
−
1
)
[
0
]
√
2
+
∑
[
]
c
os
(
(
2
+
1
)
2
)
−
1
=
1
)
k
=
0
,
1
,
…
,
K
–
1
(
1
1
)
As a
m
atr
i
x
f
o
r
m
,
t
h
e
n
ex
t
m
o
d
el
co
m
p
r
ess
e
s
th
e
s
tr
ea
m
b
y
N
ew
:
=
(
1
2
)
T
h
u
s
,
th
e
h
y
b
r
id
C
OM
P
SS
s
ch
e
m
e
ca
n
b
e
d
escr
ib
ed
as
a
s
tr
u
ct
u
r
e,
as
s
h
o
w
n
i
n
Fi
g
u
r
e
5
.
Fin
all
y
,
t
h
e
test
s
tatis
t
ic
f
o
r
th
e
f
i
n
al
co
m
p
r
ess
ed
s
p
ec
tr
u
m
r
es
u
lts
ca
n
b
e
ex
p
r
ess
ed
to
test
th
e
d
et
ec
tio
n
p
er
f
o
r
m
a
n
ce
,
as sh
o
w
n
i
n
th
e
n
ex
t e
q
u
atio
n
.
=
1
∑
|
[
]
|
2
−
1
=
0
(
1
3
)
Fig
u
r
e
5
.
H
y
b
r
id
C
OM
P
SS
s
tr
u
ctu
r
e
B
y
s
u
b
s
t
itu
tin
g
P
S
D
COM
P
an
d
N
ew
in
to
t
h
e
C
D
C
T
f
o
r
n
o
n
-
co
o
p
er
ativ
e
ca
s
e
an
d
M
C
DC
T
f
o
r
co
o
p
er
ativ
e
ca
s
e
alg
o
r
ith
m
s
,
th
e
ca
s
ca
d
ed
s
y
s
te
m
s
ca
n
ac
h
iev
e
a
lo
ca
l
d
ec
is
io
n
f
o
r
th
e
f
ir
s
t
al
g
o
r
ith
m
a
n
d
a
g
lo
b
al
d
ec
is
io
n
f
o
r
th
e
s
ec
o
n
d
o
n
e
as
d
escr
ib
ed
b
elo
w
.
Ho
w
ev
er
,
t
h
e
C
DC
T
alg
o
r
ith
m
eli
m
i
n
ate
s
th
e
co
ef
f
icie
n
ts
t
h
at
h
a
v
e
a
th
r
esh
o
ld
v
alu
e
o
f
ze
r
o
o
r
ap
p
r
o
ac
h
es
to
ze
r
o
.
A
f
ter
th
at,
t
h
e
alg
o
r
ith
m
o
b
tai
n
s
th
e
P
SD
w
h
ich
h
as
b
ee
n
co
m
p
ar
ed
w
it
h
t
h
e
p
r
ed
ef
in
ed
t
h
r
e
s
h
o
ld
to
s
en
s
e
th
e
P
U
s
i
g
n
al
a
n
d
id
en
ti
f
y
w
h
et
h
er
it is
p
r
esen
t o
r
ab
s
en
t,
as
s
h
o
wn
in
Fig
u
r
e
7
.
N
e
w
X
Ф
D
D
W
T
Z
N
C
O
M
P
N
N
Ф
D
C
D
T
N
C
O
M
P
N
e
w
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
C
o
mp
r
ess
ive
s
p
ec
tr
u
m
s
en
s
in
g
u
s
in
g
tw
o
-
s
ta
g
e
s
ch
eme
fo
r
co
g
n
i
tive
r
a
d
io
n
etw
o
r
ks (
Mo
n
ta
d
a
r
A
b
a
s
Ta
h
er)
5903
A
s
p
r
ev
i
o
u
s
ly
m
en
t
i
o
n
e
d
,
e
ac
h
s
ig
n
a
l
c
an
b
e
r
e
p
r
e
s
e
n
t
e
d
b
y
a
n
u
m
b
e
r
o
f
DC
T
c
o
e
f
f
ic
i
en
ts
to
e
v
a
lu
ate
t
h
e
r
ec
e
iv
e
d
PU
s
i
g
n
al
is
f
i
r
s
t
m
a
th
em
at
i
ca
l
ly
t
r
an
s
f
o
r
m
e
d
t
o
a
n
o
th
e
r
d
o
m
a
in
u
s
in
g
DC
T
-
I
I
f
am
ily
f
u
s
i
o
n
:
[
]
=
(
(
−
1
)
[
0
]
√
2
+
∑
[
]
c
os
(
(
2
+
1
)
2
)
−
1
=
1
)
√
2
=
0
,
1
,
…
,
−
1
(
1
4
)
Af
ter
th
a
t,
th
e
n
e
w
s
ig
n
al
Y
[
k
]
b
ec
o
m
e
s
h
o
r
ter
d
u
e
to
elim
i
n
atio
n
o
f
t
h
e
ze
r
o
th
r
es
h
o
ld
,
ca
n
b
e
m
o
d
elled
as f
o
llo
w
s
:
[
]
=
[
]
=
0
,
1
,
…
,
−
1
(
1
5
)
Nex
t,
t
h
e
test
s
tat
is
tic
f
o
r
ac
ti
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Fi
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h
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l
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at
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D
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iq
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atica
l
a
n
d
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w
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m
p
u
tatio
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co
m
p
le
x
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y
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2
4
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.
Fig
u
r
e
6
.
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r
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p
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D
b
ased
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o
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f
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ap
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ap
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ated
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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8708
I
n
t J
E
lec
&
C
o
m
p
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n
g
,
Vo
l.
10
,
No
.
6
,
Dec
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b
er
2
0
2
0
:
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8
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Af
ter
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s
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8
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Fu
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η
[
2
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cc
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(
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s
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2
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v
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ef
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it,
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p
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s
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u
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d
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3
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b
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th
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cr
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ac
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s
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s
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s
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L
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(
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01
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7
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b
s
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te
t
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e
s
h
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(
2
3
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to
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ig
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t
t
h
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t
h
f
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r
th
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d
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g
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L
D
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(
+
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lt
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t
h
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n
ce
lled
co
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f
f
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f
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t
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p
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r
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n
t
h
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en
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r
elatio
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d
el
ca
n
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e
s
tated
as f
o
llo
w
s
:
=
[
]
⨂
[
]
=
0
,
1
,
…
,
+
−
1
(
2
9
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w
h
er
e
⨂
d
en
o
tes li
n
ea
r
cr
o
s
s
-
co
r
r
elatio
n
o
p
er
atio
n
.
As
a
f
o
r
e
m
e
n
tio
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ed
,
ea
c
h
SU
s
en
d
s
its
lo
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l
d
ec
is
io
n
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th
e
f
u
s
io
n
ce
n
t
er
(
FC
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w
h
ic
h
d
ec
id
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a
g
lo
b
al
d
ec
is
io
n
.
Ho
w
e
v
er
,
t
h
e
MCD
C
T
alg
o
r
ith
m
eli
m
in
a
tes
th
e
co
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f
icie
n
t
s
th
a
t
h
a
v
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a
th
r
esh
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ld
v
a
lu
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o
f
ze
r
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o
r
ap
p
r
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ac
h
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ze
r
o
a
cc
o
r
d
in
g
to
th
e
n
u
m
b
er
o
f
S
Us.
Af
ter
th
a
t,
th
e
alg
o
r
it
h
m
o
b
tain
s
th
e
g
lo
b
al
d
ec
is
io
n
v
ia
O
R
-
r
u
le,
a
n
d
s
en
d
s
its
d
ec
is
io
n
to
all
SU
s
,
as s
h
o
w
n
i
n
Fi
g
u
r
e
7
.
T
h
e
FC
m
u
s
t
d
ec
id
e
th
e
p
r
ev
io
u
s
d
esire
v
alu
e
s
f
r
o
m
(
2
0
)
an
d
(
2
3
)
ea
ch
u
s
er
s
h
o
u
ld
m
a
k
e
a
lo
ca
l
d
ec
is
io
n
r
eg
ar
d
in
g
t
h
e
g
lo
b
al
o
n
e.
T
h
er
ef
o
r
e,
th
e
lo
ca
l
d
ec
is
io
n
ca
n
b
e
f
o
r
m
u
lated
b
y
u
s
in
g
a
C
G
F
A
R
a
nd
a
co
n
s
tan
t g
lo
b
al
d
etec
tio
n
r
at
e
(
C
GDR)
f
r
o
m
(
2
0
)
an
d
(
2
3
)
as f
o
llo
w
s
:
=
1
−
(
1
−
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1
=
1
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99
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=
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−
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1
−
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−
(
0
.
1
)
1
(
3
1
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
C
o
mp
r
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s
p
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tr
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m
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ks (
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r
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b
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s
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5905
Fig
u
r
e
7
.
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r
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ased
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MCD
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r
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s
h
o
u
ld
d
ec
id
e
lo
ca
lly
f
r
o
m
(
3
0
)
,
(
3
1
)
to
h
elp
th
e
FC
to
d
ec
id
e
o
n
d
esire
d
g
lo
b
al
r
atio
s
.
4.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
I
n
t
h
is
s
ec
tio
n
,
a
s
y
s
te
m
-
lev
e
l
s
i
m
u
lat
io
n
w
a
s
b
u
ilt
b
y
u
s
i
n
g
MA
T
L
A
B
to
ac
h
ie
v
e
th
e
s
p
ec
if
icatio
n
s
o
f
C
R
N
s
tan
d
ar
d
[
1
1
]
.
T
h
e
s
im
u
latio
n
e
n
v
ir
o
n
m
e
n
t
co
n
s
id
er
ed
an
u
p
-
lin
k
tr
an
s
m
is
s
io
n
f
r
o
m
P
U
eq
u
ip
m
e
n
t
,
w
h
ic
h
i
s
lo
ca
ted
i
n
s
o
m
e
r
eg
io
n
.
T
h
is
r
e
g
io
n
co
n
tai
n
ed
ab
o
u
t
1
0
0
SU
d
ev
ices
an
d
w
a
s
co
v
e
r
ed
b
y
a
n
A
W
G
N
ch
an
n
el
f
o
r
v
ar
io
u
s
SNR
v
al
u
es f
r
o
m
ze
r
o
till
-
5
0
d
B
an
d
o
t
h
er
s
i
m
u
la
tio
n
p
ar
a
m
eter
s
as s
h
o
w
n
i
n
T
ab
le
1
.
T
ab
le
1
.
T
h
e
s
i
m
u
latio
n
p
ar
am
eter
s
Up
-
l
i
n
k
P
a
r
a
me
t
e
r
s
V
a
l
u
e
T
r
a
n
smissi
o
n
mo
d
e
2
K
mo
d
e
N
u
mb
e
r
o
f
F
F
T
2
0
4
8
sa
mp
l
e
s
B
a
n
d
w
i
d
t
h
6
,
7
,
a
n
d
8
M
H
z
S
a
mp
l
i
n
g
t
i
me
7
/
4
8
,
7
/
5
6
,
a
n
d
7
/
6
4
C
y
c
l
i
c
p
r
e
f
i
x
1
/
4
,
1
/
8
,
1
/
1
6
,
a
n
d
1
/
3
2
N
u
mb
e
r
o
f
su
b
c
a
r
r
i
e
r
s
1
7
0
5
sa
mp
l
e
s
M
o
d
u
l
a
t
i
o
n
s
c
e
n
a
r
i
o
s
Q
P
S
K
a
n
d
1
6
-
Q
A
M
C
h
a
n
n
e
l
t
y
p
e
A
W
G
N
c
h
a
n
n
e
l
S
N
R
-
50
–
0
d
B
4
.
1
.
De
t
ec
t
io
n per
f
o
rm
a
nce
f
o
r
f
ix
ed
Q
f
Fig
u
r
e
8
ex
h
ib
it
s
a
s
u
r
f
ac
e
p
lo
t
f
o
r
th
e
th
e
g
lo
b
al
p
r
o
b
a
b
ilit
y
o
f
d
etec
tio
n
v
er
s
u
s
th
e
n
u
m
b
er
o
f
SUs
an
d
SN
R
,
w
h
er
ea
s
th
e
g
lo
b
al
p
r
o
b
a
b
ilit
y
o
f
f
al
s
e
alar
m
is
c
o
n
s
ta
n
t
at
0
.
0
1
an
d
o
n
e
SU
o
n
l
y
.
Fro
m
Fig
u
r
e
8
,
it
ca
n
b
e
d
ed
u
ce
d
th
at
th
e
p
er
f
o
r
m
a
n
ce
is
e
x
ce
lle
n
t
f
o
r
ev
er
y
SNR
an
d
SU
n
u
m
b
er
th
a
t
is
e
q
u
al
to
an
d
g
r
ea
ter
th
an
2
0
u
s
er
s
.
T
h
e
v
al
u
es
o
f
th
e
o
r
ig
in
al
s
tr
ea
m
,
f
ir
s
t
co
m
p
r
e
s
s
io
n
s
ta
g
e,
an
d
s
ec
o
n
d
co
m
p
r
ess
io
n
s
ta
g
e
len
g
th
s
ar
e
li
s
ted
in
T
ab
le
2
,
w
h
er
e
ϵ
h
,
a
n
d
ϵ
l
d
en
o
te
t
h
e
h
i
g
h
er
an
d
lo
w
er
r
e
m
o
v
ed
p
o
w
er
r
atio
s
,
r
esp
ec
tiv
el
y
.
Fro
m
T
ab
le
2
,
th
e
r
es
u
lta
n
t
c
o
m
p
r
es
s
io
n
r
atio
s
ar
e
ar
o
u
n
d
8
0
%,
8
0
.
5
%
,
8
1
.
5
%,
an
d
8
1
%
f
o
r
th
e
1
6
-
Q
A
M
(G
=
4
)
,
QP
SK
(
G
=
4
)
,
1
6
-
QAM
(
G
=
3
2
)
,
an
d
QP
SK
(
G
=
3
2
)
,
s
ce
n
ar
io
s
r
esp
ec
tiv
e
l
y
.
T
h
is
f
i
g
u
r
e
also
s
h
o
ws
th
at
th
e
n
o
is
e
v
ar
ia
n
ce
is
s
i
g
n
i
f
ica
n
tl
y
r
ed
u
ce
d
in
b
o
th
s
tag
e
s
,
esp
ec
i
all
y
f
o
r
h
ig
h
n
u
m
b
er
s
o
f
SU
s
in
th
e
C
R
N.
C
o
m
p
a
r
i
n
g
&
D
e
c
i
s
i
o
n
P
S
D
P
r
e
d
e
f
i
n
e
d
T
h
r
e
s
h
o
l
d
E
s
t
i
m
a
t
i
o
n
F
i
l
t
e
r
e
d
R
e
c
e
i
v
e
d
S
i
g
n
a
l
M
C
D
C
T
C
o
m
p
a
r
i
n
g
&
D
e
c
i
s
i
o
n
P
S
D
P
r
e
d
e
f
i
n
e
d
T
h
r
e
s
h
o
l
d
E
s
t
i
m
a
t
i
o
n
M
C
D
C
T
C
o
m
p
a
r
i
n
g
&
D
e
c
i
s
i
o
n
P
S
D
P
r
e
d
e
f
i
n
e
d
T
h
r
e
s
h
o
l
d
E
s
t
i
m
a
t
i
o
n
M
C
D
C
T
S
U
m
S
U
1
S
U
2
.
.
.
F
C
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
6
,
Dec
em
b
er
2
0
2
0
:
5
8
9
9
-
5
9
0
8
5906
(
a)
(
b
)
Fig
u
r
e
8
.
Q
d
o
f
DDW
T
-
C
DC
T
,
Q
f
=
0
.
0
1
,
n
s
u
=
1
-
1
0
0
u
s
er
s
an
d
SNR
=
-
50
-
0
d
B
,
(
a)
G
=
¼
f
o
r
1
6
-
QA
M
s
ce
n
ar
i
o
,
(
b
)
G
=
¼
f
o
r
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P
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s
ce
n
ar
io
T
ab
le
2
.
Q
d
,
ϵ
h
,
an
d
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l
o
f
DDW
T
-
C
DC
T
f
o
r
Q
f
=
0
.
0
1
,
an
d
d
i
f
f
er
en
t
v
alu
e
s
o
f
c
y
clic
p
r
ef
i
x
16
-
Q
A
M
(
G
=
4)
Q
PSK
(
G
=
4)
16
-
Q
A
M
(
G
=
3
2
)
Q
PSK
(
G
=
3
2
)
N
=
2
5
6
0
ϵ
l
=
-
5
5
.
2
3
d
B
N
=
5
1
2
0
ϵ
l
=
-
6
3
d
B
N
=
2
1
1
2
ϵ
l
=
-
5
3
d
B
N
=
4
2
2
4
ϵ
l
=
-
6
0
d
B
N
CO
M
P
=
1
2
8
0
New
=
1117
N
CO
M
P
=
2
5
6
0
New
=
2318
N
CO
M
P
=
1
0
5
6
New
=
907
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CO
M
P
=
2
1
1
2
New
=
1879
New
/
ϵ
h
=
5
1
6
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
9
9
8
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
3
8
9
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
8
0
4
ϵ
h
=
-
2
0
d
B
4
.
2
.
De
t
ec
t
io
n per
f
o
rm
a
nce
f
o
r
f
ix
ed
SNR
T
h
e
s
u
r
f
ac
e
p
lo
t
o
f
Fi
g
u
r
e
9
s
h
o
w
s
th
e
R
O
C
v
er
s
u
s
t
h
e
n
u
m
b
er
o
f
SU
s
w
h
er
e
t
h
e
SN
R
i
s
co
n
s
ta
n
t
at
-
5
0
d
B
.
T
h
e
s
ig
n
al
i
s
w
atc
h
ed
b
y
a
n
u
m
b
er
o
f
SU
s
t
h
at
v
ar
ies
b
et
w
ee
n
1
an
d
1
0
0
u
s
er
s
alo
n
g
th
e
R
O
C
.
Fro
m
F
i
g
u
r
e
9
,
it
ca
n
b
e
s
ee
n
th
at
th
e
g
lo
b
al
d
etec
tio
n
p
r
o
b
ab
ilit
y
is
e
x
ce
lle
n
t
f
o
r
2
0
u
s
er
s
o
r
m
o
r
e
f
o
r
all
c
y
clic
p
r
ef
i
x
a
n
d
s
ce
n
ar
io
s
.
F
r
o
m
o
n
e
u
s
er
till
2
0
u
s
er
s
in
th
e
1
6
-
Q
A
M
s
ce
n
ar
io
,
t
h
e
g
l
o
b
al
p
r
o
b
ab
ilit
y
o
f
f
alse
alar
m
ch
a
n
g
es
f
r
o
m
ze
r
o
to
0
.
0
7
an
d
ze
r
o
t
o
0
.
0
3
,
an
d
th
e
r
esu
ltan
t
g
lo
b
al
d
etec
tio
n
p
r
o
b
a
b
ilit
y
is
f
r
o
m
0
.
9
to
1
.
I
n
ter
m
s
o
f
t
h
e
s
a
m
e
r
an
g
e
o
f
u
s
er
s
i
n
th
e
QP
SK
s
ce
n
ar
io
,
th
e
g
lo
b
al
f
al
s
e
alar
m
p
r
o
b
ab
ilit
y
v
ar
ies
b
et
w
ee
n
ze
r
o
to
0
.
0
7
an
d
ze
r
o
to
0
.
1
,
an
d
th
e
r
esu
lta
n
t
g
lo
b
al
d
etec
tio
n
p
r
o
b
ab
ilit
y
is
f
r
o
m
0
.
9
to
1
.
(
a)
(
b
)
Fig
u
r
e
9
.
Q
d
o
f
DDW
T
-
C
DC
T
,
SNR
=
-
5
0
d
B
,
n
s
u
=
1
-
1
0
0
u
s
er
s
an
d
Q
f
=
0
–
1
,
(
a)
G
=
¼
f
o
r
1
6
-
QA
M
s
ce
n
ar
i
o
,
(
b
)
G
=
¼
f
o
r
Q
P
SK
s
ce
n
ar
io
Fro
m
th
e
T
ab
le
3
,
it
ca
n
b
e
s
ee
n
th
a
t
th
e
f
ir
s
t
s
tag
e
ac
h
ie
v
ed
co
m
p
r
es
s
io
n
r
atio
s
t
h
at
ar
e
th
e
s
a
m
e
a
s
th
o
s
e
o
f
f
i
x
ed
g
lo
b
al
f
al
s
e
alar
m
p
r
o
b
ab
ilit
y
.
Fro
m
th
e
s
e
v
a
l
u
es
o
f
le
n
g
t
h
s
,
t
h
e
o
v
er
all
co
m
p
r
e
s
s
io
n
r
atio
s
ar
e
8
0
%,
8
0
%,
8
1
%,
an
d
8
1
% f
o
r
1
6
-
Q
AM
(
G
=
4
)
,
QP
SK (
G
=
4
)
,
1
6
-
Q
A
M
(
G
=
3
2
)
,
an
d
QP
SK
(
G
=
3
2
)
,
s
ce
n
ar
io
s
r
esp
ec
tiv
el
y
.
T
h
e
d
if
f
er
en
ce
i
n
r
atio
s
b
et
w
ee
n
th
e
ca
s
e
o
f
f
ix
ed
g
lo
b
al
f
al
s
e
alar
m
p
r
o
b
a
b
ilit
y
an
d
t
h
e
f
i
x
ed
SNR
e
x
h
ib
it
s
t
h
e
ef
f
ec
t o
f
t
h
e
SNR
w
all
f
o
r
d
if
f
er
en
t sce
n
ar
i
o
s
an
d
c
y
clic
p
r
ef
i
x
r
atio
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
C
o
mp
r
ess
ive
s
p
ec
tr
u
m
s
en
s
in
g
u
s
in
g
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o
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s
ta
g
e
s
ch
eme
fo
r
co
g
n
i
tive
r
a
d
io
n
etw
o
r
ks (
Mo
n
ta
d
a
r
A
b
a
s
Ta
h
er)
5907
T
ab
le
3
.
Q
d
,
ϵ
h
,
an
d
ϵ
l
o
f
DDW
T
-
C
DC
T
f
o
r
SNR
=
-
5
0
d
B
,
an
d
d
if
f
er
e
n
t
v
alu
e
s
o
f
c
y
clic
p
r
ef
ix
16
-
Q
A
M
(
G
=
4)
Q
PSK
(
G
=
4)
16
-
Q
A
M
(
G
=
3
2
)
Q
PSK
(
G
=
3
2
)
N
=
2
5
6
0
ϵ
l
=
-
5
5
.
2
3
d
B
N
=
5
1
2
0
ϵ
l
=
-
6
3
d
B
N
=
2
5
6
0
ϵ
l
=
-
5
5
.
2
3
d
B
N
=
5
1
2
0
ϵ
l
=
-
6
3
d
B
N
CO
M
P
=
1
2
8
0
New
=
1109
N
CO
M
P
=
2
5
6
0
New
=
2324
N
CO
M
P
=
1
2
8
0
New
=
1109
N
CO
M
P
=
2
5
6
0
New
=
2324
New
/
ϵ
h
=
5
1
7
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
1
0
0
2
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
5
1
7
ϵ
h
=
-
2
0
d
B
New
/
ϵ
h
=
1
0
0
2
ϵ
h
=
-
2
0
d
B
4
.
3
.
Dis
cus
s
io
n
A
ll
in
all,
t
h
e
p
r
o
p
o
s
ed
Hy
b
r
i
d
C
OM
P
SS
s
c
h
e
m
e
d
ec
r
ea
s
e
d
th
e
co
n
s
u
m
ed
p
o
w
er
b
y
a
r
atio
u
p
to
8
0
%
r
eg
ar
d
in
g
s
ig
n
al
m
ea
s
u
r
em
en
ts
.
T
h
u
s
,
th
e
p
o
llu
tio
n
o
f
r
ad
ii
th
at
e
m
it
s
f
r
o
m
eq
u
ip
m
en
t
w
ill
s
i
g
n
i
f
ican
tl
y
d
ec
r
ea
s
e.
Fu
r
th
er
m
o
r
e,
th
e
f
ir
s
t
s
ta
g
e
o
p
er
atio
n
s
ar
e
t
o
o
s
i
m
p
le
an
d
ar
e
eq
u
al
to
2
N
o
p
er
at
io
n
s
o
n
l
y
,
w
h
ich
i
s
th
e
a
v
er
ag
e
o
f
ad
d
itio
n
s
a
n
d
s
u
b
tr
ac
tio
n
s
.
T
h
e
s
ec
o
n
d
s
t
ag
e
i
n
cr
ea
s
ed
t
h
e
co
m
p
r
es
s
i
o
n
r
atio
,
en
h
a
n
ce
d
th
e
r
eliab
ilit
y
a
n
d
d
ec
r
ea
s
ed
t
h
e
v
ar
ian
ce
o
f
n
o
is
e
a
n
d
er
r
o
r
.
Mo
r
eo
v
er
,
b
o
th
s
tag
e
s
u
s
ed
s
m
al
ler
s
i
g
n
a
ls
a
n
d
th
en
r
eq
u
ir
ed
a
s
h
o
r
t
ti
m
e
to
s
en
s
e
al
th
o
u
g
h
t
h
er
e
ar
e
t
w
o
s
tag
es
a
n
d
n
o
t
o
n
l
y
o
n
e.
T
ab
le
4
s
u
m
m
ar
izes
th
e
d
if
f
er
e
n
t
p
ar
a
m
eter
s
a
m
o
n
g
t
h
e
H
y
b
r
id
C
OM
P
SS
,
t
h
e
s
tatio
n
ar
y
w
av
e
let
ed
g
e
tr
a
n
s
f
o
r
m
[
3
]
an
d
s
i
g
n
al
m
atr
i
x
esti
m
atio
n
[
1
0
]
alg
o
r
ith
m
s
.
T
ab
le
4
.
Q
d
,
ϵ
h
,
an
d
ϵ
l
o
f
DDW
T
-
C
DC
T
f
o
r
SNR
=
-
5
0
d
B
,
an
d
d
if
f
er
e
n
t
v
alu
e
s
o
f
c
y
clic
p
r
ef
ix
P
a
r
a
me
t
e
r
s
S
t
a
t
i
o
n
a
r
y
W
a
v
e
l
e
t
Ed
g
e
T
r
a
n
sf
o
r
m [
3
]
A
l
g
o
r
i
t
h
m
S
i
g
n
a
l
M
a
t
r
i
x
Es
t
i
m
a
t
i
o
n
[
1
0
]
A
l
g
o
r
i
t
h
m
H
y
b
r
i
d
C
O
M
P
S
S
C
o
mp
a
r
i
so
n
D
e
t
e
c
t
i
o
n
P
e
r
f
o
r
man
c
e
f
o
r
n
o
n
-
c
o
o
p
e
r
a
t
i
v
e
(
P
d
,
P
fa
)
(
0
.
8
,
0
.
0
9
)
N
/
A
(
0
.
9
,
0
.
0
1
)
H
y
b
r
i
d
C
O
M
P
S
S
sc
h
e
me
i
s
b
e
t
t
e
r
f
o
r
o
n
e
S
U
D
e
t
e
c
t
i
o
n
P
e
r
f
o
r
man
c
e
f
o
r
c
o
o
p
e
r
a
t
i
v
e
(
Q
d
,
Q
fa
)
N
/
A
(
0
.
6
7
,
0
.
0
1
)
(
0
.
9
9
,
0
.
0
1
)
H
y
b
r
i
d
C
O
M
P
S
S
sc
h
e
me
i
s
b
e
t
t
e
r
f
o
r
M
u
l
t
i
-
S
U
s
C
o
mp
r
e
ssi
o
n
R
a
t
i
o
5
0
%
7
0
%
8
1
.
5
%
H
i
g
h
e
r
C
o
mp
r
e
ssi
o
n
R
a
t
i
o
S
N
R
W
a
l
l
/
dB
-
10
1
-
50
S
N
R
W
a
l
l
l
o
w
e
r
5
t
i
me
s
S
U
N
u
mb
e
r
O
n
e
o
n
l
y
10
1
0
0
U
se
r
s
U
se
d
f
o
r
n
o
n
-
c
o
o
p
e
r
a
t
i
v
e
a
n
d
c
o
o
p
e
r
a
t
i
v
e
u
se
r
s
5.
CO
NCLU
SI
O
N
I
n
th
i
s
p
ap
er
,
a
h
y
b
r
id
C
OM
P
SS
s
ch
e
m
e
s
f
o
r
n
o
n
-
co
o
p
er
ativ
e
a
n
d
co
o
p
er
ativ
e
SUs
ar
e
d
er
iv
ed
.
Th
e
s
e
s
ch
e
m
e
s
w
er
e
co
n
s
tr
u
c
ted
u
s
i
n
g
t
w
o
s
ta
g
es
;
DDW
T
an
d
C
DC
T
/
MCD
C
T
f
o
r
o
n
e
s
ch
e
m
e
.
T
h
e
f
ir
s
t
s
tag
e
e
n
h
an
ce
d
t
h
e
d
etec
tio
n
p
er
f
o
r
m
a
n
ce
,
ac
h
iev
ed
5
0
%
co
m
p
r
es
s
io
n
r
atio
t
h
at
s
h
o
r
ten
ed
th
e
s
en
s
i
n
g
p
er
io
d
,
d
ec
r
ea
s
ed
th
e
n
o
is
e
v
ar
ian
ce
,
an
d
h
ad
lo
w
co
s
t
b
y
r
ed
u
cin
g
co
m
p
u
tati
o
n
al
co
m
p
lex
it
y
.
O
n
th
e
o
th
e
r
h
an
d
,
t
h
e
s
ec
o
n
d
s
tag
e
e
n
h
an
ce
d
th
e
d
etec
tio
n
p
er
f
o
r
m
a
n
c
e
f
u
r
t
h
er
m
o
r
e
to
ac
h
iev
e
u
p
t
o
3
0
%
co
m
p
r
ess
io
n
r
atio
(
8
0
%
o
v
er
all
co
m
p
r
ess
io
n
r
atio
)
,
r
ed
u
ce
d
th
e
SNR
w
al
l,
an
d
h
ad
to
o
lo
w
co
s
t
s
i
n
ce
it
d
ea
lt
w
it
h
h
al
f
o
f
th
e
o
r
ig
i
n
al
s
ig
n
al.
T
h
es
e
ac
h
i
ev
e
m
e
n
t
s
w
er
e
ac
h
iev
ed
f
o
r
b
o
th
m
o
d
u
latio
n
s
ce
n
ar
io
s
a
n
d
f
o
r
co
o
p
er
ativ
e
an
d
n
o
n
-
co
o
p
er
ativ
e
C
R
N
s
.
F
u
r
t
h
er
m
o
r
e,
a
r
ec
o
n
s
tr
u
ctio
n
o
f
th
e
s
i
g
n
al
w
as
n
o
t
r
eq
u
ir
ed
s
i
n
ce
b
o
th
h
y
b
r
id
C
OM
P
SS
s
c
h
e
m
es
k
ep
t th
e
n
e
ce
s
s
ar
y
m
ea
s
u
r
e
m
en
t
s
o
f
t
h
e
d
etec
t
ed
s
ig
n
al.
RE
F
E
R
E
NC
E
S
[1
]
I.
F
.
A
k
y
il
d
iz,
e
t
a
l.
,
“
Ne
X
t
g
e
n
e
ra
ti
o
n
/
d
y
n
a
m
ic
sp
e
c
tru
m
a
c
c
e
ss
/
c
o
g
n
it
iv
e
ra
d
io
w
irele
ss
n
e
tw
o
rk
s:
A
su
rv
e
y
,”
Co
mp
u
ter
n
e
two
rk
s
,
v
o
l.
5
0
,
n
o
.
1
3
,
p
p
.
2
1
2
7
-
2
1
5
9
,
2
0
0
6
.
[2
]
Q.
Zh
a
o
,
e
t
a
l
.
,
“
En
e
rg
y
e
ff
icie
n
c
y
o
f
c
o
m
p
re
ss
e
d
sp
e
c
tru
m
se
n
sin
g
in
w
id
e
b
a
n
d
c
o
g
n
it
iv
e
ra
d
io
n
e
tw
o
rk
s
,”
EURA
S
IP
J
o
u
r
n
a
l
o
n
W
ire
les
s Co
mm
u
n
ica
ti
o
n
s a
n
d
Ne
two
rk
in
g
,
v
o
l.
2
0
1
6
,
n
o
.
1
,
p
p
.
83
-
93
,
2
0
1
6
.
[3
]
S
.
E.
El
-
K
h
a
m
y
,
e
t
a
l.
,
“
A
sta
ti
o
n
a
ry
w
a
v
e
let
tran
s
f
o
r
m
a
p
p
ro
a
c
h
to
c
o
m
p
re
ss
e
d
sp
e
c
tru
m
se
n
si
n
g
in
c
o
g
n
it
iv
e
ra
d
io
,”
I
n
ter
n
a
t
io
n
a
l
J
o
u
r
n
a
l
o
f
C
o
mm
u
n
ic
a
ti
o
n
S
y
ste
ms
,
v
o
l.
3
0
,
n
o
.
7
,
p
.
e
3
1
4
0
,
2
0
1
6
.
[4
]
S
.
D.
B
o
rd
e
a
n
d
K
.
R
.
Jo
s
h
i
,
“
E
n
h
a
n
c
e
d
sig
n
a
l
d
e
tec
ti
o
n
slg
o
rit
h
m
u
sin
g
train
e
d
n
e
u
ra
l
n
e
tw
o
rk
f
o
r
c
o
g
n
it
iv
e
ra
d
i
o
re
c
e
iv
e
r
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
mp
u
ter
E
n
g
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
1
,
p
p
.
3
2
3
-
3
3
1
,
2
0
1
9
.
[5
]
P.
V
a
ra
d
e
,
e
t
a
l.
,
“
T
h
ro
u
g
h
p
u
t
M
a
x
i
m
iza
ti
o
n
o
f
Co
g
n
it
iv
e
Ra
d
io
M
u
lt
i
Re
lay
Ne
t
w
o
rk
w
it
h
In
terf
e
re
n
c
e
M
a
n
a
g
e
m
e
n
t
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
&
Co
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
8
,
n
o
.
4
,
p
p
.
2
2
3
0
-
2
2
3
8
,
2
0
1
8
.
[6
]
P
.
M
.
Na
m
,
e
t
a
l.
,
“
P
e
rf
o
r
m
a
n
c
e
o
f
c
lu
ste
r
-
b
a
se
d
c
o
g
n
it
iv
e
m
u
lt
ih
o
p
n
e
tw
o
rk
s
u
n
d
e
r
j
o
in
t
im
p
a
c
t
o
f
h
a
rd
w
a
re
n
o
ise
s
a
n
d
n
o
n
-
id
e
n
ti
c
a
l
p
rim
a
r
y
c
o
-
c
h
a
n
n
e
l
in
terf
e
re
n
c
e
,”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ica
ti
o
n
Co
m
p
u
t
in
g
El
e
c
tro
n
ics
a
n
d
C
o
n
tro
l,
v
o
l.
1
7
,
n
o
.
1
,
p
p
.
49
-
59
,
2
0
1
9
.
[7
]
E.
A
st
a
iza
,
e
t
a
l.
,
“
Co
m
p
re
ss
i
v
e
lo
c
a
l
w
id
e
b
a
n
d
sp
e
c
tru
m
s
e
n
sin
g
a
l
g
o
rit
h
m
f
o
r
m
u
lt
ian
ten
n
a
c
o
g
n
it
iv
e
ra
d
io
s
,”
i
n
2
0
1
6
8
th
IEE
E
L
a
ti
n
-
Ame
ric
a
n
Co
n
fer
e
n
c
e
o
n
Co
mm
u
n
ic
a
ti
o
n
s
(
L
AT
INCOM
)
,
p
p
.
1
-
6
,
2
0
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.
Wan
g
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e
t
a
l.
,
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m
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e
n
sin
g
o
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p
o
siti
o
n
in
g
tec
h
n
o
lo
g
y
,”
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n
2
0
1
6
IEE
E
In
ter
n
a
ti
o
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l
Co
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fer
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Ub
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[9
]
F.
L
i,
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t
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l.
,
“
A
No
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A
p
p
ro
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n
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sin
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a
tel
li
te S
y
ste
m
s
,”
M
a
th
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ma
ti
c
a
l
Pr
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g
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n
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rin
g
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p
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0
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6
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Evaluation Warning : The document was created with Spire.PDF for Python.
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S.
Re
n
,
e
t
a
l.
,
“
A
lo
w
c
o
m
p
l
e
x
it
y
se
n
sin
g
a
lg
o
rit
h
m
f
o
r
w
i
d
e
b
a
n
d
sp
a
rse
sp
e
c
tra
,”
IEE
E
Co
mm
u
n
ica
ti
o
n
s
L
e
tt
e
rs
,
v
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l.
2
1
,
n
o
.
1
,
p
p
.
92
-
95
,
2
0
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6
.
[1
1
]
L
.
X
u
,
e
t
a
l.
,
“
DRiV
E
-
in
g
to
t
h
e
In
tern
e
t:
Dy
n
a
m
ic r
a
d
io
f
o
r
IP
se
r
v
ice
s in
v
e
h
icu
lar en
v
iro
n
m
e
n
ts
,”
i
n
Pro
c
e
e
d
i
n
g
s
2
5
t
h
A
n
n
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a
l
IEE
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C
o
n
fer
e
n
c
e
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n
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o
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a
l
Co
mp
u
ter
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two
rk
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CN
2
0
0
0
,
p
p
.
2
8
1
-
2
8
9
,
2
0
0
0
.
[1
2
]
D.
P
in
e
d
a
a
n
d
C
.
He
rn
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n
d
e
z
,
“
C
o
g
n
it
iv
e
ra
d
i
o
f
o
r
T
V
W
S
u
sa
g
e
,”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
i
n
c
a
t
io
n
Co
mp
u
ti
n
g
El
e
c
tro
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ics
a
n
d
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o
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tro
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v
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l.
1
7
,
n
o
.
6
,
p
p
.
2
7
3
5
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2
7
4
6
,
2
0
1
9
.
[1
3
]
S.
Ra
z
m
i
a
n
d
N
.
P
a
r
h
izg
a
r
,
“
A
d
a
p
ti
v
e
re
so
u
rc
e
s
a
ss
ig
n
m
e
n
t
in
OFD
M
-
b
a
se
d
c
o
g
n
it
iv
e
r
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d
io
sy
ste
m
s
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
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l
o
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E
lec
trica
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a
n
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o
mp
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ter
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g
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g
,
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l.
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,
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o
.
3
,
p
p
.
1
9
3
5
-
1
9
4
3
,
2
0
1
9
.
[1
4
]
D.
T
.
Do
,
e
t
a
l.
,
“
Co
o
p
e
ra
ti
v
e
u
n
d
e
rlay
c
o
g
n
it
iv
e
r
a
d
io
a
ss
iste
d
NO
M
A
:
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c
o
n
d
a
ry
n
e
t
w
o
rk
i
m
p
ro
v
e
m
e
n
t
a
n
d
o
u
tag
e
p
e
rf
o
rm
a
n
c
e
,”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ica
t
io
n
Co
mp
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ti
n
g
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e
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tro
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ics
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n
d
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tro
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v
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l.
1
7
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5
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p
p
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2
1
4
7
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1
5
4
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0
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[1
5
]
E.
Ca
n
d
e
s
a
n
d
J
.
Ro
m
b
e
rg
,
“
S
p
a
rsity
a
n
d
in
c
o
h
e
re
n
c
e
in
c
o
m
p
re
ss
iv
e
sa
m
p
li
n
g
,”
In
v
e
rs
e
p
ro
b
lem
s
,
v
o
l.
2
3
,
n
o
.
3
,
p.
9
6
9
,
2
0
0
7
.
[1
6
]
E.
J.
Ca
n
d
è
s
a
n
d
M
.
B.
W
a
k
in
,
“
A
n
in
tro
d
u
c
ti
o
n
t
o
c
o
m
p
re
ss
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e
s
a
m
p
li
n
g
[
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se
n
sin
g
/sa
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p
li
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ra
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t
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g
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in
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o
m
m
o
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k
n
o
w
led
g
e
in
d
a
ta
a
c
q
u
isit
i
o
n
]
,”
IE
EE
sig
n
a
l
p
ro
c
e
ss
in
g
ma
g
a
zin
e
,
v
o
l.
2
5
,
n
o
.
2
,
p
p
.
21
-
30
,
2
0
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8
.
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7
]
F.
S
a
lah
d
in
e
,
e
t
a
l.
,
“
A
su
rv
e
y
o
n
c
o
m
p
re
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n
sin
g
tec
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n
iq
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s
f
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c
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g
n
it
iv
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ra
d
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o
n
e
tw
o
rk
s
,”
Ph
y
sic
a
l
Co
mm
u
n
ica
ti
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n
,
v
o
l
.
20
,
p
p
.
61
-
73
,
2
0
1
6
.
[1
8
]
D.
L
.
Do
n
o
h
o
,
“
Co
m
p
re
ss
e
d
se
n
sin
g
,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
in
f
o
rm
a
ti
o
n
t
h
e
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ry
,
v
o
l.
5
2
,
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o
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4
,
p
p
.
1
2
8
9
-
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3
0
6
,
2
0
0
6
.
[1
9
]
N.
U
m
e
z
u
,
e
t
a
l.
,
“
2
D
wa
v
e
let
tr
a
n
sf
o
r
m
d
a
ta
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o
m
p
re
ss
io
n
w
it
h
e
rro
r
le
v
e
l
g
u
a
ra
n
tee
f
o
r
Z
-
m
a
p
m
o
d
e
ls
,”
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o
u
rn
a
l
o
f
Co
m
p
u
t
a
ti
o
n
a
l
De
sig
n
a
n
d
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g
in
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rin
g
,
v
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l.
4
,
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o
.
3
,
p
p
.
2
3
8
-
2
4
7
,
2
0
1
7
.
[2
0
]
P.
S
a
ra
v
a
n
a
n
,
e
t
a
l.
,
“
Dig
it
a
l
im
a
g
e
wa
ter
m
a
r
k
in
g
u
sin
g
d
a
u
b
e
c
h
ies
wa
v
e
lets
,”
i
n
2
0
1
6
3
r
d
In
ter
n
a
ti
o
n
a
l
Co
n
fer
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n
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e
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n
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g
n
a
l
Pro
c
e
ss
in
g
a
n
d
In
te
g
ra
ted
Ne
two
rk
s (
S
PIN)
,
p
p
.
5
7
-
62
,
2
0
1
6
.
[2
1
]
Y.
Zh
e
n
g
,
e
t
a
l.
,
“
A
n
a
d
v
a
n
c
e
d
i
m
a
g
e
f
u
sio
n
a
lg
o
rit
h
m
b
a
se
d
o
n
w
a
v
e
let
tran
s
f
o
r
m
:
in
c
o
rp
o
ra
ti
o
n
w
it
h
P
CA
a
n
d
m
o
rp
h
o
lo
g
ica
l
p
ro
c
e
ss
in
g
,”
i
n
Im
a
g
e
p
ro
c
e
ss
in
g
:
a
lg
o
rit
h
ms
a
n
d
s
y
ste
ms
III
,
In
ter
n
a
ti
o
n
a
l
S
o
c
iety
fo
r
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ti
c
s
a
n
d
Ph
o
t
o
n
ics
,
v
o
l.
5
2
9
8
,
p
p
.
1
7
7
-
1
8
7
,
2
0
0
4
.
[2
2
]
I.
Da
u
b
e
c
h
ies
,
“
T
e
n
lec
tu
re
s
o
n
w
a
v
e
l
e
ts
,”
CBM
S
-
NS
F
re
g
io
n
a
l
Co
n
fer
e
n
c
e
S
e
rie
s
in
Ap
p
li
e
d
M
a
th
e
m
a
ti
c
s
,
v
o
l.
6
1
,
1
9
9
2
.
[2
3
]
S
.
A
.
G
o
les
tan
e
h
a
n
d
D
.
M
.
C
h
a
n
d
ler
,
“
No
-
re
f
e
re
n
c
e
q
u
a
li
ty
a
ss
e
ss
m
e
n
t
o
f
JP
EG
i
m
a
g
e
s
v
ia
a
q
u
a
li
ty
r
e
lev
a
n
c
e
map
,”
IEE
E
S
ig
n
a
l
Pro
c
e
ss
in
g
L
e
tt
e
rs
,
v
o
l.
2
1
,
n
o
.
2
,
p
p
.
1
5
5
-
1
5
8
,
2
0
1
3
.
[2
4
]
N.
R.
Ba
n
a
v
a
th
u
a
n
d
M
.
Z
.
A
.
K
h
a
n
,
“
Op
ti
m
a
l
n
-
o
u
t
-
of
-
k
v
o
ti
n
g
ru
le
f
o
r
c
o
o
p
e
ra
ti
v
e
sp
e
c
tru
m
se
n
s
in
g
w
it
h
e
n
e
rg
y
d
e
tec
to
r
o
v
e
r
e
rro
n
e
o
u
s
c
o
n
tr
o
l
c
h
a
n
n
e
l
,”
i
n
2
0
1
5
I
EE
E
8
1
st
Veh
icu
l
a
r
T
e
c
h
n
o
l
o
g
y
C
o
n
fer
e
n
c
e
(
VT
C
S
p
rin
g
)
,
p
p
.
1
-
5
,
2
0
1
5
.
[2
5
]
T
.
Yu
c
e
k
a
n
d
H
.
A
rsla
n
,
“
A
s
u
rv
e
y
o
f
sp
e
c
tru
m
s
e
n
sin
g
a
lg
o
rit
h
m
s
f
o
r
c
o
g
n
it
iv
e
r
a
d
io
a
p
p
li
c
a
ti
o
n
s
,”
IEE
E
c
o
mm
u
n
ica
t
io
n
s su
rv
e
y
s
&
tu
to
ria
ls
,
v
o
l.
1
1
,
n
o
.
1
,
p
p
.
1
1
6
-
1
3
0
,
2
0
0
9
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
M
o
n
ta
d
a
r
Aba
s
Ta
h
e
r
.
He
re
c
e
iv
e
d
th
e
B.
S
c
.
d
e
g
re
e
in
El
e
c
tro
n
ics
a
n
d
C
o
m
m
u
n
ica
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n
En
g
in
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g
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n
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h
e
M
.
S
c
.
d
e
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re
e
in
S
a
telli
te
E
n
g
in
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g
f
ro
m
A
l
-
Na
h
ra
in
Un
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e
rsity
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n
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sp
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e
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h
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ro
m
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n
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a
la
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a
,
in
2
0
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w
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s
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h
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o
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a
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m
m
u
n
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En
g
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rin
g
De
p
a
rtm
e
n
t,
Un
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e
r
sity
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f
Di
y
a
la.
His
m
a
in
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
OFDM
,
CDMA
,
M
C
-
CDMA
,
4
G
,
a
n
d
5
G
.
He
is
a
Re
v
ie
we
r
f
o
r
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m
e
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sp
e
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ted
in
tern
a
ti
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a
l
j
o
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r
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a
ls.
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o
h
a
m
m
a
d
Z
.
A
h
m
e
d
wa
s
Bo
rn
in
Am
m
a
n
(Jo
rd
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n
)
in
1
9
8
0
.
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re
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e
iv
e
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h
is
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h
.
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i
n
M
icr
o
e
n
g
in
e
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g
a
n
d
n
a
n
o
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lec
tro
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in
2
0
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f
ro
m
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h
e
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ti
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in
2
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1
9
.
His
m
a
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re
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rc
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in
tere
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re
Co
g
n
it
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e
Ra
d
io
,
(3
-
6)
G
sta
n
d
a
rd
s.
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