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201
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1451
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2.
RE
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[
2
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.
T
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
3
,
J
u
n
e
201
8
:
1
4
5
1
–
1459
1452
o
f
th
r
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d
if
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c
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3
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So
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ar
,
th
e
m
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t
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m
m
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l
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s
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ch
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n
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w
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a
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[
4
]
.
Si
m
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tu
d
ie
s
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a
v
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b
ee
n
co
n
d
u
cted
b
y
[
5
]
,
a
n
e
w
s
u
m
-
of
-
s
in
u
s
o
id
s
s
tatis
tical
s
i
m
u
lat
io
n
m
o
d
el
s
ar
e
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n
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o
d
u
ce
d
f
o
r
R
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ad
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n
g
ch
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n
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s
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co
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p
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of
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s
in
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s
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id
(
SO
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s
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lat
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m
o
d
el
f
o
r
R
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h
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t f
ad
in
g
c
h
an
n
el
s
was p
r
o
p
o
s
ed
b
y
[
6
]
.
T
h
e
p
r
o
p
ag
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n
tak
es
p
lace
in
ar
ea
s
w
h
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s
p
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s
el
y
p
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w
it
h
s
ca
tter
s
.
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h
e
y
s
t
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d
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th
e
s
tatis
t
ical
p
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[
7
]
.
A
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m
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c
h
an
n
el
s
an
d
MS
d
y
n
a
m
i
cs
w
a
s
p
r
o
p
o
s
ed
b
y
[
8
]
.
3.
P
RO
P
O
SE
D
SI
M
UL
A
T
I
O
N
AP
P
RO
ACH
T
h
e
p
r
o
p
o
s
ed
s
i
m
u
latio
n
ap
p
r
o
ac
h
ca
n
b
e
d
i
v
id
ed
in
to
t
w
o
m
ai
n
s
ta
g
e
s
s
u
c
h
as:
ch
a
n
n
el
an
d
m
o
b
ile
ch
an
n
el.
R
a
y
lei
g
h
f
ad
i
n
g
c
h
a
n
n
el
ca
n
b
e
d
i
v
id
ed
in
to
A
W
GN
an
d
s
p
ac
e
lo
s
s
w
h
ile
m
o
b
ile
ch
a
n
n
e
l
ca
n
b
e
d
iv
id
ed
in
to
f
lat
f
ad
in
g
a
n
d
s
el
ec
tiv
e
f
ad
in
g
as s
h
o
w
n
i
n
Fi
g
u
r
e
1
.
Fig
u
r
e
1
.
T
h
e
s
tag
es
o
f
p
r
o
p
o
s
ed
s
i
m
u
latio
n
ap
p
r
o
ac
h
3
.
1
.
Ra
y
leig
h f
a
din
g
cha
nn
el
R
a
y
le
ig
h
f
ad
i
n
g
ch
a
n
n
e
l
r
ef
l
ec
ts
th
e
f
ad
in
g
is
ca
u
s
ed
b
y
m
u
ltip
ath
r
ec
ep
tio
n
.
T
h
er
eb
y
,
R
a
y
lei
g
h
f
ad
in
g
ch
a
n
n
el
u
n
d
er
tak
es
t
h
at
th
e
m
a
g
n
it
u
d
e
o
f
a
s
ig
n
al
w
h
ich
h
a
s
b
ee
n
p
ass
ed
t
h
r
o
u
g
h
tr
an
s
m
i
s
s
io
n
m
ed
iu
m
w
i
ll
d
if
f
er
r
an
d
o
m
l
y
,
o
r
f
ad
e,
ac
co
r
d
in
g
to
a
R
a
y
lei
g
h
d
is
tr
ib
u
tio
n
.
As
w
ell
as,
R
a
y
leig
h
f
ad
in
g
d
ef
in
ed
a
s
a
r
ea
s
o
n
ab
le
m
o
d
el
w
h
e
n
th
er
e
ar
e
m
an
y
o
b
j
ec
ts
in
t
h
e
en
v
ir
o
n
m
e
n
t
w
h
ic
h
h
a
s
s
ca
tter
ed
th
e
r
ad
io
s
ig
n
al
b
ef
o
r
e
it
ar
r
iv
es
at
th
e
r
ec
eiv
er
.
W
h
e
n
th
er
e
is
n
o
d
o
m
i
n
a
n
t
l
in
e
-
of
-
s
ig
h
t
p
r
o
p
a
g
atio
n
b
et
w
ee
n
t
h
e
tr
an
s
m
itter
a
n
d
r
ec
eiv
er
,
R
a
y
l
eig
h
f
ad
i
n
g
c
h
an
n
el
i
s
m
o
s
t a
p
p
licab
le.
3
.
1
.
1
.
AWG
N
cha
nn
el
T
h
e
A
W
GN
C
h
an
n
el
b
lo
ck
p
r
esen
ts
w
h
ite
Ga
u
s
s
ia
n
n
o
is
e
to
a
r
ea
l
o
r
co
m
p
lex
i
n
p
u
t
s
ig
n
al.
W
h
e
n
th
e
i
n
p
u
t
s
ig
n
al
i
s
r
ea
l,
th
is
b
l
o
ck
p
r
esen
ts
r
ea
l
Gau
s
s
ia
n
n
o
is
e
an
d
g
en
er
ate
s
a
r
ea
l
o
u
tp
u
t
s
ig
n
al.
W
h
ile
t
h
e
in
p
u
t
s
i
g
n
al
i
s
co
m
p
le
x
,
th
is
b
lo
ck
p
r
esen
ts
co
m
p
le
x
Ga
u
s
s
ian
n
o
is
e
a
n
d
g
e
n
er
ates
a
co
m
p
lex
o
u
tp
u
t
s
ig
n
al.
T
h
is
b
lo
ck
r
ec
eiv
es
it
s
s
a
m
p
le
ti
m
e
f
r
o
m
t
h
e
i
n
p
u
t
s
ig
n
al
.
T
h
is
b
lo
ck
ac
ce
p
ts
a
s
ca
lar
-
v
a
lu
ed
,
v
ec
to
r
,
o
r
m
atr
i
x
i
n
p
u
t
s
i
g
n
a
l
w
it
h
a
d
ata
k
i
n
d
o
f
k
i
n
d
s
in
g
le
o
r
d
o
u
b
l
e.
T
h
e
o
u
tp
u
t
s
i
g
n
al
r
ec
eiv
e
s
p
o
r
t
d
ata
ty
p
e
s
f
r
o
m
th
e
s
i
g
n
als t
h
at
d
r
iv
e
t
h
e
b
lo
ck
.
I
n
t
h
is
s
t
u
d
y
,
th
e
r
ea
l
a
n
d
i
m
ag
in
ar
y
p
ar
ts
o
f
t
h
e
co
m
p
le
x
v
alu
e
ar
e
a
s
s
u
m
ed
to
b
e
w
h
it
e
Gau
s
s
ia
n
n
o
is
e
(
m
ea
n
is
eq
u
al
to
ze
r
o
a
n
d
th
e
s
a
m
e
v
ar
ian
ce
)
.
T
h
e
s
ig
n
al
to
n
o
is
e
r
atio
(
SNR
)
ca
n
b
e
co
m
p
u
ted
b
y
[
9
]
:
0
10
2
l
o
g
10
N
E
S
N
R
b
(
1
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it r
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(
2
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3
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1
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2
.
P
a
t
h lo
s
s
A
p
r
in
cip
all
y
s
i
g
n
i
f
ica
n
t
ele
m
en
t
in
t
h
e
d
esig
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eless
s
y
s
te
m
o
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a
r
ad
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co
m
m
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icati
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s
y
s
te
m
co
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s
id
er
s
as
th
e
r
ad
io
s
ig
n
a
l
p
ath
lo
s
s
.
T
h
e
r
ad
io
s
ig
n
a
l
p
ath
lo
s
s
w
ill
s
p
ec
i
f
y
f
e
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ele
m
en
t
s
o
f
th
e
co
m
m
u
n
icatio
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s
u
c
h
as
t
h
e
a
n
ten
n
a
s
h
ei
g
h
t,
t
h
e
tr
a
n
s
m
itter
p
o
w
er
an
d
p
r
i
n
cip
all
y
t
h
e
g
ain
.
Fu
r
t
h
er
m
o
r
e,
p
at
h
lo
s
s
w
ill al
s
o
af
f
ec
t th
e
f
o
r
m
o
f
tr
an
s
m
is
s
io
n
u
tili
ze
d
,
th
e
es
s
en
tial r
ec
eiv
er
s
en
s
iti
v
it
y
an
d
s
o
m
e
o
th
er
f
ac
to
r
s
.
T
h
e
s
ig
n
al
p
at
h
lo
s
s
ca
n
b
e
s
p
ec
if
ied
ar
ith
m
etica
ll
y
a
n
d
th
ese
co
m
p
u
tatio
n
s
ar
e
o
f
ten
ass
u
m
ed
w
h
er
ea
s
d
esig
n
in
g
s
y
s
te
m
ac
t
iv
i
ties
.
T
h
ese
b
ased
o
n
i
n
f
o
r
m
atio
n
o
f
t
h
e
s
i
g
n
a
l
p
r
o
p
ag
atio
n
attr
ib
u
te
s
.
T
h
e
s
ig
n
a
l
r
ad
io
p
ath
lo
s
s
i
n
clu
d
e
s
g
e
n
er
all
y
i
n
a
r
ed
u
ctio
n
i
n
p
o
w
er
d
en
s
it
y
o
f
a
s
i
g
n
al
as
it
tr
an
s
m
its
v
ia
th
e
en
v
ir
o
n
m
e
n
t
th
at
it i
s
tr
av
elli
n
g
.
T
h
e
ch
ief
r
ea
s
o
n
s
ar
e
th
e
f
o
llo
w
i
n
g
:
a.
Fre
e
s
p
ac
e
p
ath
lo
s
s
:
th
e
f
r
ee
s
p
ac
e
p
ath
lo
s
s
ap
p
ea
r
s
as
t
h
e
s
i
g
n
al
tr
a
v
els
v
ia
s
p
ac
e
w
i
th
o
u
t
an
y
o
t
h
er
ef
f
ec
ts
r
ed
u
ci
n
g
th
e
s
i
g
n
al.
T
h
is
ca
n
b
e
s
u
p
p
o
s
ed
o
f
as t
h
e
s
i
g
n
al
g
r
o
w
t
h
as a
n
ev
er
i
n
cr
ea
s
in
g
s
p
h
er
e.
T
h
e
en
er
g
y
in
a
n
y
s
p
ec
if
ied
ar
ea
w
ill d
ec
r
ea
s
e
as th
e
ar
ea
en
clo
s
e
d
b
ec
o
m
es lar
g
er
.
b.
A
b
s
o
r
p
tio
n
lo
s
s
es
:
w
h
en
a
r
a
d
io
s
ig
n
al
p
u
s
h
t
h
r
o
u
g
h
a
m
ed
iu
m
th
a
t
it
is
n
o
t
o
b
v
io
u
s
to
r
ad
io
s
ig
n
als
ab
s
o
r
p
tio
n
lo
s
s
es a
p
p
ea
r
.
c.
Dif
f
r
ac
tio
n
:
T
h
ese
lo
s
s
es
ap
p
ea
r
w
h
e
n
a
n
o
b
j
ec
t o
cc
u
r
s
i
n
th
e
s
i
g
n
a
l’
s
p
at
h
.
T
h
e
s
ig
n
al
ca
n
d
if
f
r
ac
t
n
ea
r
b
y
th
e
o
b
j
ec
t,
b
u
t
lo
s
s
es
ap
p
ea
r
.
T
h
e
lo
s
s
is
g
r
ea
ter
th
e
m
o
r
e
r
o
u
n
d
ed
th
e
o
b
j
ec
t.
C
o
n
ce
r
n
in
g
s
h
ar
p
ed
g
es,
th
e
r
ad
io
s
ig
n
al
s
ar
e
lik
el
y
to
d
if
f
r
ac
t b
etter
.
d.
Mu
ltip
at
h
:
s
ig
n
al
s
w
ill
r
ea
ch
t
h
e
r
ec
eiv
er
t
h
r
o
u
g
h
s
e
v
er
al
v
a
r
ian
t
p
ath
s
b
ec
au
s
e
a
lo
t
o
f
r
ef
lectio
n
s
.
T
h
es
e
s
ig
n
al
r
ef
lectio
n
s
ca
n
ad
d
o
r
s
u
b
tr
ac
t f
r
o
m
ea
c
h
o
th
er
b
ased
o
n
th
e
r
elati
v
e
p
h
ase
s
o
f
t
h
e
s
i
g
n
al
s
.
T
h
e
clea
r
ex
a
m
p
le
is
ce
llu
lar
telec
o
m
m
u
n
ica
tio
n
p
h
o
n
e
s
,
d
u
e
to
t
h
e
y
ar
e
s
u
b
j
ec
ted
to
th
i
s
e
f
f
ec
t
t
h
at
is
r
ec
o
g
n
ized
as R
a
y
leig
h
f
ad
in
g
.
e.
A
t
m
o
s
p
h
er
e:
t
h
e
at
m
o
s
p
h
er
e
w
a
s
a
f
f
ec
ted
i
n
r
ad
io
s
i
g
n
al
p
a
th
s
.
B
elo
w
3
0
-
5
0
MH
z,
lo
w
er
f
r
eq
u
en
c
ies,
a
n
d
th
e
io
n
o
s
p
h
er
e
h
a
s
a
n
i
m
p
o
r
tan
t
e
f
f
ec
t,
r
e
f
r
ac
tin
g
th
e
m
r
e
tu
r
n
b
ac
k
to
t
h
e
ea
r
t
h
.
A
b
o
v
e
5
0
MH
z,
t
h
e
tr
o
p
o
s
p
h
er
e
h
as a
m
ai
n
ef
f
ec
t,
r
ef
r
ac
tin
g
also
t
h
e
s
i
g
n
a
ls
r
etu
r
n
b
ac
k
to
th
e
ea
r
th
.
f.
Ob
s
tacle
s
:
b
u
ild
i
n
g
s
a
n
d
v
eg
etatio
n
h
av
e
a
n
a
m
az
i
n
g
ef
f
ec
t.
T
h
e
b
u
ild
in
g
s
w
il
l
ab
s
o
r
b
an
d
n
o
t
o
n
l
y
r
ef
lect
t
h
e
s
i
g
n
al
also
.
I
n
co
n
tex
t,
p
r
in
cip
all
y
w
h
e
n
tr
ee
s
,
w
e,
an
d
f
o
lia
g
e
m
a
y
r
ed
u
ce
r
ad
io
s
ig
n
al
s
.
Fu
r
t
h
er
m
o
r
e,
th
e
h
ills
,
c
lear
l
y
w
il
l
c
h
ec
k
th
e
p
ath
a
n
d
s
i
g
n
i
f
i
ca
n
tl
y
r
ed
u
ce
t
h
e
s
i
g
n
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2
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1
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F
la
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a
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f
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later
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I
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2
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s
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k
k
k
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n
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=1
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u
r
e
2
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Flat f
ad
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h
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2
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re
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r
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o
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a
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OFDM
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s
m
i
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at
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p
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T
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ier
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On
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o
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itted
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h
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t
h
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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C
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p
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I
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N:
2088
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h
/
2
1
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(
1
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w
h
er
e
ci
ca
n
b
e
d
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i
n
ed
a
s
t
h
e
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m
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le
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al
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ed
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h
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n
el
g
ain
o
f
t
h
e
i
t
h
m
u
ltip
at
h
ele
m
en
t
a
n
d
m
ca
n
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e
d
ef
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ed
a
s
t
h
e
n
u
m
b
er
o
f
r
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o
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le
m
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ltip
at
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m
e
n
ts
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an
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h
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t
h
e
m
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ltip
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s
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r
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ad
T
m
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d
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tio
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o
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th
e
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ltip
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h
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n
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e
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ef
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ed
as 1
/W
,
a
s
s
h
o
w
n
i
n
E
q
u
atio
n
(
11
)
as b
ello
w
s
:
1
W
T
m
m
(
1
1
)
A
c
h
a
n
n
el
h
a
v
i
n
g
th
e
i
m
p
u
ls
e
r
ep
ly
is
g
i
v
en
b
y
E
q
u
at
io
n
(
9
)
ca
n
b
e
r
ep
r
esen
ted
b
y
a
tap
p
ed
–
d
ela
y
lin
e
w
it
h
L
tap
s
a
n
d
co
m
p
le
x
v
al
u
ed
,
ti
m
e
–
v
ar
ia
n
t
tap
co
ef
f
icie
n
ts
ci(
t)
.
Fi
g
u
r
e
3
s
h
o
w
s
th
e
tap
p
ed
–
d
ela
y
–
lin
e
c
h
an
n
el
m
o
d
el
t
h
at
i
s
s
u
it
ab
le
f
o
r
th
e
f
r
eq
u
e
n
c
y
s
elec
t
iv
e
f
ad
in
g
ch
a
n
n
el.
T
h
e
r
an
d
o
m
l
y
ti
m
e
v
ar
ia
n
t
tap
ga
in
s
ci(
t)
ca
n
also
b
e
r
ep
r
esen
ted
b
y
E
q
u
atio
n
(
12
)
as b
ello
w
s
:
t
i
j
i
e
t
t
c
)
(
i=1
,
2
….
,
m
(
1
2
)
w
h
er
e
c
i
(
t)
d
en
o
te
th
e
a
m
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lit
u
d
es
an
d
υ
i
(
t)
d
en
o
te
th
e
p
h
ase
m
atc
h
in
g
p
h
a
s
es.
Fo
r
th
e
f
r
eq
u
en
c
y
s
elec
ti
v
e
f
ad
in
g
ch
a
n
n
el,
ea
ch
o
f
t
h
e
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g
ain
h
as a
m
ag
n
it
u
d
e
th
a
t is s
h
o
w
ed
as R
a
y
leig
h
f
ad
in
g
[
1
3
]
.
Fig
u
r
e
3
.
T
a
p
p
ed
-
d
elay
-
li
n
e
ch
an
n
el
m
o
d
el
4.
E
XP
E
RM
E
NT
AL
R
E
SU
T
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T
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er
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r
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al
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atio
n
o
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c
h
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n
el
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d
i
s
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la
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ed
i
n
Fi
g
u
r
e
4
.
T
h
e
A
W
GN,
p
at
h
lo
s
s
,
a
n
d
m
o
b
il
e
ch
an
n
el
ca
n
b
e
ap
p
ea
r
ed
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
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&
C
o
m
p
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n
g
,
Vo
l.
8
,
No
.
3
,
J
u
n
e
201
8
:
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4
5
1
–
1459
1456
Fig
u
r
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4
.
T
h
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s
i
m
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l
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tio
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h
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ter
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Fig
u
r
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5
s
h
o
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e
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ar
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itiv
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ite
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f
o
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e
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o
d
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th
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s
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w
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th
e
m
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n
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m
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l
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d
th
e
v
ar
ia
n
ce
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σ
2
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al
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e.
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h
ile
Fig
u
r
e
6
d
is
p
lay
s
th
e
n
o
r
m
ali
ze
d
p
r
o
b
ab
ilit
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d
en
s
it
y
f
u
n
ct
i
o
n
o
f
A
W
GN
t
h
at
is
ad
d
ed
to
r
ec
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e
b
aseb
an
d
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ig
n
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Fig
u
r
e
5
.
T
h
e
r
an
d
o
m
ad
d
itiv
e
w
h
ite
Ga
u
s
s
ian
n
o
is
e
w
it
h
m
e
an
(
m
=0
)
an
d
v
ar
ia
n
ce
(
σ
2
=1
)
Fig
u
r
e
6
.
T
h
e
s
tan
d
ar
d
n
o
r
m
al
p
r
o
b
a
b
ilit
y
d
en
s
it
y
f
u
n
ctio
n
(
σ
2
=
1
)
A
f
u
r
th
er
m
eth
o
d
to
s
h
o
w
t
h
at
th
e
f
r
eq
u
en
c
y
r
ep
l
y
r
e
m
a
i
n
s
w
h
ite
a
f
ter
m
u
lt
ip
l
y
i
n
g
th
e
ti
m
e
ar
ea
f
u
n
ctio
n
w
it
h
a
r
ec
ta
n
g
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lar
w
i
n
d
o
w
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s
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etec
t
t
h
e
au
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co
r
r
elatio
n
f
u
n
ctio
n
in
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ch
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s
e:
a
u
n
if
o
r
m
f
u
n
ctio
n
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e
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e
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r
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n
f
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n
ct
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n
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A
W
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ig
n
al
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i
m
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u
l
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l
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e
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d
d
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g
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e
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lt
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r
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ein
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m
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ls
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d
th
er
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r
e
th
e
f
r
eq
u
en
c
y
r
ep
ly
w
i
ll
s
till
b
e
co
n
s
ta
n
t
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wh
ite)
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A
d
d
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s
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o
es
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tr
o
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u
ce
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et
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n
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h
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
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C
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p
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I
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N:
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8708
I
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f F
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1457
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/T
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t
all
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s
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et
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le
s
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id
ed
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y
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As
s
h
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w
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in
Fi
g
u
r
e
7
t
h
e
p
e
r
f
o
r
m
an
ce
s
e
v
alu
a
tio
n
o
f
t
h
e
A
W
GN
c
h
a
n
n
el
w
it
h
m
ea
n
(
m
=0
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an
d
v
ar
ian
ce
(
σ
2
=1
)
.
T
h
e
p
er
f
o
r
m
an
ce
e
v
alu
a
tio
n
o
f
t
h
i
s
c
h
an
n
e
l
is
a
p
p
lied
b
y
tr
an
s
m
itti
n
g
1
0
0
0
0
0
b
its
.
I
t
ca
n
b
e
d
is
p
la
y
ed
f
r
o
m
t
h
e
f
ig
u
r
e;
t
h
e
v
alu
e
o
f
SN
R
is
1
2
d
B
f
o
r
b
it e
r
r
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r
r
ate
(
B
E
R
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b
etw
ee
n
(
1
0
-
5
).
Fig
u
r
e
7
.
P
er
f
o
r
m
a
n
ce
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al
u
at
io
n
w
ith
A
W
G
N
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2
d
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an
d
B
E
R
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(
0
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10
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5
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4
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2
.
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r
m
a
nce
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t
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a
t
h lo
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s
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h
e
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er
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o
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m
a
n
ce
e
v
al
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atio
n
o
f
p
ath
lo
s
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h
a
s
b
ee
n
ca
lcu
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ted
b
y
u
s
i
n
g
E
q
u
atio
n
(
13
)
as g
i
v
en
b
y
[
1
3
]
as f
o
llo
w
s
:
L
d
G
G
P
d
P
t
r
t
r
2
2
4
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3
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t
is
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a
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n
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th
th
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d
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ta
n
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s
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g
u
r
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8
.
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h
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f
i
g
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r
e
s
h
o
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t
t
h
e
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er
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w
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d
B
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r
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ig
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r
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s
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itter
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5
,
7
W
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d
th
e
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t statio
n
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te
n
n
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h
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m
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.
Fig
u
r
e
8
.
T
h
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r
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n
b
et
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n
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ec
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er
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n
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d
e
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en
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e
P
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d
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ta
n
ce
(
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m
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Fig
u
r
e
9
d
is
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t
h
e
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ile
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n
a
n
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h
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ig
h
t
(
H
m
=1
to
1
0
m
)
an
d
p
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w
er
tr
an
s
m
itted
w
it
h
(
5
W
)
.
I
t
is
clea
r
f
r
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m
th
is
f
ig
u
r
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e
e
f
f
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o
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e
m
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ile
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n
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a
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t
(
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m
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w
it
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r
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.
0
2
4
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10
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10
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S
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R
(
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BER
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N
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
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lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
3
,
J
u
n
e
201
8
:
1
4
5
1
–
1459
1458
Fig
u
r
e
9
.
T
h
e
r
elatio
n
b
et
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n
th
e
r
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v
e
r
p
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w
er
in
d
B
an
d
th
e
h
ei
g
h
t H
m
4
.
3
.
P
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f
o
r
m
a
nce
ev
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it
h
m
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cha
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Fig
u
r
e
1
0
d
is
p
lay
s
t
h
e
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er
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o
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m
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n
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n
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f
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w
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h
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P
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o
d
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l
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n
.
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a
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ce
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o
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te
m
i
s
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an
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i
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1
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ata
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its
.
I
t
i
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f
r
o
m
t
h
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f
ig
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r
e;
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e
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al
u
e
o
f
SNR
i
s
eq
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al
to
4
5
d
B
at
B
E
R
=1
0
-
5
.
Fig
u
r
e
10
.
Pe
r
f
o
r
m
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ce
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v
alu
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o
f
f
lat
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n
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ch
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n
n
el
Fig
u
r
e
1
1
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is
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lay
s
t
h
e
p
er
f
o
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m
an
ce
e
v
alu
a
tio
n
o
f
f
r
eq
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e
n
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ti
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e
f
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h
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P
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NC
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S
[1
]
D.
T
se
a
n
d
P
.
V
isw
a
n
a
th
,
“
F
u
n
d
a
m
e
n
tals o
f
w
ir
e
les
s co
m
m
u
n
ica
ti
o
n
,”
Ca
m
b
rid
g
e
,
2
0
0
4
.
[2
]
M.
P
a
tzo
l
d
,
“
M
o
b
i
le f
a
d
in
g
c
h
a
n
n
e
ls
,”
Jo
h
n
W
il
e
y
&
S
o
n
s,
In
c
,
2
0
0
3
.
[3
]
M
.
S
.
M
ia
h
,
e
t
a
l
.
,
“
P
e
rf
o
rm
a
n
c
e
c
o
m
p
a
riso
n
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f
A
WGN,
f
lat
fa
d
in
g
a
n
d
f
re
q
u
e
n
c
y
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lec
ti
v
e
f
a
d
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c
h
a
n
n
e
l
f
o
r
w
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ss
c
o
m
m
u
n
ica
ti
o
n
sy
ste
m
u
sin
g
4
Q
P
S
K
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
m
p
u
ter
a
n
d
In
fo
rm
a
t
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o
n
T
e
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h
n
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v
o
l
.
1
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n
o
.
2
,
p
p
.
8
2
-
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0
,
2
0
1
1
.
[4
]
C.
X
iao
,
e
t
a
l.
,
“
No
v
e
l
su
m
-
of
-
sin
u
so
i
d
s
sim
u
latio
n
m
o
d
e
ls
f
o
r
Ra
y
l
e
ig
h
a
n
d
Ricia
n
f
a
d
in
g
c
h
a
n
n
e
ls
,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
W
ire
les
s Co
mm
u
n
ica
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o
n
s
,
vol
.
5
,
n
o
.
1
2
,
2
0
0
6
.
[5
]
C.
X
iao
,
e
t
a
l.
,
“
S
tatisti
c
a
l
sim
u
l
a
ti
o
n
m
o
d
e
ls
f
o
r
Ra
y
leig
h
a
n
d
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n
f
a
d
in
g
,”
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ter
n
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ti
o
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l
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fer
e
n
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e
o
n
th
e
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mm
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n
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n
s
,
ICC
'0
3
.
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,
2
0
0
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.
[6
]
A
.
A
li
m
o
h
a
m
m
a
d
,
e
t
a
l.
,
“
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n
a
c
c
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ra
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p
a
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f
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l
sim
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EE
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2
0
0
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.
[7
]
R.
Hic
h
e
ri,
e
t
a
l.
,
“
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ti
sti
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th
f
a
d
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c
h
a
n
n
e
l
s
,”
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ter
n
a
t
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Co
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fer
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n
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o
n
th
e
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n
c
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d
T
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c
h
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o
lo
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fo
r C
o
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n
ica
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o
n
s (
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C)
,
2
0
1
4
.
[8
]
S.
Yin
,
e
t
a
l.
,
“
S
tatisti
c
a
l
m
o
d
e
li
n
g
f
o
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sp
e
c
tru
m
u
sa
g
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c
h
a
ra
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teri
z
in
g
w
irele
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a
d
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h
a
n
n
e
ls
a
n
d
m
o
b
il
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se
rv
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y
n
a
m
ics
,”
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ra
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sa
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ti
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l
.
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2
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8
,
p
p
.
3
8
0
0
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3
8
1
2
,
2
0
1
3
.
[9
]
L
.
W
.
Co
u
c
h
,
e
t
a
l.
,
“
Dig
it
a
l
a
n
d
a
n
a
lo
g
c
o
m
m
u
n
ica
ti
o
n
sy
ste
m
s,
v
o
l.
6
,
1
9
9
7
.
[1
0
]
S
k
lar,
B.
Ra
y
l
e
ig
h
f
a
d
in
g
c
h
a
n
n
e
ls
in
m
o
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il
e
d
ig
it
a
l
c
o
m
m
u
n
ica
ti
o
n
sy
ste
m
s
,”
I.
Ch
a
ra
c
t
e
riza
ti
o
n
.
IEE
E
Co
mm
u
n
ica
ti
o
n
s ma
g
a
zi
n
e
,
v
o
l
.
3
5
,
n
o
.
9
,
p
p
.
1
3
6
-
1
4
6
,
1
9
9
7
.
[1
1
]
T
.
S
.
Ra
p
p
a
p
o
rt,
“
W
irele
ss
Co
m
m
u
n
ica
ti
o
n
s
--
P
r
in
c
ip
les
a
n
d
P
ra
c
ti
c
e
,
(
T
h
e
Bo
o
k
En
d
)
,”
M
icr
o
wa
v
e
J
o
u
rn
a
l
,
v
o
l
.
4
5
,
n
o
.
1
2
,
p
p
.
1
2
8
-
1
2
9
,
2
0
0
2
.
[1
2
]
S.
G
a
u
r,
“
A
n
a
l
y
sis o
f
A
d
v
a
n
c
e
d
Div
e
rsit
y
Re
c
e
iv
e
r
s f
o
r
F
a
d
in
g
Ch
a
n
n
e
ls,
”
2
0
0
3
.
[1
3
]
J.
Yu
n
,
“
A
d
a
p
ti
v
e
Re
so
u
rc
e
A
ll
o
c
a
ti
o
n
f
o
r
D
-
T
DD
S
y
ste
m
s in
W
ir
e
les
s M
u
lt
im
e
d
ia Ne
t
w
o
rk
s,
”
2
0
0
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.