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In
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1.
I
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RO
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O
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No
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m
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1
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-
[
3
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ased
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l
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[
8
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-
[
9
]
.
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I
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[
1
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w
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etail
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to
d
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iat
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f
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th
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id
ea
l
lo
ca
tio
n
.
On
e
s
tep
i
n
t
h
e
d
e
m
o
d
u
latio
n
p
r
o
ce
s
s
is
th
e
p
h
as
e
s
h
i
f
t,
w
h
ic
h
cr
ea
tes
an
I
-
Q
(
I
n
-
p
h
a
s
e
–
Qu
a
d
r
atu
r
e)
f
lo
w
th
at
ca
n
b
e
u
s
ed
as
t
h
e
r
eliab
le
est
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m
ated
p
ar
a
m
eter
s
f
o
r
th
e
id
ea
l tr
an
s
m
i
tted
s
ig
n
al
.
Fig
u
r
e
4
illu
s
tr
ates
th
a
t
th
e
c
o
n
s
tellat
i
o
n
s
h
ad
ca
n
o
n
ic
p
r
o
p
er
ties
,
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h
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m
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n
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t
h
at
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ee
n
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w
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ax
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m
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m
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e
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ated
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.
F
ig
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t
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en
s
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r
th
an
t
h
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m
al
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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mp
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u
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4
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h
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Fig
u
r
e
5
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h
e
co
n
s
tellatio
n
u
s
i
n
g
t
h
e
p
r
o
p
o
s
ed
s
ch
e
m
e
i
n
th
e
o
p
tical
f
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it
h
th
e
le
n
g
t
h
o
f
a)
1
0
k
m
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)
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0
km
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a
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1
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0
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T
h
e
g
en
er
ated
co
n
s
tel
latio
n
h
ad
a
ca
n
o
n
ical
f
o
r
m
,
w
h
ic
h
is
a
co
n
d
itio
n
t
h
at
r
ep
r
ese
n
ts
t
h
e
r
esu
l
tin
g
co
o
r
d
in
ate
tr
an
s
f
o
r
m
atio
n
is
i
n
t
h
e
o
p
ti
m
u
m
s
ep
ar
atio
n
(
m
ax
i
m
u
m
s
ep
ar
atio
n
)
.
T
h
e
r
esu
ltin
g
er
r
o
r
is
s
m
all
an
d
t
h
e
co
r
r
ec
t
s
i
g
n
al
p
o
s
itio
n
co
r
r
ec
tl
y
is
ea
s
il
y
d
etec
tab
l
e.
I
n
ca
n
o
n
ical
co
n
d
itio
n
s
,
t
h
e
r
ec
eiv
ed
s
ig
n
al
is
m
o
r
e
as
s
o
ciate
d
w
it
h
th
e
w
o
r
k
in
g
e
f
f
icie
n
c
y
o
f
th
e
s
y
s
te
m
.
I
n
a
m
at
h
e
m
a
tical
s
en
s
e,
t
h
e
ca
n
o
n
ica
l
f
o
r
m
o
f
t
h
e
s
ta
n
d
ar
d
w
a
y
o
f
r
ep
r
es
s
in
g
t
h
e
o
b
j
ec
t
as
an
ex
p
er
i
m
e
n
t
o
f
a
m
ath
e
m
atica
l
f
u
n
ctio
n
.
I
n
s
o
m
e
g
e
n
er
al
f
ield
s
,
th
e
ca
n
o
n
ical
f
o
r
m
d
eter
m
in
e
s
th
e
u
n
iq
u
e
r
ep
r
esen
tatio
n
o
f
ea
ch
o
b
j
ec
t.
Me
an
w
h
ile,
t
h
e
n
o
r
m
al
f
o
r
m
d
eter
m
i
n
e
s
it
s
s
h
ap
e
with
o
u
t
an
y
u
n
iq
u
e
re
q
u
ir
e
m
en
t
.
T
h
e
ca
n
o
n
ical
f
o
r
m
o
f
p
o
s
it
iv
e
in
teg
er
s
in
t
h
e
d
ec
i
m
al
r
ep
r
ese
n
tatio
n
is
a
f
i
n
ite
s
eq
u
e
n
ce
o
f
n
u
m
b
er
s
t
h
at
d
o
n
o
t
o
r
ig
in
ate
f
r
o
m
ze
r
o
.
T
h
e
ca
n
o
n
ical
d
i
f
f
er
en
tia
l
f
o
r
m
ca
n
b
e
attr
ib
u
ted
to
Ha
m
ilt
o
n
's
m
ec
h
an
ica
l
t
h
e
o
r
y
.
T
h
e
t
h
eo
r
y
w
a
s
d
ev
elo
p
ed
as
a
r
ef
o
r
m
u
latio
n
o
f
class
ical
m
ec
h
a
n
ics
(
clas
s
i
ca
l
m
ec
h
a
n
ics
is
p
ar
t
o
f
th
e
p
h
y
s
ics
o
f
t
h
e
f
o
r
ce
s
ac
tin
g
o
n
an
o
b
j
ec
t)
.
T
h
e
o
b
j
ec
ts
in
class
ical
m
ec
h
an
ic
s
ca
n
b
e
s
tati
s
tical,
k
in
e
m
at
ics
,
an
d
d
y
n
a
m
ic
s
(
o
b
j
ec
ts
th
at
m
o
v
e
b
y
f
o
r
ce
in
f
l
u
en
ce
s
)
.
T
h
e
f
o
r
m
u
latio
n
o
f
class
ical
m
ec
h
an
ics
i
s
ess
e
n
ti
all
y
co
n
tr
ib
u
te
d
to
th
e
f
o
r
m
u
latio
n
o
f
s
tati
s
tical
an
d
q
u
an
t
u
m
m
ec
h
a
n
ic
s
.
On
e
p
ar
ticle
w
it
h
m
as
s
m
r
ep
r
esen
t
s
th
e
Ha
m
ilto
n
f
u
n
ctio
n
in
a
o
n
e
-
d
i
m
e
n
s
io
n
a
l s
y
s
te
m
,
w
i
th
t
h
e
Ha
m
ilto
n
ia
n
r
ep
r
ese
n
tin
g
t
h
e
to
tal
en
er
g
y
o
f
th
e
s
y
s
te
m
w
h
ic
h
is
th
e
s
u
m
o
f
t
h
e
k
in
et
ic
en
er
g
y
an
d
th
e
p
o
ten
tial e
n
er
g
y
.
4.
CO
NCLU
SI
O
N
T
h
e
s
m
all
li
n
e
w
id
t
h
co
r
r
elate
s
w
ith
t
h
e
co
h
er
e
n
t
v
al
u
e
a
n
d
p
r
o
d
u
ce
s
a
lar
g
e
o
p
tical
s
p
ec
tr
u
m
.
Op
tical
p
o
w
er
s
p
ec
tr
al
d
en
s
ities
ca
n
b
e
attr
ib
u
ted
to
f
i
x
ed
o
p
tical
f
r
eq
u
en
c
y
i
n
ter
v
als
(
m
ea
s
u
r
ed
in
T
er
ah
er
tz)
,
o
r
at
w
a
v
elen
g
t
h
in
ter
v
a
ls
(
i
n
n
a
n
o
m
eter
u
n
it
s
)
.
T
h
is
s
u
g
g
e
s
ts
t
h
at
t
h
e
s
h
o
r
ter
w
a
v
ele
n
g
th
s
i
n
n
an
o
m
eter
s
h
av
e
t
h
e
v
alu
e
i
n
th
e
s
ca
le
o
f
T
er
ah
er
tz.
T
h
e
co
n
s
eq
u
e
n
ce
is
t
h
at
t
h
e
p
ea
k
p
o
s
itio
n
o
f
t
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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5
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2
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4752
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1
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201
8
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–
432
432
s
p
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tr
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g
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er
en
t
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e
,
an
d
t
h
e
co
h
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en
ce
le
n
g
th
.
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im
e
co
h
er
en
ce
i
s
a
co
m
m
o
n
f
o
r
m
to
d
eter
m
i
n
e
th
e
le
n
g
th
o
f
co
h
er
en
ce
.
T
h
e
c
o
h
er
en
ce
le
n
g
th
is
a
f
u
n
c
tio
n
o
f
co
h
er
e
n
ce
ti
m
e
m
u
ltip
lied
b
y
t
h
e
v
ac
u
u
m
v
elo
cit
y
.
T
im
e
co
h
er
e
n
ce
ca
n
b
e
u
s
ed
to
m
ea
s
u
r
e
t
h
e
d
eg
r
ee
o
f
te
m
p
o
r
al
co
h
er
en
ce
in
t
h
e
l
ig
h
t.
I
n
o
th
er
co
h
er
e
n
ce
t
y
p
es,
th
e
co
h
er
en
t
le
n
g
th
ca
n
b
e
u
s
ed
to
m
ea
s
u
r
e
t
h
e
co
o
r
d
in
ate
le
v
el
o
f
te
m
p
o
r
al
co
h
er
e
n
ce
as
t
h
e
len
g
t
h
o
f
p
r
o
p
ag
atio
n
(
p
r
o
p
ag
atio
n
ti
m
e
)
.
T
h
is
is
n
ec
es
s
ar
y
b
ec
au
s
e
i
n
th
is
p
r
o
ce
s
s
,
co
h
er
en
ce
d
ec
r
ea
s
es
s
i
g
n
i
f
ican
tl
y
.
I
t
is
d
e
f
i
n
ed
as
th
e
ti
m
e
co
h
e
r
en
ce
m
u
l
tip
lied
b
y
th
e
co
n
s
t
an
t
s
p
ee
d
o
f
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ig
h
t.
A
n
ar
r
o
w
o
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li
m
ited
lin
e
w
id
th
e
m
u
lates
f
r
o
m
p
h
ase
n
o
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s
e
i
f
th
e
p
h
ase
d
r
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f
t
(
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ch
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ct
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ter
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w
it
h
s
m
all
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ase
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g
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li
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d
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if
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o
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th
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r
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r
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ca
n
th
e
n
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ib
u
te
to
th
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lin
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w
id
t
h
q
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an
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d
ca
n
m
a
k
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its
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at
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r
e
d
ep
en
d
s
o
n
th
e
m
ea
s
u
r
e
m
en
t
o
f
ti
m
e.
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h
o
w
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t
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at
l
in
e
w
id
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h
eq
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ip
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ed
w
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h
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p
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al
f
o
r
m
ca
n
p
r
o
v
i
d
e
co
m
p
r
e
h
en
s
iv
e
i
n
f
o
r
m
atio
n
.
T
h
e
i
n
f
o
r
m
a
tio
n
co
n
tai
n
s
t
h
e
p
u
r
it
y
o
f
a
laser
lig
h
t sp
ec
tr
al
(
th
i
s
h
ap
p
en
s
u
s
u
all
y
in
la
s
er
s
t
h
at
d
o
m
i
n
ate
f
r
eq
u
en
cie
s
w
it
h
lo
w
-
f
r
eq
u
e
n
c
y
p
h
ases
)
.
RE
F
E
R
E
NC
E
S
[1
]
M
.
Xu
e
,
S
.
P
a
n
,
a
n
d
Y.
Zh
a
o
.
Op
ti
c
a
l
S
in
g
le
-
S
id
e
b
a
n
d
M
o
d
u
latio
n
Ba
se
d
o
n
a
Du
a
l
-
Driv
e
M
ZM
a
n
d
a
1
2
0
°
H
y
b
rid
Co
u
p
ler.
J
o
u
rn
a
l
o
f
L
i
g
h
twa
v
e
T
e
c
h
n
o
l
o
g
y
.
2
0
1
4
;
3
2
(1
9
):
3
3
1
7
-
3
3
2
3
.
[2
]
Y.
W
a
n
g
,
J.
Yu
,
X
.
L
i,
Y.
X
u
,
N
.
Ch
i,
a
n
d
G
.
K.
Ch
a
n
g
.
P
h
o
to
n
i
c
V
e
c
to
r
S
ig
n
a
l
G
e
n
e
ra
ti
o
n
Em
p
l
o
y
in
g
a
S
in
g
le
-
Driv
e
M
ZM
-
Ba
se
d
Op
ti
c
a
l
Ca
rrier
S
u
p
p
re
ss
io
n
w
it
h
o
u
t
P
re
-
c
o
d
i
n
g
.
J
o
u
rn
a
l
o
f
L
ig
h
twa
v
e
T
e
c
h
n
o
lo
g
y
.
2
0
1
5
;
3
3
(2
4
):
5
2
3
5
-
52
41
.
[3
]
T
.
Ka
n
e
s
a
n
,
W
.
P
a
n
g
,
Z.
G
h
a
s
se
m
lo
o
y
,
a
n
d
C.
L
u
.
Imp
a
c
t
o
f
Op
ti
c
a
l
M
o
d
u
la
t
o
rs
in
L
T
E
R
o
F
S
y
ste
ms
wit
h
No
n
li
n
e
a
r
Co
m
p
e
n
sa
t
o
r
f
o
r
En
h
a
n
c
e
d
Po
we
r
B
u
d
g
e
t
.
P
r
o
c
.
o
f
Op
ti
c
a
l
F
i
b
e
r
Co
m
m
u
n
ica
ti
o
n
Co
n
f
e
re
n
c
e
a
n
d
Ex
p
o
siti
o
n
a
n
d
t
h
e
Na
ti
o
n
a
l
F
i
b
e
r
Op
ti
c
E
n
g
in
e
e
rs Co
n
f
e
re
n
c
e
,
C
a
l
i
f
o
r
n
i
a
,
U
n
i
t
e
d
S
t
a
t
e
s
.
2
0
1
3
;
1
-
3.
[4
]
T
.
Ka
n
e
sa
n
,
W
.
P
a
n
g
,
Z
.
G
h
a
ss
e
m
lo
o
y
,
a
n
d
C.
L
u
.
I
n
v
e
stig
a
ti
o
n
o
f
Op
ti
c
a
l
M
o
d
u
lato
rs
in
O
p
ti
m
iz
e
d
No
n
li
n
e
a
r
Co
m
p
e
n
sa
ted
LT
E
Ro
F
S
y
ste
m
.
J
o
u
rn
a
l
o
f
L
ig
h
twa
v
e
T
e
c
h
n
o
l
o
g
y
.
2
0
1
4
;
3
2
(2
3
):
1
9
4
4
-
1
9
5
0
.
[5
]
T
.
Ka
n
e
sa
n
,
W
.
P
a
n
g
,
Z.
G
h
a
ss
e
m
lo
o
y
,
a
n
d
J.
P
e
re
z
.
Op
ti
m
iza
ti
o
n
o
f
Op
ti
c
a
l
M
o
d
u
lato
rs
f
o
r
L
T
E
Ro
F
in
N
o
n
li
n
e
a
r
F
ib
e
r
P
r
o
p
a
g
a
ti
o
n
.
IE
EE
P
h
o
t
o
n
i
c
s L
e
tt
e
rs
.
2
0
1
2
;
2
4
(7
):
6
1
7
-
6
1
9
.
[6
]
T
.
No
r
th
a
n
d
M
.
R
o
c
h
e
tt
e
.
A
n
a
l
y
sis
o
f
S
e
lf
-
P
u
lsa
ti
n
g
S
o
u
rc
e
s
Ba
se
d
o
n
Re
g
e
n
e
ra
ti
v
e
S
P
M
:
Ig
n
it
io
n
,
P
u
lse
Ch
a
ra
c
teristics
a
n
d
S
tab
il
it
y
.
J
o
u
rn
a
l
o
f
L
ig
h
twa
v
e
T
e
c
h
n
o
l
o
g
y
.
2
0
1
3
;
3
1
(
2
3
):
3
7
0
0
-
3
7
0
6
.
[7
]
Z.
Jia
o
,
R
.
Z
h
a
n
g
,
X
.
Zh
a
n
g
,
J.
L
iu
,
a
n
d
Z.
L
u
.
M
o
d
e
li
n
g
o
f
S
in
g
le
-
S
e
c
ti
o
n
Qu
a
n
t
u
m
Do
t
M
o
d
e
-
L
o
c
k
e
d
Las
e
rs
:
Im
p
a
c
t
o
f
G
ro
u
p
V
e
lo
c
it
y
Disp
e
rsio
n
a
n
d
S
e
lf
P
h
a
se
M
o
d
u
lati
o
n
.
J
o
u
rn
a
l
o
f
L
ig
h
tw
a
v
e
T
e
c
h
n
o
l
o
g
y
.
2
0
1
3
;
4
9
(1
2
):
1
0
0
8
-
1
0
1
5
.
[8
]
F
.
H.
P
a
rti
a
n
sy
a
h
,
A
.
S
u
sa
n
to
,
I.
W
.
M
u
stik
a
,
S
.
M
.
Id
ru
s,
a
n
d
S
.
H.
P
u
r
n
o
m
o
.
Dith
e
rin
g
A
n
a
l
y
s
is
in
a
n
Orth
o
g
o
n
a
l
F
re
q
u
e
n
c
y
Div
isio
n
M
u
lt
ip
lex
in
g
-
Ra
d
io
o
v
e
r
F
ib
e
r
L
in
k
.
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
En
g
i
n
e
e
rin
g
,
2
0
1
6
;
6
(3
)
:
1
1
1
2
-
1
1
2
1
.
[
9
]
F
.
Kh
a
ir,
F
.
H.
P
a
rt
ian
sy
a
h
,
I.
W
.
M
u
stika
,
a
n
d
B.
S
e
ti
y
a
n
to
.
P
e
rf
o
rm
a
n
c
e
A
n
a
l
y
si
s
o
f
Dig
it
a
l
M
o
d
u
lati
o
n
f
o
r
Co
h
e
re
n
t
De
tec
ti
o
n
o
f
OFDM
S
c
h
e
m
e
o
n
Ra
d
io
o
v
e
r
F
ib
e
r
S
y
ste
m
.
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
in
e
e
rin
g
.
2
0
1
6
;
6
(3
)
:
1
0
8
6
-
1
0
9
5
.
[
1
0
]
F
a
k
h
r
i
y
H
a
r
i
o
,
I
.
Wa
y
a
n
M
u
s
t
i
k
a
,
Ad
h
i
S
u
s
a
n
to
,
S
h
o
l
e
h
H
a
d
i
,
S
e
v
i
a
M
I
d
ru
s.
A
No
v
el
Sc
h
e
m
e
f
o
r
Or
th
o
g
o
n
a
l
Fre
q
u
en
c
y
Di
v
i
s
io
n
M
u
lt
ip
lex
in
g
-
R
ad
io
o
v
er
Fib
er
B
ased
o
n
Mo
d
u
lato
r
a
n
d
Dit
h
er
in
g
T
ec
h
n
iq
u
e:
I
m
p
ac
t
o
f
Sel
f
P
h
ase
Mo
d
u
la
tio
n
an
d
Gr
o
u
p
Velo
cit
y
D
is
p
er
s
io
n
.
I
n
tern
a
tio
n
a
l
Jo
u
r
n
a
l
o
f
I
n
tellig
en
t
E
n
g
in
ee
r
in
g
a
n
d
S
ystems
.
2
0
1
7
; (
4
)
:
1
1
7
-
1
2
5
.
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