T
E
L
KO
M
N
I
KA
T
e
lec
om
m
u
n
icat
ion
,
Com
p
u
t
i
n
g,
E
lec
t
r
on
ics
an
d
Cont
r
ol
Vol.
18
,
No.
5
,
Oc
tober
2020
,
pp
.
2284~2291
I
S
S
N:
1693
-
6930,
a
c
c
r
e
dit
e
d
F
ir
s
t
G
r
a
de
by
Ke
me
nr
is
tekdikti
,
De
c
r
e
e
No:
21/E
/KP
T
/2018
DO
I
:
10.
12928
/
T
E
L
KO
M
NI
KA
.
v18i5.
14223
2284
Jou
r
n
al
h
omepage
:
ht
tp:
//
jour
nal.
uad
.
ac
.
id/
index
.
php/T
E
L
K
OM
N
I
K
A
A
n
ove
l
d
e
la
y d
i
c
t
io
n
a
r
y d
e
si
gn
f
or
c
om
p
r
e
ssi
ve
se
n
si
n
g
-
b
ase
d
t
ime
var
yi
n
g c
h
an
n
e
l
e
st
imat
i
on
i
n
OFDM
sys
t
e
m
s
M
ar
yam
K.
Abb
ou
d
,
B
ayan
M
.
S
ab
b
ar
C
oll
e
ge
of
I
n
f
or
mation
E
nginee
r
ing
,
Al
-
Na
hr
a
in
U
niver
s
it
y,
I
r
a
q
Ar
t
icle
I
n
f
o
AB
S
T
RA
CT
A
r
ti
c
le
h
is
tor
y
:
R
e
c
e
ived
S
e
p
27,
2019
R
e
vis
e
d
M
a
y
5,
2020
Ac
c
e
pted
M
a
y
14,
2020
Co
mp
re
s
s
i
v
e
s
en
s
i
n
g
(CS)
i
s
a
n
e
w
at
t
ract
i
v
e
t
ech
n
i
q
u
e
a
d
o
p
t
e
d
fo
r
l
i
n
ear
t
i
me
v
ary
i
n
g
ch
a
n
n
e
l
es
t
i
ma
t
i
o
n
.
o
rt
h
o
g
o
n
al
freq
u
en
c
y
d
i
v
i
s
i
o
n
mu
l
t
i
p
l
ex
i
n
g
(O
FD
M)
w
as
p
r
o
p
o
s
e
d
t
o
b
e
u
s
e
d
i
n
4
G
an
d
5
G
w
h
i
c
h
s
u
p
p
o
r
t
s
h
i
g
h
d
a
t
a
rat
e
req
u
i
remen
t
s
.
D
i
ffere
n
t
p
i
l
o
t
ai
d
e
d
ch
an
n
el
es
t
i
ma
t
i
o
n
t
ech
n
i
q
u
e
s
w
ere
p
ro
p
o
s
ed
t
o
b
et
t
er
t
rack
t
h
e
ch
a
n
n
e
l
co
n
d
i
t
i
o
n
s
,
w
h
i
ch
co
n
s
u
me
s
b
a
n
d
w
i
d
t
h
,
t
h
u
s
,
co
n
s
i
d
era
b
l
e
d
a
t
a
rat
e
re
d
u
ce
d
.
In
o
rd
er
t
o
es
t
i
m
at
e
t
h
e
ch
a
n
n
e
l
w
i
t
h
mi
n
i
m
u
m
n
u
mb
er
o
f
p
i
l
o
t
s
,
co
mp
re
s
s
i
v
e
s
en
s
i
n
g
C
S
w
as
p
r
o
p
o
s
e
d
t
o
e
ffi
ci
e
n
t
l
y
e
s
t
i
mat
e
t
h
e
c
h
an
n
el
v
ar
i
at
i
o
n
s
.
In
t
h
i
s
p
ap
er,
a
n
o
v
el
d
e
l
ay
d
i
c
t
i
o
n
ar
y
-
b
a
s
ed
CS
w
a
s
d
e
s
i
g
n
e
d
an
d
s
i
m
u
l
a
t
ed
t
o
es
t
i
mat
e
t
h
e
l
i
n
ear
t
i
me
v
ary
i
n
g
(L
T
V
)
ch
an
n
el
.
T
h
e
p
r
o
p
o
s
e
d
d
i
c
t
i
o
n
ar
y
s
h
o
w
s
t
h
e
s
u
i
t
a
b
i
l
i
t
y
o
f
es
t
i
mat
i
n
g
t
h
e
ch
a
n
n
e
l
i
mp
u
l
s
e
res
p
o
n
s
e
(CIR)
w
i
t
h
l
o
w
t
o
mo
d
erat
e
D
o
p
p
l
er
freq
u
e
n
cy
s
h
i
ft
s
w
i
t
h
acce
p
t
a
b
l
e
b
i
t
erro
r
rat
e
(
BE
R)
p
erfo
rma
n
ce.
K
e
y
w
o
r
d
s
:
C
ha
nne
l
e
s
ti
mation
C
ompr
e
s
s
ive
s
e
n
s
ing
L
T
V
c
ha
nne
l
OFDM
Th
i
s
i
s
a
n
o
p
e
n
a
c
ces
s
a
r
t
i
c
l
e
u
n
d
e
r
t
h
e
CC
B
Y
-
SA
l
i
ce
n
s
e
.
C
or
r
e
s
pon
din
g
A
u
th
or
:
M
a
r
ya
m
K.
Abboud
,
C
oll
e
ge
of
I
n
f
or
mation
E
nginee
r
ing
,
Al
-
Na
hr
a
in
Unive
r
s
it
y,
I
r
aq
.
E
mail:
mar
ya
mkhali
f
a
_90@ya
hoo.
c
om
1.
I
NT
RODU
C
T
I
ON
T
he
pe
r
f
o
r
manc
e
of
high
da
ta
r
a
te
tr
a
ns
mi
s
s
ions
ove
r
wir
e
les
s
f
a
ding
c
ha
nne
ls
s
e
ve
r
e
ly
de
gr
a
de
d
due
to
the
mul
ti
pa
th
e
f
f
e
c
ts
whic
h
c
a
us
e
s
int
e
r
s
ymbol
int
e
r
f
e
r
e
nc
e
(
I
S
I
)
.
I
n
or
de
r
to
c
ombat
the
f
a
din
g
e
f
f
e
c
ts
,
OFDM
ha
s
be
e
n
wid
e
ly
a
dopted
to
w
ir
e
les
s
tr
a
n
s
mi
s
s
ion
[
1
-
8]
.
T
he
mul
ti
pa
th
pr
opa
ga
ti
on
c
a
us
e
s
a
ti
me
va
r
ying
c
ha
nne
l
s
tate
inf
o
r
mation
(
C
S
I
)
,
whic
h
ne
e
de
d
to
be
p
r
e
dica
ted
or
e
s
ti
mate
d
us
ing
c
ha
nne
l
e
s
ti
mation
tec
hniques
in
or
de
r
to
r
e
c
ove
r
the
tr
a
ns
mi
tt
e
d
s
ignal.
P
il
ot
a
ided
c
ha
nne
l
e
s
ti
mation
is
the
wi
de
ly
us
e
d
tec
hnique
be
gins
f
r
om
the
t
r
a
dit
ional
tec
hniques
s
uc
h
a
s
,
lea
s
t
s
qua
r
e
(
L
S
)
a
nd
li
ne
a
r
mi
n
im
um
mea
n
s
qua
r
e
(
L
M
M
S
)
,
e
nding
with
many
r
e
c
e
nt
one
s
us
e
d
to
i
mpr
ove
the
e
s
ti
mation
pe
r
f
or
manc
e
[
2,
9]
.
C
ompr
e
s
s
ive
s
e
n
s
ing
(
C
S
)
is
one
o
f
the
r
e
c
e
nt
tec
hn
iques
a
dopted
f
or
c
ha
nne
l
e
s
ti
mation
in
OFDM
s
ys
tems
by
e
xploi
ti
ng
c
ha
nne
l
s
pa
r
s
e
ly
r
e
pr
e
s
e
ntation
with
dictionar
y
ba
s
is
[
10]
.
S
e
ve
r
a
l
a
ppr
oa
c
he
s
h
a
ve
be
e
n
e
mpl
oye
d
to
c
ons
tr
uc
t
mat
r
ice
s
in
or
de
r
to
r
e
pr
e
s
e
nt
the
c
ha
nne
l
in
a
s
pa
r
s
e
manne
r
s
uc
h
a
s
,
dis
c
r
e
t
e
F
our
ie
r
tr
a
ns
f
or
m
(
DF
T
)
a
nd
r
a
ndom
dictionar
ies
.
T
he
s
e
a
ppr
oa
c
he
s
do
not
c
ons
ider
the
ti
me
va
r
iation
pr
ope
r
ty
of
the
c
ha
nne
l
s
ince
the
ti
me
va
r
y
ing
c
ha
nne
l
pa
r
a
me
ter
s
a
r
e
n't
take
n
int
o
a
c
c
ount
[
11
-
14]
.
T
he
main
c
ontr
ibut
ion
o
f
thi
s
pa
pe
r
is
,
the
de
s
ign
of
a
nove
l
de
lay
dictionar
y
-
ba
s
e
d
C
S
tec
hnique
to
ove
r
c
ome
the
pr
oblem
of
the
dictionar
y
pr
opos
e
d
by
[
15]
in
e
s
ti
mating
L
T
V
c
ha
nne
l
in
the
pr
e
s
e
nc
e
of
Dopple
r
f
r
e
que
nc
y
s
hif
ts
.
I
n
[
15]
,
a
s
a
mpl
e
s
pa
c
e
d
de
lay
dictionar
y
wa
s
pr
opos
e
d
to
r
e
c
o
ve
r
the
C
S
I
us
in
g
C
S
in
mul
ti
ple
inpu
t
mul
ti
ple
output
(
M
I
M
O)
-
OFDM
s
ys
tem.
T
he
c
onc
e
pt
o
f
the
r
e
s
e
a
r
c
h
ba
s
e
d
on
e
s
ti
mate
the
c
ha
nne
l
c
oe
f
f
icie
nts
f
or
a
ti
me
va
r
ying
c
ha
nne
l
c
ons
ider
ing
the
us
e
f
ul
O
F
DM
s
ymbol
dur
a
ti
on
r
e
ga
r
ding
the
gua
r
d
ba
nd
,
a
nd
tac
king
the
de
lay
pr
o
f
il
e
int
o
a
c
c
ount.
C
ons
ider
ing
c
ha
nne
l
de
lay
pa
r
a
mete
r
s
,
the
di
c
ti
ona
r
y
pr
opos
e
d
by
[
15]
im
pr
ove
s
it
s
a
bil
it
y
to
r
e
c
ove
r
t
he
C
S
I
e
ve
n
whe
n
number
of
pil
ots
r
e
duc
e
d,
while
it
f
a
il
s
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
A
nov
e
l
de
lay
d
ictionar
y
de
s
ign
for
c
ompr
e
s
s
iv
e
s
e
ns
ing
-
bas
e
d
ti
me
v
ar
y
ing
…
(
M
ar
y
am
K
.
A
bboud
)
2285
in
e
s
ti
mating
L
T
V
c
ha
nne
l
c
oe
f
f
icie
nts
in
the
p
r
e
s
e
nc
e
of
Dopp
ler
e
f
f
e
c
t
s
ince
it
e
xploi
ts
the
ti
me
v
a
r
iabili
ty
c
ha
r
a
c
ter
is
ti
c
of
the
c
ha
nne
l.
W
hich
lea
ds
to
a
c
onc
lus
ion
that,
the
d
ictionar
y
p
r
opos
e
d
by
[
15]
c
a
n't
be
a
ppli
e
d
f
or
c
ha
nne
l
e
s
ti
mation
in
L
T
V
c
ha
nne
ls
s
ince
it
do
e
s
n't
s
e
ns
e
the
Dopple
r
e
f
f
e
c
t
of
the
c
ha
n
ne
l.
T
he
r
e
s
t
o
f
thi
s
pa
pe
r
is
o
r
ga
nize
d
a
s
f
ol
lows
,
in
s
e
c
ti
on
2,
a
b
r
ief
int
r
oduc
ti
on
to
C
S
theor
y
int
r
oduc
e
d
with
the
r
e
qui
r
e
d
a
na
lys
is
o
f
L
T
V
c
ha
nne
l
a
nd
t
he
pr
opos
e
d
s
ys
tem
model
f
or
s
pa
r
s
e
c
ha
nne
l
e
s
ti
mation.
S
im
ulation
tes
ts
,
r
e
quir
e
d
s
ys
tem
pa
r
a
met
e
r
s
,
a
nd
tes
t
r
e
s
ult
s
a
r
e
int
r
oduc
e
d
in
s
e
c
ti
on
3.
F
inally,
t
he
main
c
onc
luded
r
e
mar
ks
a
nd
f
utu
r
e
wor
k
a
r
e
li
s
ted
in
s
e
c
ti
on
4.
2.
L
T
V
CHAN
NE
L
AN
A
L
YSI
S
AN
D
E
S
T
I
M
A
T
I
ON
B
ASE
D
CS
T
HE
ORY
2.
1
.
Com
p
r
e
s
s
ive
s
e
n
s
in
g
S
ince
the
idea
be
hind
s
ignal
s
pa
r
s
it
y
a
ppe
a
r
s
,
m
a
n
y
publi
c
a
ti
ons
o
f
s
pa
r
s
e
s
ignal
r
e
pr
e
s
e
ntations
a
nd
c
ompr
e
s
s
ive
s
e
ns
ing
int
r
oduc
e
d
e
s
pe
c
ially
in
s
ign
a
l
pr
oc
e
s
s
ing
c
omm
unit
y
[
16]
.
W
it
h
c
ompr
e
s
s
ive
s
e
ns
ing,
a
r
e
a
l
f
ini
te
s
ignal
∈
,
c
a
n
be
e
xpr
e
s
s
e
d
in
a
n
or
thonor
mal
ba
s
is
;
x
=
∑
1
(
1)
whe
r
e
=
[
1
2
…
]
r
e
pr
e
s
e
nts
the
or
thonor
mal
ba
s
is
,
a
nd
=
[
1
2
…
]
is
t
he
s
pa
r
s
e
ve
c
tor
whe
r
e
the
number
of
non
-
z
e
r
o
e
leme
nts
(
K
<
<
M
)
much
s
maller
than
the
number
o
f
z
e
r
o
e
leme
nts
a
nd
n
a
med
a
s
a
K
-
s
pa
r
s
e
ve
c
tor
.
Us
ing
mat
r
ix
no
tations
,
=
,
whe
r
e
of
s
ize
M
x
M
[
17
]
.
C
ons
ider
a
c
las
s
ica
l
li
ne
a
r
mea
s
ur
e
ment
model
whe
r
e
=
=
.
W
he
r
e
r
e
pr
e
s
e
nt
the
k
-
s
pa
r
s
e
ve
c
tor
of
s
i
z
e
M
x
1
to
be
e
s
ti
mate
d
us
ing
the
e
f
f
e
c
ti
ve
mea
s
ur
e
ment
matr
ix
,
whe
r
e
the
mea
s
ur
e
ment
matr
ix
is
of
s
ize
N
x
M
,
a
nd
y
is
the
mea
s
ur
e
ment
ve
c
tor
of
s
ize
N
x
1.
He
nc
e
,
e
a
c
h
obs
e
r
va
ti
on
of
y
ve
c
tor
r
e
pr
e
s
e
nts
the
pr
ojec
ti
on
of
ve
c
tor
x
on
a
r
ow
of
th
e
s
e
ns
ing
matr
ix
a
s
de
s
c
r
ibed
in
F
igu
r
e
1
[
18]
.
F
r
om
the
mathe
matica
l
e
xpr
e
s
s
ion
of
C
S
in
the
F
igur
e
1,
it
is
c
lea
r
that
a
non
-
li
ne
a
r
s
ys
tem
of
e
qua
ti
ons
mus
t
be
s
olved
to
r
e
c
ove
r
the
s
pa
r
s
e
ve
c
tor
,
whe
r
e
the
numbe
r
o
f
obs
e
r
va
ti
ons
N
is
much
les
s
tha
n
number
of
unknowns
M
.
S
ince
matr
ix
pr
ojec
ti
ng
t
he
ve
c
tor
x,
low
va
lue
of
incohe
r
e
nc
e
is
r
e
quir
e
d
to
ins
ur
e
mut
ua
ll
y
indepe
nde
nt
matr
ice
s
a
nd
he
nc
e
be
tt
e
r
C
S
pe
r
f
o
r
manc
e
.
T
he
maximum
va
lue
a
mongs
t
inne
r
pr
oduc
t
of
the
Or
thonor
mal
ba
s
is
a
nd
the
or
thonor
mal
m
e
a
s
ur
e
ment
matr
ix
de
f
ined
a
s
incohe
r
e
nc
e
.
T
he
r
e
f
or
e
,
to
r
e
c
ove
r
the
s
pa
r
s
e
ve
c
tor
c
or
r
e
c
tl
y
f
r
om
=
,
the
s
e
ns
ing
matr
ix
s
hould
be
de
s
igned
c
a
r
e
f
ul
ly
[
19
,
20
]
.
F
igur
e
1.
C
S
mathe
matica
l
r
e
pr
e
s
e
ntation
2.
2.
S
ys
t
e
m
m
od
e
l
an
d
L
T
V
c
h
an
n
e
l
I
n
thi
s
pa
pe
r
,
the
OFDM
s
ys
tem
of
F
igu
r
e
2
is
c
o
ns
ider
e
d.
At
the
tr
a
ns
mi
tt
e
r
s
ide
of
thi
s
s
ys
tem,
a
s
tr
e
a
m
of
s
ymbol
s
x[
k]
(
da
ta
d[
k]
a
nd
pi
lot
s
p[
k]
)
a
r
e
mappe
d
us
ing
binar
y
pha
s
e
s
hif
t
ke
ying
(
B
P
S
K)
,
whe
r
e
x[
k]
s
pli
t
int
o
da
ta
blocks
a
f
ter
s
e
r
ia
l
t
o
pa
r
a
l
lel
c
onve
r
s
ion.
E
a
c
h
of
thes
e
blocks
r
e
pr
e
s
e
nt
OFDM
block
c
ontain
da
ta
a
nd
pil
o
t
s
ymbol
s
.
T
he
length
of
e
a
c
h
OFDM
block
is
N
s
ubc
a
r
r
ier
s
.
A
c
yc
li
c
pr
e
f
ix
(
C
P
)
of
length
(
)
is
pr
e
pe
nde
d
to
e
a
c
h
OFDM
block
to
pr
e
ve
nt
a
d
jac
e
nt
int
e
r
f
e
r
e
nc
e
a
nd
c
o
ns
ider
e
d
a
s
a
gua
r
d
ba
nd
(
)
.
Af
ter
C
P
ins
e
r
ti
on,
the
OFDM
block
tr
a
ns
mi
tt
e
d
ove
r
a
n
L
T
V
c
ha
nne
l
whic
h
is
a
mul
ti
pa
th
p
r
o
pa
ga
ti
on
c
ha
nne
l.
I
n
the
pr
opos
e
d
wor
k,
the
L
T
V
c
ha
nne
l
ha
s
be
e
n
a
s
s
umed
to
ha
ve
a
f
ini
te
im
puls
e
r
e
s
pon
s
e
with
L
pa
ths
.
T
h
e
t
r
a
ns
m
it
ter
a
nd
r
e
c
e
iver
a
r
e
a
s
s
umed
s
ync
hr
onize
d
in
both
ti
me
a
nd
c
a
r
r
ier
f
r
e
que
nc
y.
T
he
mul
ti
pa
th
f
a
ding
c
ha
nne
l
r
e
s
pons
e
is
e
xpr
e
s
s
e
d
a
s
f
oll
ows
[
21
,
22
]
;
ℎ
(
)
=
∑
∗
(
−
)
−
1
=
0
(
2)
whe
r
e
,
the
it
h
pa
th
of
wi
r
e
les
s
e
nvir
onment
is
c
ha
r
a
c
ter
ize
d
by
a
pr
opa
ga
ti
on
de
lay
(
)
a
nd
a
tt
e
nua
ti
on
(
)
.
T
he
r
e
c
e
ived
ba
s
e
ba
nd
s
ignal
r
(
t
)
is
modele
d
b
y
two
c
omponents
,
a
mpl
it
ude
a
nd
pha
s
e
,
whic
h
c
a
n
be
e
xpr
e
s
s
e
d
a
s
;
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
5
,
Oc
tober
2020:
2284
-
2291
2286
(
)
=
∑
∗
(
−
)
∗
−
2
−
1
=
0
(
3)
whe
r
e
,
−
2
is
the
c
ompl
e
x
pha
s
e
f
a
c
tor
,
a
nd
f
or
a
na
r
r
ow
ba
nd
tr
a
ns
mi
s
s
ion;
(
−
)
=
(
)
[
23]
.
He
nc
e
;
ℎ
(
)
=
∑
−
2
−
1
=
0
(
4)
T
he
ti
me
va
r
ying
pr
ope
r
ty
o
f
the
c
ha
nne
l
im
pl
ies
t
ha
t
c
ha
nne
l
c
oe
f
f
icie
nts
c
ha
nge
d
ove
r
ti
me.
T
his
c
ha
nging
is
r
e
la
ted
to
the
c
ha
nge
in
the
f
r
e
que
nc
y
of
the
r
e
c
e
ived
s
ignal,
whic
h
r
e
late
d
to
the
r
e
lative
moveme
nt
be
twe
e
n
the
tr
a
ns
mi
tt
e
r
a
nd
the
r
e
c
e
iver
,
He
nc
e
,
the
c
or
r
e
s
p
onding
c
ha
nne
l
de
lay
(
)
is
c
ha
nging
[
21
,
22
]
;
(
)
=
−
c
os
(
5)
whe
r
e
(
)
is
a
f
unc
ti
on
o
f
dis
tanc
e
,
a
nd
he
nc
e
;
ℎ
(
)
=
∑
−
2
∗
[
−
c
o
s
]
−
1
=
0
(
6)
ℎ
(
)
=
∑
−
2
−
1
=
0
2
c
o
s
(
7)
whe
r
e
,
c
os
is
the
Dopple
r
f
r
e
que
nc
y
=
co
s
,
whe
r
e
=
is
the
maximum
Dopple
r
s
hif
t
(
)
.
As
s
umi
ng
that
the
moveme
nt
of
t
he
mobi
le
s
ys
tem
is
unif
or
ml
y
dis
tr
ibu
ted
f
r
om
0
≤
θ
≤
π
r
ad
,
a
nd
θ
is
nor
malize
d.
T
hus
,
the
c
ha
nne
l
im
puls
e
r
e
s
pons
e
is
;
ℎ
(
)
=
∑
−
2
−
1
=
0
2
(
8)
S
ince
thi
s
c
omponent
(
2
)
is
a
f
unc
ti
on
of
ti
me,
a
s
a
r
e
s
ult
,
the
c
ha
nne
l
c
oe
f
f
icie
nts
h
(
t)
a
r
e
ti
me
va
r
ying
.
S
uc
h
a
ti
me
va
r
ying
c
ha
nne
l
is
known
a
s
a
ti
me
s
e
lec
ti
ve
c
ha
nne
l.
How
f
a
s
t
o
r
s
low
the
c
ha
nne
l
c
ha
nge
s
de
pe
nds
on
the
c
ha
nne
l
c
o
he
r
e
nc
e
ti
me
(
)
whe
r
e
the
c
ha
nne
l
is
a
ppr
ox
im
a
tely
c
ons
tant
dur
ing
[
21]
.
At
the
other
ha
nd,
in
or
de
r
to
e
s
ti
mate
the
ti
me
va
r
iant
c
ha
nne
l
c
oe
f
f
icie
nts
us
ing
C
S
tec
hnique,
the
s
e
ns
ing
matr
ix
s
hould
be
de
s
igned
with
a
to
ms
r
e
late
d
to
the
two
e
f
f
e
c
ti
ng
pa
r
a
mete
r
s
(
)
of
the
L
T
V
c
ha
nne
l
of
(
8)
.
T
his
will
lea
d
to
c
omput
e
the
r
a
te
of
c
ha
nge
o
f
the
wi
r
e
les
s
c
ha
nne
l
by
a
na
lyzing
the
c
or
r
e
latio
n
be
twe
e
n
c
ha
nne
l
c
oe
f
f
icie
nts
.
As
s
ume
that
(
)
is
the
c
ha
nne
l
c
oe
f
f
icie
nt
a
t
the
it
h
pa
th
a
t
ti
me
t;
(
)
=
−
2
2
(
9)
T
hus
,
to
c
omput
e
the
c
or
r
e
lation
be
twe
e
n
(
)
a
nd
(
+
∆
)
,
the
e
xpe
c
tation
o
f
(
)
a
nd
(
+
∆
)
,
{
(
)
(
+
∆
)
}
s
hould
be
c
omput
e
d
[
24]
;
(
)
=
−
2
2
(
10)
(
+
∆
)
=
−
2
2
(
+
∆
)
(
11)
thus
;
(
∆
)
=
{
|
|
2
∗
2
∆
}
(
12)
whe
r
e
(
∆
)
r
e
f
e
r
to
the
c
o
r
r
e
lation
f
unc
ti
on
be
twe
e
n
(
)
a
nd
(
+
∆
)
.
L
e
t
|
|
2
nor
malize
d
to
be
1
,
thus
,
(
∆
)
=
{
2
∆
}
(
13)
whic
h
s
umm
a
r
ize
d
a
s
;
(
∆
)
=
0
(
2
∆
)
(
14)
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
A
nov
e
l
de
lay
d
ictionar
y
de
s
ign
for
c
ompr
e
s
s
iv
e
s
e
ns
ing
-
bas
e
d
ti
me
v
ar
y
ing
…
(
M
ar
y
am
K
.
A
bboud
)
2287
whe
r
e
r
e
pr
e
s
e
nts
the
maximum
Dopple
r
f
r
e
que
nc
y
a
nd
0
is
the
B
e
s
s
e
l
f
unc
ti
on
of
0
th
or
de
r
.
F
ina
ll
y,
the
a
utocor
r
e
lation
f
unc
ti
on
(
∆
)
of
L
T
V
c
ha
nne
l
c
a
n
b
e
e
xpr
e
s
s
e
d
in
ter
ms
of
c
ohe
r
e
nc
e
ti
me
[
25
]
;
(
∆
)
=
0
(
2
.
∆
)
(
15)
whe
r
e
;
∆
=
,
=
1
,
2
,
3
…
…
.
,
a
nd
,
=
1
4
.
F
igur
e
2.
OFDM
S
ys
tem
M
ode
l
2.
3
.
S
p
ar
s
e
c
h
an
n
e
l
e
s
t
im
at
io
n
S
ince
C
S
ha
s
ga
ined
a
much
popular
it
y
in
c
omm
un
ica
ti
ons
,
r
e
c
e
ntl
y,
it
is
one
of
the
s
mall
numbe
r
s
of
s
tr
ong
pa
ths
us
e
d
f
o
r
c
ha
nne
l
e
s
ti
mation
.
I
t
a
s
s
umes
that
s
pa
r
s
e
s
ign
a
ls
c
a
n
be
a
ppr
oxim
a
ted
wit
h
a
s
mall
number
of
mea
s
ur
e
ments
c
ompar
e
d
to
the
lar
ge
numb
e
r
r
e
quir
e
d
with
S
ha
nnon
-
Nyquis
t
r
a
te
[
1]
.
H
e
nc
e
,
to
e
s
ti
mate
the
c
ha
nne
l
ve
c
tor
ℎ
∈
×
1
f
r
om
y
mea
s
ur
e
ments
,
a
C
S
pr
oblem
o
f
s
e
c
ti
on
(
2.
1
)
s
hould
be
s
olved,
whe
r
e
y
is
e
xpr
e
s
s
e
d
a
s
f
oll
ows
;
=
ℎ
+
(
16)
n
:
AW
GN
nois
e
with
z
e
r
o
mea
n
a
nd
va
r
ianc
e
2
=
0
2
:
T
he
s
e
ns
ing
matr
ix
T
he
s
pa
r
s
e
r
e
pr
e
s
e
ntation
of
da
ta
in
ter
ms
of
a
tom
s
is
the
main
objec
ti
ve
of
the
dictionar
y
de
s
ign,
whic
h
late
r
us
e
d
to
r
e
c
ons
tr
uc
t
the
s
pa
r
s
e
s
ignal,
w
he
r
e
ℎ
a
s
s
umed
to
be
K
-
s
pa
r
s
e
C
S
I
a
nd
it
s
e
ne
r
gy
unif
or
ml
y
dis
tr
ibut
e
d
a
mong
a
s
mall
number
of
taps
witho
ut
a
ny
pr
ior
knowle
dge
of
their
loca
ti
on,
whic
h
mus
t
be
e
s
ti
mate
d
with
e
f
f
e
c
ti
ve
s
e
ns
ing.
I
t
is
c
lea
r
f
r
om
(
15
)
tha
t
c
ha
nne
l
c
oe
f
f
icie
nts
a
r
e
c
ha
nge
d
with
r
e
s
pe
c
t
to
the
c
ha
nne
l
c
ohe
r
e
nc
e
ti
me.
T
he
r
e
f
or
e
,
in
thi
s
pa
pe
r
,
t
he
dictionar
y
matr
ix
is
de
s
igned
in
a
manne
r
in
whic
h
the
two
de
lay
pa
r
a
mete
r
s
o
f
the
a
utocor
r
e
lation
f
unc
ti
on
a
r
e
take
n
int
o
a
c
c
ount.
T
he
e
quis
pa
c
e
d
pil
ot
s
u
bc
a
r
r
ier
s
p[
k]
a
r
e
e
mbedde
d
with
in
the
da
ta
s
ubc
a
r
r
ie
r
s
d[
k]
of
the
OFDM
s
ys
tem
of
F
igu
r
e
2,
whe
r
e
the
n
umber
of
tr
a
ini
ng
pil
ots
is
,
a
nd
∆
is
a
s
s
umed
to
be
a
tape
d
de
l
a
y
pr
of
il
e
a
long
the
OFDM
s
ymbol
.
W
he
r
e
;
∆
=
[
0
,
×
,
]
=
1
,
2
,
3
,
…
,
(
17)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
5
,
Oc
tober
2020:
2284
-
2291
2288
r
e
pr
e
s
e
nt
the
mi
nim
um
c
ha
nne
l
tap
s
pa
c
ing
w
hich
e
qua
ls
to
(
×
−
×
×
)
,
a
nd
is
the
gua
r
d
int
e
r
va
l
whic
h
a
s
s
umed
to
be
the
C
P
a
ppe
nde
d
to
e
a
c
h
OF
DM
s
ymbol
in
or
de
r
to
mi
ti
ga
te
the
I
C
I
,
a
nd
is
the
OFDM
s
a
mpl
e
ti
me.
An
N
x
N
dictiona
r
y
matr
ix
is
c
ons
tr
u
c
ted
with
a
tom
s
r
e
late
d
to
e
a
c
h
s
ubc
a
r
r
ie
r
pos
it
ion
ℓ
a
long
the
OFDM
block
length
,
a
nd
mul
ti
p
li
e
d
by
the
tape
d
de
lay
a
tom
s
of
∆
.
=
(
+
)
,
is
the
OFDM
s
ymbol
ti
me
including
.
T
he
r
e
f
o
r
e
,
t
he
dictionar
y
×
is
r
e
pr
e
s
e
nted
a
s
f
ol
lows
;
=
[
−
2
ℓ
1
1
⋯
−
2
ℓ
1
⋮
⋱
⋮
−
2
ℓ
1
⋯
−
2
ℓ
]
×
(
18)
whe
r
e
the
r
ows
o
f
dictionar
y
matr
ix
D
a
r
e
r
e
f
e
r
t
o
th
e
s
ubc
a
r
r
ier
s
pos
it
ions
a
long
the
OFDM
s
ymb
ol,
while
c
olum
ns
a
r
e
r
e
f
e
r
to
the
de
lay
ve
c
tor
of
e
a
c
h
s
ubc
a
r
r
ier
.
R
e
ga
r
ding
s
e
ns
ing
matr
ix
.
A
c
ons
tr
uc
ti
on,
a
n
r
ows
a
r
e
s
e
lec
ted
f
r
om
D
r
e
late
d
to
pil
ot
loca
ti
ons
,
a
nd
mul
ti
pli
e
d
by
×
matr
ix
of
p
il
ot
da
ta
us
ing
do
t
pr
oduc
t
mul
ti
pli
c
a
ti
on;
=
[
−
2
ℓ
1
1
⋯
−
2
ℓ
1
⋮
⋱
⋮
−
2
ℓ
1
⋯
−
2
ℓ
]
×
.
[
−
1
⋯
−
1
(
)
⋮
⋱
⋮
−
⋯
−
(
)
]
×
(
19)
is
the
pil
ot
s
ymbol
us
e
d
f
o
r
e
s
ti
mation
c
ons
ider
ing
e
qua
ll
y
li
ke
ly
s
ymbol
s
o
f
[
0,
1
]
,
a
nd
=
1
,
2
,
3
,
…
.
,
.
Dif
f
e
r
e
nt
s
pa
r
s
e
s
ignal
r
e
c
ove
r
y
a
lgo
r
it
hms
c
a
n
be
a
ppli
e
d
to
s
olve
the
C
S
p
r
oblem
in
a
number
of
it
e
r
a
ti
ons
to
mi
ni
mi
z
e
C
S
e
r
r
o
r
with
r
e
s
pe
c
t
to
D
.
Onc
e
the
c
ha
nne
l
dom
inant
taps
e
s
ti
mate
d
(
i.
e
.
r
e
c
ove
r
ing
of
the
s
pa
r
s
e
ve
c
tor
)
,
the
whole
C
I
R
is
bui
lt
a
t
a
ll
loca
ti
ons
s
im
ply
f
r
om
ℎ
̂
=
×
,
a
nd
the
e
qua
li
z
a
ti
on
pr
oc
e
s
s
im
pleme
nted.
3.
S
I
M
UL
AT
I
ON
T
E
S
T
AN
D
RE
S
UL
T
S
I
n
th
is
pa
pe
r
,
t
he
O
F
DM
s
ys
t
e
m
of
F
i
gu
r
e
2
c
o
mp
a
r
e
s
th
e
tes
t
r
e
s
u
lt
s
o
f
bo
th
lea
s
t
s
q
ua
r
e
(
LS
)
a
nd
ba
s
i
s
p
u
r
s
u
i
t
(
BP
)
ba
s
e
d
c
ha
nne
l
e
s
t
im
a
t
i
o
n
t
e
c
h
n
iqu
e
s
.
D
i
f
f
e
r
e
nt
OF
DM
s
ys
te
m
p
a
r
a
m
e
t
e
r
s
a
r
e
l
is
te
d
i
n
T
a
bl
e
1
.
I
n
a
d
d
it
io
n
t
o
A
W
GN
no
is
e
,
a
6
ta
p
L
T
V
c
h
a
n
ne
l
is
c
o
ns
i
de
r
e
d
a
s
a
R
a
yle
i
gh
f
a
di
ng
c
h
a
n
ne
l
wi
t
h
p
a
t
hs
d
e
l
a
ys
a
n
d
p
owe
r
ve
c
t
or
s
s
t
a
n
da
r
d
ize
d
by
I
T
U
c
h
a
nn
e
l
m
ode
l
of
T
a
b
le
2
.
B
a
s
is
pu
r
s
ui
t
(
B
P
)
a
l
go
r
it
h
m
is
us
e
d
t
o
s
ol
ve
th
e
c
on
ve
x
o
pt
im
iz
a
t
io
n
p
r
ob
le
m
w
i
th
M
a
tL
a
b
f
o
r
s
pa
r
s
e
s
i
gn
a
l
r
e
c
o
ve
r
y
,
w
he
r
e
it
us
e
s
t
he
1
_
t
o
r
e
gu
la
r
ize
t
he
p
r
ob
le
m
[
9]
.
T
he
pe
r
f
o
r
ma
nc
e
tes
t
o
f
O
F
D
M
s
ys
t
e
m
w
a
s
s
ho
wn
i
n
t
he
f
o
r
m
o
f
b
i
t
e
r
r
o
r
r
a
t
e
(
B
E
R
)
v
e
r
s
us
s
ig
na
l
t
o
n
o
is
e
r
a
ti
o
(
S
NR
)
,
w
he
r
e
S
NR
is
d
e
t
e
r
m
i
n
e
d
by
th
e
c
or
r
e
s
p
on
di
ng
(
E
b
N
o
⁄
)
i
n
dB
.
T
a
ble
1.
OFDM
s
ys
tem
p
a
r
a
mete
r
s
P
a
r
a
me
te
r
V
a
lu
e
N
umbe
r
of
t
r
a
ns
mi
tt
e
d bi
ts
M
odul
a
ti
on
S
a
mpl
in
g T
im
e
(
T
s
)
O
F
D
M
S
ubc
a
r
r
ie
r
s
N
umbe
r
of
pi
lo
ts
C
yc
li
c
pr
e
f
ix
l
e
ngt
h (
)
M
a
xi
mum
D
oppl
e
r
s
hi
f
t
(
)
H
z
64000, 128000, 256000
B
P
S
K
1 µs
e
c
64, 128, 256
16, 13
16
0,
10, 20,
40
I
n
F
i
gur
e
3,
th
e
B
E
R
p
e
r
f
o
r
m
a
n
c
e
of
O
F
D
M
s
y
s
te
m
o
v
e
r
a
mu
lt
i
pa
th
in
do
or
c
h
a
n
ne
l
e
nv
ir
o
nm
e
n
t
u
s
in
g
L
S
a
n
d
B
P
i
s
pr
e
s
e
nt
e
d.
I
n
a
d
dit
io
n
t
o
c
omp
a
r
e
t
h
e
e
s
ti
m
a
t
io
n
p
e
r
f
or
m
a
nc
e
o
f
B
P
o
ve
r
L
S
a
lg
or
it
h
m,
t
h
e
p
ur
p
o
s
e
of
th
i
s
t
e
s
t
i
s
to
s
h
ow
th
e
a
bi
li
ty
of
t
h
e
pr
o
po
s
e
d
d
ic
ti
on
a
r
y
to
r
e
c
o
v
e
r
t
h
e
C
S
I
wit
h
di
f
f
e
r
e
nt
d
e
la
y
pa
r
a
me
te
r
s
f
or
bo
th
in
do
or
a
nd
o
ut
do
or
e
n
vir
on
me
nt
s
.
I
n
th
e
pr
e
s
e
n
t
t
e
s
t,
B
P
p
e
r
f
o
r
m
a
n
c
e
o
utp
e
r
f
or
ms
L
S
te
c
hni
qu
e
b
y
a
b
out
4.
5
d
B
a
t
a
B
E
R
of
10
−
3
with
16
pi
lot
s
ou
t
of
64
s
u
b
c
a
r
r
i
e
r
s
a
nd
z
e
r
o
Do
ppl
e
r
f
r
e
q
u
e
n
c
y.
I
n
F
ig
ur
e
4,
L
S
a
nd
B
P
a
l
go
r
it
hm
s
a
r
e
t
e
s
t
e
d
ov
e
r
a
m
ul
ti
p
a
th
out
do
or
c
h
a
n
n
e
l
e
n
vir
on
m
e
nt
of
T
a
b
le
2.
I
n
th
is
t
e
s
t,
th
e
OF
D
M
bl
oc
k
c
on
ta
in
in
g
6
4
s
u
bc
a
r
r
ier
s
a
n
d
th
e
nu
mb
e
r
of
pil
ot
s
u
bc
a
r
r
i
e
r
s
u
s
e
d
i
s
1
6.
Dif
f
e
r
e
n
t
Do
pp
ler
s
hi
f
t
s
a
r
e
c
on
s
id
e
r
e
d
in
or
de
r
t
o
t
e
s
t
t
he
r
e
c
o
v
e
r
i
ng
a
b
il
it
y
of
th
e
pr
o
po
s
e
d
d
ic
ti
on
a
r
y
i
n
t
he
pr
e
s
e
n
c
e
of
Do
pp
ler
e
f
f
e
c
t
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
A
nov
e
l
de
lay
d
ictionar
y
de
s
ign
for
c
ompr
e
s
s
iv
e
s
e
ns
ing
-
bas
e
d
ti
me
v
ar
y
ing
…
(
M
ar
y
am
K
.
A
bboud
)
2289
F
igur
e
3.
B
E
R
pe
r
f
or
manc
e
with
=
0
,
=
16
,
=
64
F
igur
e
4.
B
E
R
pe
r
f
or
manc
e
with
=
16
,
=
6
4
T
a
ble
2.
I
T
U
C
ha
nne
l
M
ode
ls
[
26]
I
ndoor
O
ut
door
D
e
la
y (
ns
)
P
ow
e
r
(
dB
)
D
e
la
y (
ns
)
P
ow
e
r
(
dB
)
0
0
0
0
50
-
3
310
-
1.5
110
-
10
710
-
9.0
170
-
18
1090
-
10.0
290
-
26
1730
-
15.0
310
-
32
2510
-
20.0
As
c
ould
be
noti
c
e
d,
C
S
ba
s
e
d
c
ha
nne
l
e
s
ti
matio
n
a
lg
or
it
h
m
im
pr
ove
s
the
e
s
ti
mation
pe
r
f
o
r
manc
e
a
s
c
ompar
e
d
to
L
S
a
lgor
it
hm
e
ve
n
with
Dopple
r
e
f
f
e
c
t.
B
y
c
o
mpar
ing
B
P
pe
r
f
or
manc
e
f
or
both
=
0
,
a
nd
=
10
,
it
is
c
lea
r
that
a
s
incr
e
a
s
e
d
to
10
Hz
,
the
p
e
r
f
or
manc
e
tes
t
de
gr
a
de
d
by
a
bo
ut
15
dB
a
t
a
B
E
R
of
10
−
3
.
At
the
other
ha
nd,
B
P
pe
r
f
or
manc
e
de
gr
a
de
d
whe
n
incr
e
a
s
e
d
mor
e
than
10
Hz
a
nd
be
c
om
e
wor
s
e
than
L
S
unles
s
the
number
of
pil
ots
u
s
e
d
f
or
e
s
ti
mation
incr
e
a
s
e
d,
whic
h
in
tur
n
i
mpr
ove
s
L
S
pe
r
f
or
manc
e
.
T
he
s
a
me
tes
t
wa
s
r
e
pe
a
ted
with
a
lowe
r
nu
mber
o
f
pi
lot
s
,
whe
r
e
13
p
il
ots
wa
s
ins
e
r
te
d
withi
n
the
OFDM
block
a
t
e
qua
ll
y
s
pa
c
e
d
loc
a
ti
ons
ins
tea
d
of
16
pil
ots
a
s
s
hown
in
F
igur
e
5.
T
he
tes
t
s
h
ows
that
the
B
P
pe
r
f
or
manc
e
de
gr
a
de
d
but
s
ti
ll
much
be
tt
e
r
than
L
S
.
T
his
obs
e
r
va
ti
on
lea
ds
to
the
pos
s
ibi
li
ty
of
us
ing
r
e
duc
e
d
number
of
pi
lot
s
f
o
r
c
ha
nne
l
e
s
ti
mation
w
it
hout
s
a
c
r
if
icing
the
a
c
c
ur
a
c
y
o
f
c
ha
nne
l
e
s
ti
mati
on,
whe
n
the
r
a
te
of
c
ha
nge
of
c
ha
nne
l
c
oe
f
f
icie
nts
incr
e
a
s
ing
a
c
c
or
ding
to
Dopple
r
s
hif
t
e
f
f
e
c
ts
.
F
igur
e
5.
B
E
R
pe
r
f
or
manc
e
with
=
13
,
=
64
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
5
,
Oc
tober
2020:
2284
-
2291
2290
Anothe
r
tes
t
c
ons
ide
r
ing
dif
f
e
r
e
nt
s
ubc
a
r
r
ier
nu
mber
s
a
nd
Dopple
r
s
hif
ts
is
s
hown
in
F
igur
e
6
.
T
he
tes
t
r
e
s
ult
s
pr
ove
d
that
B
P
e
xc
e
e
de
d
L
S
pe
r
f
o
r
manc
e
.
B
ut
thi
s
s
upe
r
ior
it
y
is
s
ti
ll
li
mi
ted
by
the
a
mount
of
Dopple
r
s
hif
t
a
nd
number
of
pil
ots
,
whe
r
e
it
is
de
gr
a
de
d
whe
n
incr
e
a
s
e
d
a
bove
than
20
a
nd
40
f
or
128
a
nd
256
OFDM
s
ubc
a
r
r
ier
s
r
e
s
pe
c
ti
ve
ly
with
16
pil
ots
.
T
his
de
gr
a
da
ti
on
is
s
hown
in
F
igur
e
7,
whe
r
e
L
S
a
nd
B
P
a
lgor
it
hms
a
r
e
tes
ted
with,
=
30
f
or
=
128
,
a
nd
=
50
f
or
=
256
.
F
inally
,
it
c
ould
be
c
onc
luded
that
,
a
s
the
a
mount
of
Doppl
e
r
s
hif
t
incr
e
a
s
e
,
the
e
s
ti
mation
pe
r
f
o
r
manc
e
de
gr
a
de
d
due
to
t
he
Dopple
r
e
f
f
e
c
t
on
the
c
ha
nne
l.
T
his
de
gr
a
da
ti
on
manif
e
s
ts
it
s
e
lf
whe
n
the
number
of
s
u
bc
a
r
r
ier
s
incr
e
a
s
e
d,
whe
r
e
the
s
ub
c
a
r
r
ier
ba
ndwidth
wil
l
be
d
e
c
r
e
a
s
e
d,
s
o,
it
is
mo
r
e
s
e
ns
it
ive
to
the
Dopple
r
a
nd
r
e
quir
e
s
a
n
a
ddit
ional
pr
oc
e
s
s
to
e
li
mi
na
te
c
a
r
r
ier
f
r
e
que
nc
y
of
f
s
e
t
(
C
F
O
)
.
F
igur
e
6.
B
E
R
pe
r
f
or
manc
e
with
=
16
,
=
128
256
F
igur
e
7.
B
E
R
pe
r
f
or
manc
e
with
=
16
4.
CONC
L
USI
ONS
AN
D
F
UT
UR
E
WORKS
I
n
th
is
pa
pe
r
,
the
p
r
opos
e
d
dictionar
y
de
s
ign
wa
s
t
e
s
ted
to
a
c
hieving
the
de
s
ir
e
d
r
e
s
ult
s
of
B
P
ba
s
e
d
C
S
a
lgor
it
hm
in
e
s
ti
mating
of
C
I
R
of
a
L
T
V
c
ha
nn
e
l.
At
the
other
ha
nd
,
thi
s
pe
r
f
or
manc
e
is
li
mi
ted
to
the
low
to
moder
a
te
Dopple
r
f
r
e
que
nc
y
s
hif
ts
.
T
he
f
u
tu
r
e
wor
k
may
be
c
a
r
r
ied
to
e
xtend
the
c
ur
r
e
nt
wor
k
to
be
us
e
d
f
or
e
s
ti
mation
o
f
L
T
V
c
ha
nne
l
with
high
mobi
li
ty
or
high
Dopple
r
f
r
e
que
nc
y
s
hif
ts
.
RE
F
E
RE
NC
E
S
[1
]
Ch
ri
s
t
i
an
R.
B.
,
Sh
e
n
g
l
i
Z
.
,
W
e
i
an
C.
,
Pe
t
er
W
.
,
“
S
p
ars
e
Ch
an
n
el
E
s
t
i
ma
t
i
o
n
f
o
r
O
FD
M
:
O
v
er
-
co
m
p
l
e
t
e
D
i
c
t
i
o
n
a
ri
e
s
an
d
Su
p
er
Res
o
l
u
t
i
o
n
,”
IE
E
E
W
o
r
ks
h
o
p
o
n
S
i
g
n
a
l
P
r
o
ce
s
s
i
n
g
A
d
v
a
n
ce
s
i
n
W
i
r
el
e
s
s
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
2
0
0
9
.
[2
]
Sw
eat
M.
P.
an
d
A
.
N
.
J
ad
h
av
,
“
Ch
an
n
e
l
E
s
t
i
ma
t
i
o
n
U
s
i
n
g
L
S
an
d
MMSE
E
s
t
i
mat
o
rs
,”
In
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
n
R
ece
n
t
a
n
d
In
n
o
va
t
i
o
n
T
r
en
d
s
i
n
Co
m
p
u
t
i
n
g
a
n
d
Co
m
m
u
n
i
ca
t
i
o
n
,
v
o
l
.
2
,
n
o
.
3
,
p
p
.
5
1
-
5
5
,
2
0
1
4
.
[3
]
Sak
i
n
a
A
.
,
N
o
u
re
d
d
i
n
e
D
.
,
Sad
d
ek
A
.
,
“
Bl
i
n
d
freq
u
e
n
cy
o
ff
s
et
es
t
i
ma
t
o
r
f
o
r
O
FD
M
s
y
s
t
ems
,”
TE
LKO
M
N
IKA
Tel
eco
m
m
u
n
i
ca
t
i
o
n
Co
m
p
u
t
i
n
g
E
l
ect
r
o
n
i
c
s
a
n
d
Co
n
t
r
o
l
,
v
o
l
.
17
,
n
o
.
6
,
p
p
.
2
7
2
2
-
2
7
2
8
,
2
0
1
9
.
[4
]
Y
.
L
i
,
L
.
J
.
Ci
mi
n
i
,
N
.
R.
,
“
So
l
l
en
b
er
g
er.
Ro
b
u
s
t
Ch
an
n
el
E
s
t
i
ma
t
i
o
n
fo
r
O
F
D
M
Sy
s
t
ems
w
i
t
h
Rap
i
d
D
i
s
p
ers
i
v
e
Fad
i
n
g
Ch
a
n
n
e
l
s
,”
IE
E
E
T
r
a
n
s
a
ct
i
o
n
s
o
n
Co
m
m
u
n
i
ca
t
i
o
n
s
,
v
o
l
.
4
6
,
n
o
.
7
,
p
p
.
9
0
2
-
9
1
5
,
1
9
9
8
.
[5
]
T
.
H
w
an
g
an
d
C.
Y
an
g
,
“
O
F
D
M
an
d
I
t
s
W
i
r
el
e
s
s
A
p
p
l
i
cat
i
o
n
s
:
A
Su
rv
e
y
,
"
IE
E
E
T
r
a
n
s
a
ct
i
o
n
o
n
V
eh
i
c
u
l
a
r
Tech
n
o
l
o
g
y
,
v
o
l
.
5
8
,
n
o
.
4
,
p
p
.
1
6
7
3
-
1
6
9
4
,
2
0
0
9
.
[6
]
A
.
D
o
w
l
er,
A
.
D
o
u
fe
x
i
,
an
d
A
.
N
i
x
,
“
Perfo
rma
n
ce
E
v
al
u
at
i
o
n
o
f
Ch
an
n
el
E
s
t
i
mat
i
o
n
T
ech
n
i
q
u
e
s
fo
r
a
Mo
b
i
l
e
Fo
u
rt
h
G
en
erat
i
o
n
W
i
d
e
A
rea
O
FD
M
S
y
s
t
em
,
”
IE
E
E
5
6
t
h
V
eh
i
cu
l
a
r
Tech
n
o
l
o
g
y
Co
n
f
e
r
en
ce
,
V
T
C
Fal
l
,
2
0
0
2
.
[7
]
S.
Pramo
n
o
,
E
.
T
r
i
y
o
n
o
,
“
Perfo
rma
n
ce
o
f
Ch
a
n
n
e
l
E
s
t
i
ma
t
i
o
n
i
n
MIM
O
-
O
F
D
M
Sy
s
t
em
s
,”
TE
LK
O
M
NI
KA
Tel
eco
m
m
u
n
i
ca
t
i
o
n
Co
m
p
u
t
i
n
g
E
l
ect
r
o
n
i
c
s
a
n
d
Co
n
t
r
o
l
,
v
ol.
1
1
,
n
o.
2
,
p
p
.
3
5
5
-
3
6
2
,
2
0
1
3
.
[8
]
E
.
Si
n
g
h
,
“
A
D
FT
b
as
ed
ch
a
n
n
e
l
es
t
i
ma
t
i
o
n
t
ec
h
n
i
q
u
e
i
n
o
rt
h
o
g
o
n
a
l
-
freq
u
en
c
y
d
i
v
i
s
i
o
n
-
m
u
l
t
i
p
l
e
x
i
n
g
(O
FD
M):
A
Rev
i
e
w
,”
In
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
R
ecen
t
R
es
e
a
r
ch
A
s
p
ec
t
s
IS
S
N
,
v
o
l
.
3
,
2
0
1
6
.
[9
]
Sreej
i
t
h
K
.
,
Sh
eet
a
l
K
.
,
“
Sp
ars
e
Ch
an
n
el
E
s
t
i
mat
i
o
n
i
n
O
FD
M
Sy
s
t
em
s
w
i
t
h
V
i
rt
u
al
Su
b
-
Carri
ers
,”
IE
E
E
G
l
o
b
a
l
Co
m
m
u
n
i
c
a
t
i
o
n
s
Co
n
f
e
r
en
ce
(
G
LO
B
E
C
O
M
)
,
2
0
1
6
.
[
1
0
]
D
a
v
i
d
L
.
D
o
n
o
h
o
,
“
C
o
m
p
r
e
s
s
e
d
S
e
n
s
i
n
g
,”
I
E
E
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
I
n
f
o
r
m
a
t
i
o
n
T
h
e
o
r
y
,
v
o
l
.
5
2
,
no
.
4
,
p
p
.
0
0
1
8
-
9
4
4
8
,
2
0
0
6
.
[1
1
]
Ch
ri
s
t
i
an
R.
B.
,
Z
h
ao
h
u
i
W
.
,
J
i
an
z
h
o
n
g
H
.
,
Sh
e
n
g
l
i
Z
.
,
“
A
p
p
l
i
cat
i
o
n
o
f
co
m
p
res
s
i
v
e
s
en
s
i
n
g
t
o
s
p
ars
e
c
h
an
n
e
l
es
t
i
mat
i
o
n
,”
IE
E
E
Co
m
m
u
n
i
c
a
t
i
o
n
s
M
a
g
a
z
i
n
e
,
v
o
l
.
48
,
n
o
.
11
,
p
p
.
1
6
4
-
1
7
4
,
2
0
1
0
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
A
nov
e
l
de
lay
d
ictionar
y
de
s
ign
for
c
ompr
e
s
s
iv
e
s
e
ns
ing
-
bas
e
d
ti
me
v
ar
y
ing
…
(
M
ar
y
am
K
.
A
bboud
)
2291
[1
2
]
K
.
Z
h
en
g
,
J
.
Su
a
n
d
W
.
W
an
g
, “
D
FT
-
Bas
e
d
Ch
an
n
el
E
s
t
i
mat
i
o
n
i
n
C
O
MB
-
T
Y
PE
P
i
l
o
t
-
A
i
d
ed
O
F
D
M
Sy
s
t
em
s
w
i
t
h
V
i
r
t
u
a
l
Carri
er
,”
I
E
E
E
1
8
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
S
y
m
p
o
s
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u
m
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n
P
er
s
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n
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l
,
In
d
o
o
r
a
n
d
M
o
b
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l
e
R
a
d
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o
C
o
m
m
u
n
i
c
a
t
i
o
n
,
2
0
0
7
.
[1
3
]
J
.
K
i
m,
J
.
Mo
o
n
,
Y
.
Ban
g
,
H
.
L
ee
,
“
A
Pract
i
cal
Met
h
o
d
o
f
D
es
i
g
n
i
n
g
D
FT
-
b
as
e
d
C
h
an
n
el
E
s
t
i
mat
o
r
,”
IE
E
E
8
t
h
In
t
e
r
n
a
t
i
o
n
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l
Co
n
f
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e
n
ce
o
n
U
b
i
q
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n
d
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u
t
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r
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o
r
k
(ICU
F
N),
p
p
.
7
1
0
-
7
1
4
,
2
0
1
6
.
[1
4
]
H
.
Z
h
u
,
Y
.
G
e
a
n
d
X
.
Ch
e
n
,
“
D
F
T
-
b
a
s
ed
A
d
ap
t
i
v
e
Ch
a
n
n
el
E
s
t
i
mat
i
o
n
fo
r
O
F
D
M
Sy
s
t
em
s
,”
IE
E
E
1
6
t
h
In
t
er
n
a
t
i
o
n
a
l
Co
n
f
er
e
n
ce
o
n
C
o
m
m
u
n
i
c
a
t
i
o
n
Tech
n
o
l
o
g
y
(ICCT
),
p
p
.
5
1
5
-
5
1
7
,
2
0
1
5
.
[
1
5
]
F
a
r
z
a
n
a
K
.
,
A
n
n
a
V
.
,
H
a
s
s
a
n
N
.
C
.
,
P
i
e
t
r
o
S
.
,
“
P
i
l
o
t
R
e
d
u
c
t
i
o
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T
e
c
h
n
i
q
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e
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f
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