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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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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
9
2
3
-
5
9
3
1
5924
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,
th
e
s
y
s
te
m
p
er
f
o
r
m
an
ce
o
f
Di
f
f
-
D
ST
C
is
co
n
s
id
e
r
ed
lo
w
i
n
ter
m
s
o
f
b
it
er
r
o
r
r
ate
w
ith
a
h
i
g
h
d
ec
o
d
in
g
co
m
p
lex
i
t
y
.
Di
f
f
er
en
tial
tec
h
n
iq
u
es
w
i
th
b
ea
m
f
o
r
m
i
n
g
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
to
r
ec
eiv
e
tr
an
s
m
it
ted
d
ata
b
y
co
m
b
in
i
n
g
th
e
d
if
f
er
e
n
tial
d
iv
er
s
it
y
s
tr
ateg
y
an
d
b
ea
m
f
o
r
m
i
n
g
s
tr
ateg
y
[
1
-
3
]
.
T
h
is
tech
n
iq
u
e
d
o
es
n
o
t
r
eq
u
ir
e
an
y
C
SI
at
t
h
e
r
ec
eiv
er
o
r
at
th
e
tr
an
s
m
it
ter
,
h
o
w
e
v
er
it
n
ee
d
s
(
R
+
1
)
ti
m
e
s
lo
t
s
to
tr
a
n
s
m
it
ea
ch
s
y
m
b
o
l
w
h
er
e
R
is
th
e
n
u
m
b
er
o
f
r
ela
y
n
o
d
es.
As
a
r
esu
lt,
t
h
e
s
p
ec
tr
al
ef
f
icien
c
y
w
ill
d
ec
r
ea
s
e
w
it
h
th
e
in
cr
ea
s
e
o
f
th
e
n
u
m
b
er
o
f
u
s
ed
r
ela
y
s
.
Fi
n
all
y
,
s
ev
er
al
r
ela
y
in
g
p
r
o
to
co
ls
h
av
e
b
ee
n
p
r
o
p
o
s
ed
[
4
-
8
,
2
6
]
f
o
r
w
ir
eles
s
r
ela
y
n
et
w
o
r
k
s
s
u
ch
as
a
m
p
lify
-
an
d
-
f
o
r
w
a
r
d
(
AF)
an
d
d
ec
o
d
e
-
a
n
d
-
f
o
r
w
ar
d
(
DF)
p
r
o
to
co
l.
I
n
t
h
is
p
ap
er
,
w
e
p
r
o
p
o
s
e
a
n
o
v
el
s
tr
ate
g
y
b
ased
o
n
b
ea
m
-
f
o
r
m
in
g
a
n
d
d
i
f
f
er
e
n
tial
c
o
d
in
g
w
i
th
p
o
w
er
allo
ca
tio
n
s
ch
e
m
e
to
b
e
u
s
ed
f
o
r
t
w
o
-
w
a
y
w
ir
ele
s
s
r
ela
y
n
et
w
o
r
k
s
th
at
i
m
p
r
o
v
es
th
e
o
v
er
all
s
y
s
te
m
p
er
f
o
r
m
a
n
ce
in
ter
m
s
o
f
b
it
er
r
o
r
r
ate
(
B
E
R
)
w
it
h
lo
w
d
ec
o
d
in
g
co
m
p
le
x
it
y
a
n
d
l
o
w
late
n
c
y
w
i
th
o
u
t
r
eq
u
ir
in
g
C
SI
at
an
y
tr
a
n
s
m
itti
n
g
o
r
r
ec
eiv
i
n
g
n
o
d
e.
2.
RE
S
E
ARCH
M
E
T
H
O
D
Dif
f
er
en
t
ial
en
co
d
in
g
tec
h
n
iq
u
es
b
ased
o
n
t
h
e
a
m
p
l
if
y
-
an
d
-
f
o
r
w
ar
d
p
r
o
to
co
l
ar
e
w
ell
k
n
o
w
n
f
o
r
th
eir
p
o
o
r
B
E
R
p
e
r
f
o
r
m
a
n
ce
,
h
ig
h
d
ec
o
d
in
g
co
m
p
le
x
it
y
,
a
n
d
lo
n
g
late
n
c
y
.
On
t
h
e
o
th
e
r
h
an
d
,
d
if
f
er
en
tial
b
ea
m
f
o
r
m
in
g
tech
n
iq
u
e
s
p
r
o
v
id
e
h
i
g
h
er
B
E
R
p
er
f
o
r
m
an
ce
,
o
p
ti
m
al
d
ec
o
d
in
g
co
m
p
lex
i
t
y
,
an
d
lo
w
laten
c
y
[
1
-
4
]
.
T
h
is
ar
ticle
co
m
b
in
e
s
t
h
e
d
i
f
f
er
e
n
tial
d
i
v
er
s
it
y
a
n
d
t
h
e
d
is
tr
ib
u
ted
b
ea
m
f
o
r
m
i
n
g
tec
h
n
iq
u
es
u
s
i
n
g
eit
h
er
th
e
AF
o
r
th
e
D
F
p
r
o
to
co
l,
as
w
el
l
as
e
m
p
lo
y
s
a
p
o
w
er
allo
ca
tio
n
s
tr
ateg
y
a
n
d
M
-
ar
y
p
h
ase
s
h
i
f
t
k
e
y
i
n
g
(
M
-
P
SK)
co
n
s
tel
latio
n
s
to
p
r
o
v
id
e
a
n
i
m
p
r
o
v
ed
B
E
R
p
er
f
o
r
m
an
ce
,
lo
w
d
ec
o
d
in
g
co
m
p
le
x
it
y
,
an
d
o
p
ti
m
al
d
ela
y
w
it
h
o
u
t th
e
n
ee
d
f
o
r
an
y
C
SI.
2
.
1
.
Sy
s
t
em
m
o
del
As
th
e
d
i
f
f
er
en
tia
l
b
ea
m
f
o
r
m
in
g
tech
n
iq
u
e
d
o
es
n
o
t
p
er
f
o
r
m
an
y
c
h
an
n
el
e
s
ti
m
atio
n
a
t
all
n
o
d
es,
th
en
t
h
e
k
n
o
w
led
g
e
o
f
an
y
C
SI
is
n
o
t
r
eq
u
ir
ed
[
1
,
6
]
.
Fu
r
th
er
m
o
r
e,
d
if
f
er
e
n
tial
b
ea
m
f
o
r
m
i
n
g
e
m
p
lo
y
s
eit
h
er
th
e
A
F
an
d
DF
p
r
o
to
co
ls
u
s
in
g
f
o
u
r
-
p
h
a
s
e
m
o
d
u
lat
io
n
s
ch
e
m
es
to
ac
h
ie
v
e
a
h
ig
h
B
E
R
p
er
f
o
r
m
a
n
ce
,
s
m
al
l
e
n
d
-
to
-
en
d
d
ela
y
,
an
d
l
o
w
d
ec
o
d
in
g
co
m
p
le
x
it
y
t
h
r
o
u
g
h
ad
j
u
s
t
in
g
t
h
e
p
h
ase
o
f
t
h
e
r
ec
eiv
ed
s
i
g
n
al
a
t
th
e
r
ela
y
-
n
o
d
es,
an
d
b
y
f
o
r
m
i
n
g
a
b
ea
m
s
teer
ed
to
w
a
r
d
th
e
r
ec
eiv
in
g
n
o
d
es
[
1
-
3
,
1
7
,
1
8
]
.
Ou
r
s
y
s
te
m
m
o
d
el
is
s
h
o
w
n
i
n
Fig
u
r
e
1
th
at
is
c
o
m
p
o
s
ed
o
f
+
2
h
alf
d
u
p
le
x
w
ir
eless
n
e
t
w
o
r
k
n
o
d
es,
in
c
lu
d
i
n
g
t
w
o
ter
m
i
n
a
l
n
o
d
es
τ
1
an
d
τ
2
w
h
o
ar
e
w
illi
n
g
to
ex
c
h
an
g
e
s
i
g
n
als
t
h
r
o
u
g
h
r
r
ela
y
n
o
d
es
lo
ca
ted
b
et
w
ee
n
th
e
m
.
T
h
o
s
e
r
ela
y
n
o
d
es
ar
e
eq
u
ip
p
ed
w
it
h
a
s
i
n
g
le
an
te
n
n
a
an
d
ar
e
w
o
r
k
i
n
g
in
th
e
h
alf
-
d
u
p
lex
m
o
d
e.
I
t
is
ass
u
m
ed
h
er
e
t
h
at
th
e
c
h
an
n
el
r
e
m
ai
n
s
co
n
s
tan
t
f
o
r
th
e
d
u
r
atio
n
o
f
a
f
r
a
m
e
a
n
d
it
m
a
y
v
ar
y
in
d
ep
en
d
e
n
tl
y
f
r
o
m
o
n
e
f
r
a
m
e
to
th
e
o
t
h
er
.
F
u
r
t
h
er
m
o
r
e,
th
e
c
h
an
n
el
s
ar
e
ass
u
m
ed
to
b
e
a
R
a
y
le
ig
h
f
ad
in
g
c
h
an
n
el
w
i
th
ze
r
o
m
ea
n
a
n
d
2
v
ar
ian
ce
,
i.e
.
,
f
r
~
(
(
0
,
2
)
an
d
g
r
~
(
(
0
,
2
)
.
Mo
r
eo
v
er
,
w
e
d
en
o
te
t
h
e
ch
a
n
n
e
l
f
r
o
m
τ
1
to
th
e
k
th
r
ela
y
n
o
d
e
as
f
r
(
k
)
,
a
n
d
th
e
ch
a
n
n
el
f
r
o
m
τ
2
to
th
e
k
th
r
ela
y
n
o
d
e
as
g
r
(
k
)
.
Fin
all
y
,
it
is
ass
u
m
ed
t
h
at
t
h
e
r
ela
y
-
n
o
d
es
ar
e
p
er
f
ec
tl
y
s
y
n
c
h
r
o
n
ized
a
n
d
t
h
at
C
SI
ar
e
n
o
t
r
eq
u
ir
ed
to
τ
1
an
d
τ
2
,
a
n
d
th
a
t
all
n
o
d
es
h
a
v
e
li
m
i
ted
av
er
a
g
e
tr
an
s
m
it
p
o
w
er
s
[
1
,
2
,
1
,
…
].
T
h
e
tw
o
ter
m
i
n
als
τ
1
an
d
τ
2
ar
e
tr
a
n
s
m
itt
in
g
th
e
d
if
f
er
en
tiall
y
e
n
co
d
e
d
s
ca
lar
s
1
(
)
2
(
)
r
esp
ec
tiv
el
y
,
t
h
en
a
tr
a
n
s
m
itted
s
i
g
n
al
b
y
ter
m
i
n
als
τ
1
an
d
τ
2
ca
n
b
e
ex
p
r
ess
ed
as:
(
)
=
(
−
1
)
(
)
(
1
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w
h
er
e
t
=1
,
2
,
1
(
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an
d
2
(
)
ar
e
th
e
d
ata
s
y
m
b
o
ls
o
f
th
e
ℎ
b
lo
ck
.
No
te
h
er
e
th
a
t
th
e
in
i
tial
s
y
m
b
o
l
s
in
th
e
f
ir
s
t
tr
an
s
m
i
s
s
io
n
r
o
u
n
d
,
1
(
0
)
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2
(
0
)
=
1
ca
n
b
e
u
s
ed
a
s
a
r
ef
er
e
n
c
e
at
th
e
r
ec
eiv
er
,
a
n
d
th
a
t
{
|
1
(
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{
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1
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.
No
w
,
ass
u
m
i
n
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th
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u
s
e
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M
-
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co
n
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y
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in
r
esp
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t
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t
,
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en
ce
(
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.
T
h
en
at
th
e
f
ir
s
t
p
h
ase,
t
h
e
ℎ
r
elay
r
ec
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es
th
e
f
o
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w
i
n
g
s
i
g
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a
l:
1
,
(
)
=
√
1
(
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1
(
)
+
1
,
(
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(
2
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Si
m
i
lar
l
y
,
t
h
e
r
th
r
ela
y
R
r
i
n
t
h
e
s
ec
o
n
d
p
h
ase
r
ec
eiv
e
s
th
e
b
e
lo
w
s
i
g
n
al:
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I
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&
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p
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2
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a
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m
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i
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.
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h
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)
2
,
(
)
=
2
2
,
(
)
2
,
(
)
(
5
)
w
h
er
e
1
an
d
2
ar
e
t
w
o
s
ca
li
n
g
f
a
cto
r
s
.
No
te
h
er
e
t
h
at
t
h
e
o
p
ti
m
a
l
v
a
lu
e
o
f
,
(
)
,
=
1
,
2
,
=
1
,
2
,
3
,
.
.
,
,
ca
n
b
e
f
o
u
n
d
u
s
i
n
g
c
o
h
er
en
t
s
u
p
er
p
o
s
itio
n
o
f
t
h
e
r
ec
eiv
ed
s
ig
n
al
s
at
ea
ch
r
ela
y
-
n
o
d
e,
s
u
ch
th
at
th
e
o
v
er
all
s
i
g
n
al
to
n
o
is
e
r
atio
(
SNR
)
at
b
o
th
ter
m
i
n
als i
s
m
a
x
i
m
ized
,
an
d
ca
n
b
e
g
i
v
en
a
s
:
1
,
(
)
=
−
(
∡
1
,
(
−
1
)
+
∡
2
,
(
)
)
+
(
6
)
2
,
(
)
=
−
(
∡
1
,
(
)
+
∡
2
,
(
−
1
)
)
+
(
7
)
w
h
er
e
is
an
ar
b
itra
r
y
co
n
s
tan
t
.
No
w
,
let
u
s
as
s
u
m
e
th
at
1
=
2
=
⋯
=
=
.
T
h
en
,
t
h
e
o
v
er
all
SN
R
at
ter
m
i
n
al
2
ca
n
b
e
g
iv
e
n
as
2
=
1
1
+
1
{
|
∑
(
)
(
)
1
,
(
)
=
1
|
2
}
{
|
+
2
(
)
|
2
}
(
8
)
w
h
er
e
(
+
2
(
)
)
d
en
o
tes
th
e
n
o
is
e
at
t
h
e
s
ec
o
n
d
ter
m
i
n
al.
U
s
in
g
C
au
ch
y
-
Sc
h
w
ar
z
i
n
eq
u
alit
y
t
h
e
o
r
em
,
w
e
g
et:
|
∑
(
)
(
)
1
,
=
1
|
2
≤
|
∑
(
)
(
)
=
1
|
2
(
9
)
No
te
h
er
e
th
at
(
9
)
h
o
ld
s
w
ith
e
q
u
alit
y
w
h
e
n
th
e
p
h
ase
s
h
i
f
t
1
,
−
(
∡
(
)
+
∡
(
)
)
+
,
∀
.
Fig
u
r
e
1
.
T
o
w
-
w
a
y
s
w
ir
eless
r
ela
y
n
et
w
o
r
k
(
T
W
R
N)
w
ith
m
u
ltip
le
s
i
n
g
le
-
an
te
n
n
a
r
ela
y
s
Usi
n
g
o
u
r
p
r
ev
io
u
s
as
s
u
m
p
ti
o
n
th
at
t
h
er
e
is
n
o
c
h
an
n
el
s
tate
in
f
o
r
m
atio
n
(
C
SI)
av
aila
b
le
at
an
y
n
o
d
e,
an
d
ass
u
m
i
n
g
(
)
=
(
−
1
)
,
(
)
=
(
−
1
)
an
d
u
n
d
er
th
e
id
ea
l
n
o
is
e
f
r
e
e
s
ce
n
ar
io
w
h
er
e
,
(
−
1
)
=
0
,
=
1
,
2
,
=
1
,
2
,
3
,
…
,
.
T
h
u
s
,
(
6
)
an
d
(
7
)
ca
n
n
o
w
b
e
r
e
w
r
itte
n
as:
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
9
2
3
-
5
9
3
1
5926
1
,
(
)
=
−
(
∡
(
)
+
∡
(
)
)
−
(
∡
1
(
−
1
)
+
∡
2
(
)
)
(
1
0
)
2
,
(
)
=
−
(
∡
(
)
+
∡
(
)
)
−
(
∡
1
(
)
+
∡
2
(
−
1
)
)
(
1
1
)
I
t
ca
n
b
e
n
o
ted
h
er
e
th
at
in
(
1
0
)
an
d
(
1
1
)
,
th
e
t
w
o
p
h
ase
ter
m
s
−
(
∡
1
(
−
1
)
+
∡
2
(
−
1
)
)
an
d
−
(
∡
1
(
−
1
)
+
∡
2
(
−
1
)
)
ar
e
co
n
s
tan
t
s
.
T
h
en
,
th
e
s
ig
n
a
ls
r
ec
eiv
ed
at
th
e
ter
m
i
n
a
ls
1
2
in
th
e
th
ir
d
an
d
f
o
u
r
t
h
ti
m
e
s
lo
t o
f
th
e
ℎ
tr
an
s
m
is
s
io
n
b
lo
ck
,
ar
e
g
iv
e
n
b
y
:
1
(
)
=
∑
(
)
2
,
(
)
=
1
+
1
(
)
(
1
2
)
2
(
)
=
∑
(
)
1
,
(
)
=
1
+
2
(
)
(1
3
)
w
h
er
e
1
(
)
a
n
d
2
(
)
ar
e
th
e
n
o
is
e
s
i
g
n
a
ls
a
t
th
e
t
w
o
ter
m
in
a
ls
1
2
in
r
esp
ec
t
to
th
e
ℎ
b
lo
ck
.
Giv
e
n
th
e
h
i
g
h
SNR
i
n
(
1
2
)
an
d
(
1
3
)
,
th
o
s
e
t
w
o
eq
u
atio
n
s
ca
n
b
e
r
e
w
r
itte
n
as:
1
(
)
≅
∑
√
2
+
1
=
1
|
(
)
|
|
(
)
|
(
−
1
(
)
)
2
(
)
+
1
(
1
4
)
2
(
)
≅
∑
√
2
+
1
=
1
|
(
)
|
|
(
)
|
(
−
2
(
)
)
1
(
)
+
2
(
1
5
)
w
h
er
e
1
=
∑
√
2
+
1
(
(
)
(
2
,
(
)
)
)
+
1
=
1
(
1
6
)
2
=
∑
√
1
+
1
(
(
)
(
R1
,
r
(
)
)
)
+
2
=
1
(
1
7
)
No
w
,
to
r
etr
iev
e
th
e
tr
a
n
s
m
it
te
d
s
ig
n
a
l a
t th
e
f
ir
s
t te
r
m
i
n
al
1
,
th
e
f
o
llo
w
i
n
g
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
:
a
r
g
min
(
)
‖
1
(
)
(
−
∡
1
(
)
)
−
|
1
(
−
1
)
(
−
∡
1
(
−
1
)
)
|
(
)
‖
2
(
1
8
)
Si
m
i
lar
l
y
,
t
h
e
f
o
llo
w
i
n
g
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
to
r
ec
o
v
er
th
e
tr
an
s
m
it
ted
s
ig
n
al
at
t
h
e
s
ec
o
n
d
ter
m
in
a
l
2
:
a
r
g
min
(
)
‖
2
(
)
(
−
∡
2
(
)
)
−
|
2
(
−
1
)
(
−
∡
2
(
−
1
)
)
|
(
)
‖
2
(
1
9
)
C
o
n
s
id
er
in
g
[
(
)
]
[
̃
(
)
]
an
d
u
s
i
n
g
M
-
P
SK
co
n
s
tellatio
n
s
o
f
th
e
s
et
o
f
̃
(
)
ca
n
b
e
f
o
u
n
d
co
r
r
esp
o
n
d
in
g
to
t
h
e
r
ec
eiv
i
n
g
ter
m
i
n
als
,
w
h
er
e
[
(
)
]
∈
[
̃
(
)
]
∈
.
2
.
2
.
Dif
f
er
ent
ia
l
bea
m
f
o
r
m
i
ng
us
ing
t
he
DF
pro
t
o
co
l
Fro
m
(
2
)
an
d
(
3
)
th
e
r
ela
y
-
n
o
d
es
ca
n
d
ec
o
d
e
̃
1
(
)
an
d
̃
2
(
)
.
I
n
o
r
d
e
r
to
r
ec
o
v
er
th
e
tr
an
s
m
itted
s
ig
n
al
s
at
th
e
r
ela
y
-
n
o
d
es,
th
e
f
o
llo
w
in
g
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
:
̃
1
(
)
=
min
1
(
)
‖
,
1
(
)
−
|
,
1
(
−
1
)
|
1
(
)
‖
2
(
2
0
)
̃
2
(
)
=
min
2
(
)
‖
,
2
(
)
−
|
,
2
(
−
1
)
|
2
(
)
‖
2
(
2
1
)
T
h
en
,
th
e
ℎ
r
ela
y
-
n
o
d
e
tr
an
s
m
it
s
t
h
e
f
o
llo
w
i
n
g
s
i
g
n
al
to
b
o
th
ter
m
i
n
al
s
d
u
r
i
n
g
t
h
e
t
h
ir
d
an
d
f
o
u
r
th
ti
m
e
s
lo
ts
:
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
Dis
tr
ib
u
ted
d
iffer
en
tia
l b
ea
mf
o
r
min
g
a
n
d
p
o
w
er a
llo
ca
tio
n
…
(
S
a
mer A
la
b
ed
)
5927
1
,
(
)
=
1
̃
1
(
)
−
∡
(
,
2
(
)
)
=
1
̃
1
(
)
(
,
2
(
)
)
∗
|
,
2
(
)
|
=
1
̃
1
(
)
−
∡
(
)
−
∡
2
(
)
(
2
2
)
2
,
(
)
=
1
̃
2
(
)
−
∡
(
)
−
∡
1
(
)
(
2
3
)
Me
an
w
h
ile,
in
th
e
t
h
ir
d
an
d
f
o
u
r
th
ti
m
e
s
lo
t
o
f
th
e
ℎ
tr
an
s
3
m
is
s
io
n
b
lo
ck
,
th
e
r
ec
eiv
ed
s
i
g
n
al
s
at
ter
m
i
n
als
1
2
ca
n
b
e
ex
p
r
ess
ed
as
:
1
(
)
=
∑
(
)
2
,
(
)
=
1
+
1
(
)
(
2
4
)
2
(
)
=
∑
(
)
1
,
(
)
=
1
+
2
(
)
(
2
5
)
w
h
er
e
1
(
)
2
(
)
ar
e
th
e
n
o
is
e
s
ig
n
al
s
at
th
e
t
w
o
ter
m
i
n
als
1
2
in
r
esp
ec
t
to
ℎ
b
lo
ck
.
Ass
u
m
in
g
h
ig
h
SN
R
,
th
e
n
(
2
4
)
an
d
(
2
5
)
ca
n
b
e
ex
p
r
ess
ed
as:
1
(
)
≅
∑
√
2
+
1
=
1
|
(
)
|
(
−
1
(
)
)
2
(
)
+
1
(
2
6
)
2
(
)
≅
∑
√
1
+
1
=
1
|
(
)
|
(
−
2
(
)
)
1
(
)
+
2
(
2
7
)
w
h
er
e,
1
=
∑
√
2
+
1
(
(
)
(
R2
,
r
(
)
)
)
+
1
=
1
(
2
8
)
2
=
∑
√
1
+
1
(
(
)
(
R1
,
r
(
)
)
)
+
2
=
1
(
2
9
)
Fin
all
y
,
to
r
etr
iev
e
t
h
e
tr
an
s
m
i
tted
s
ig
n
al
at
t
h
e
f
ir
s
t te
r
m
i
n
al
1
,
th
e
f
o
llo
w
i
n
g
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
:
a
r
g
min
̃
(
)
‖
1
(
)
(
−
∡
1
(
)
)
−
|
1
(
−
1
)
(
−
∡
1
(
−
1
)
)
|
̃
(
)
‖
2
(
3
0
)
Si
m
i
lar
l
y
,
t
h
e
f
o
llo
w
i
n
g
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
to
r
ec
o
v
er
th
e
tr
an
s
m
it
ted
s
ig
n
al
at
t
h
e
s
ec
o
n
d
ter
m
in
a
l
2
:
a
r
g
min
̃
(
)
‖
2
(
)
(
−
∡
2
(
)
)
−
|
2
(
−
1
)
(
−
∡
2
(
−
1
)
)
|
̃
(
)
‖
2
(
3
1
)
C
o
n
s
id
er
in
g
[
(
)
]
[
̃
(
)
]
an
d
u
s
i
n
g
M
-
P
SK
co
n
s
t
ellatio
n
s
o
f
th
e
s
et
o
f
̃
(
)
ca
n
b
e
f
o
u
n
d
co
r
r
esp
o
n
d
in
g
to
t
h
e
r
ec
eiv
i
n
g
ter
m
i
n
als
,
w
h
er
e
[
(
)
]
∈
[
̃
(
)
]
∈
.
2
.
3
.
Dif
f
er
ent
ia
l
bea
m
f
o
r
m
i
ng
us
ing
po
w
er
a
llo
ca
t
io
n st
ra
t
eg
y
Fro
m
(
2
)
,
(
3
)
,
(
4
)
,
(
2
0
)
an
d
(
2
1
)
d
is
cu
s
s
ed
ea
r
lier
,
th
e
ℎ
r
elay
b
r
o
a
d
ca
s
ts
to
th
e
r
ec
eiv
i
n
g
te
r
m
in
a
l
s
th
e
f
o
llo
w
i
n
g
t
w
o
s
i
g
n
al
s
1
,
an
d
2
,
,
g
iv
e
n
b
y
:
1
,
=
1
,
̃
1
(
)
−
∡
(
)
−
∡
2
(
)
(
3
2
)
w
h
er
e
1
,
=
|
1
,
(
)
∡
(
1
,
(
−
1
)
)
√
1
|
≅
|
(
)
|
.
Si
m
i
lar
l
y
,
2
,
ca
n
b
e
w
r
i
tten
as
f
o
llo
w
s
:
2
,
=
2
,
̃
2
(
)
−
∡
(
)
−
∡
1
(
)
(
3
3
)
w
h
er
e
2
,
=
|
2
,
(
)
∡
(
2
,
(
−
1
)
)
√
2
|
≅
|
(
)
|
.
Si
m
ilar
l
y
,
i
n
th
e
th
i
r
d
an
d
f
o
u
r
th
ti
m
e
s
lo
ts
o
f
th
e
ℎ
tr
an
s
m
is
s
io
n
b
lo
ck
,
t
h
e
s
i
g
n
al
is
r
ec
eiv
ed
at
th
e
t
w
o
ter
m
in
a
l
s
1
2
ca
n
b
e
ex
p
r
ess
ed
as:
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
9
2
3
-
5
9
3
1
5928
1
(
)
=
∑
(
)
2
,
(
)
=
1
+
1
(
)
(
3
4
)
2
(
)
=
∑
(
)
1
,
(
)
=
1
+
2
(
)
(
3
5
)
w
h
er
e
1
(
)
2
(
)
ar
e
th
e
n
o
is
e
s
ig
n
als
a
t
th
e
t
w
o
r
ec
eiv
i
n
g
ter
m
in
al
1
2
i
n
r
esp
ec
t
to
th
e
ℎ
b
lo
ck
.
A
s
s
u
m
in
g
h
ig
h
SN
R
,
(
3
4
)
an
d
(
3
5
)
ca
n
b
e
r
e
w
r
itte
n
as:
1
(
)
≅
∑
√
2
+
1
=
1
|
(
)
|
|
(
)
|
(
−
1
(
)
)
2
(
)
+
1
(
3
6
)
2
(
)
≅
∑
√
1
+
1
=
1
|
(
)
|
|
(
)
|
(
−
2
(
)
)
2
(
)
+
2
(
3
7
)
T
h
e
ex
p
r
ess
io
n
o
f
th
e
m
a
x
i
m
u
m
lik
e
lih
o
o
d
(
ML
)
d
ec
o
d
er
w
h
ile
r
ec
o
v
er
i
n
g
th
e
tr
a
n
s
m
itt
ed
s
ig
n
al
at
th
e
f
ir
s
t r
ec
eiv
i
n
g
ter
m
i
n
al
1
,
ca
n
b
e
ex
p
r
ess
ed
as:
a
r
g
min
̃
(
)
‖
1
(
)
(
−
∡
1
(
)
)
−
|
1
(
−
1
)
(
−
∡
1
(
−
1
)
)
|
̃
(
)
‖
2
(
3
8
)
Si
m
i
lar
l
y
,
th
e
d
ec
o
d
er
ca
n
b
e
p
er
f
o
r
m
ed
to
r
ec
o
v
er
th
e
tr
an
s
m
itted
s
i
g
n
a
l
at
th
e
s
ec
o
n
d
r
ec
eiv
i
n
g
ter
m
in
a
l
2
.
W
h
er
e,
1
(
)
is
d
ec
o
d
ed
as:
a
r
g
min
̃
(
)
‖
2
(
)
(
−
∡
2
(
)
)
−
|
2
(
−
1
)
(
−
∡
2
(
−
1
)
)
|
̃
(
)
‖
2
(
3
9
)
C
o
n
s
id
er
in
g
[
(
)
]
[
̃
(
)
]
an
d
u
s
in
g
M
-
P
SK
co
n
s
tellatio
n
s
o
f
th
e
s
et
o
f
̃
(
)
ca
n
b
e
f
o
u
n
d
co
r
r
esp
o
n
d
in
g
to
th
e
r
ec
eiv
in
g
ter
m
in
a
ls
,
w
h
er
e
[
(
)
]
∈
[
̃
(
)
]
∈
.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
Fig
u
r
e
2
to
Fig
u
r
e
4
s
h
o
w
t
h
e
p
er
f
o
r
m
an
ce
o
f
a
w
ir
eles
s
r
ela
y
n
et
w
o
r
k
u
s
i
n
g
=
2
;
u
n
d
er
an
in
d
ep
en
d
en
t
f
la
t
R
a
y
lei
g
h
f
ad
in
g
ch
a
n
n
els,
a
n
d
eq
u
all
y
p
o
w
er
d
is
tr
ib
u
ted
t
h
r
o
u
g
h
co
m
m
u
n
icat
in
g
ter
m
i
n
als
an
d
r
ela
y
n
o
d
es
w
h
ic
h
i
s
g
iv
en
as
1
=
2
=
∑
=
1
.
I
n
ad
d
itio
n
,
th
e
to
tal
p
o
w
er
ca
n
b
e
ex
p
r
es
s
ed
as
=
1
+
2
+
∑
=
1
,
1
=
2
=
⋯
=
.
Fig
u
r
e
2
a
n
d
Fig
u
r
e
3
s
h
o
w
a
3
d
B
p
e
r
f
o
r
m
a
n
c
e
d
i
f
f
e
r
e
n
c
e
b
e
tw
e
en
c
o
h
e
r
en
t
an
d
d
if
f
e
r
e
n
ti
a
l
t
ec
h
n
i
q
u
es
u
s
i
n
g
b
in
ar
y
PS
K
(
B
PS
K
)
an
d
q
u
a
d
r
at
u
r
e
PS
K
(
Q
PS
K
)
m
o
d
u
l
a
ti
o
n
,
A
F
p
r
o
t
o
c
o
l
,
an
d
tw
o
r
e
lay
s
.
T
h
i
s
is
b
e
c
au
s
e
d
if
f
e
r
en
ti
a
l
t
e
ch
n
i
q
u
es
d
o
n
o
t
r
e
q
u
i
r
e
th
e
k
n
o
w
le
d
g
e
o
f
C
S
I
a
t
a
n
y
n
o
d
e
an
d
c
an
b
e
a
p
p
l
i
e
d
in
f
a
s
t
f
a
d
in
g
ch
a
n
n
el
s
.
Fig
u
r
e
2
.
C
o
m
p
ar
is
o
n
o
f
co
h
e
r
en
t a
n
d
d
if
f
er
en
t
ial
tech
n
iq
u
e
s
u
s
in
g
B
P
SK
m
o
d
u
latio
n
an
d
2
r
elay
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
Dis
tr
ib
u
ted
d
iffer
en
tia
l b
ea
mf
o
r
min
g
a
n
d
p
o
w
er a
llo
ca
tio
n
…
(
S
a
mer A
la
b
ed
)
5929
Fig
u
r
e
3
.
C
o
m
p
ar
is
o
n
o
f
co
h
e
r
en
t a
n
d
d
if
f
er
en
t
ial
tech
n
iq
u
e
s
u
s
in
g
QP
SK
m
o
d
u
latio
n
a
n
d
2
r
elay
s
Fig
u
r
e
4
s
h
o
w
s
th
e
B
E
R
p
e
r
f
o
r
m
an
ce
v
er
s
u
s
SN
R
u
s
in
g
d
is
tr
ib
u
ted
b
ea
m
f
o
r
m
i
n
g
tec
h
n
iq
u
e
in
th
e
p
r
ese
n
ce
o
f
t
w
o
a
n
d
f
o
u
r
r
ela
y
-
n
o
d
es,
a
n
d
ea
ch
o
f
t
h
e
r
ela
y
-
n
o
d
es
h
as
a
s
in
g
le
a
n
te
n
n
a.
T
h
e
f
ig
u
r
e
u
s
es
16
-
P
SK
m
o
d
u
la
tio
n
a
n
d
co
m
p
ar
es
a
f
o
u
r
-
p
h
ase
d
if
f
er
e
n
tial
b
ea
m
f
o
r
m
in
g
s
c
h
e
m
e
u
n
d
er
p
o
w
er
allo
ca
tio
n
a
n
d
w
h
e
n
u
s
i
n
g
eq
u
a
l
p
o
w
er
d
is
tr
ib
u
tio
n
.
Fro
m
th
i
s
f
i
g
u
r
e,
w
e
ca
n
o
b
s
er
v
e
th
at
t
h
e
tec
h
n
iq
u
e
w
i
th
p
o
w
er
allo
ca
tio
n
s
h
o
w
s
i
m
p
r
o
v
ed
p
e
r
f
o
r
m
an
ce
co
m
p
ar
ed
to
th
e
tec
h
n
iq
u
e
w
it
h
eq
u
al
p
o
w
er
d
is
tr
i
b
u
tio
n
.
Fig
u
r
e
4
.
P
o
w
er
allo
ca
tio
n
i
n
d
is
tr
ib
u
ted
r
ela
y
n
e
t
w
o
r
k
(
R
=
2
an
d
4
)
u
s
in
g
1
6
-
P
SK
4.
CO
NCLU
SI
O
N
T
h
e
id
ea
o
f
p
r
o
p
o
s
in
g
a
co
o
p
er
ativ
e
d
iv
er
s
it
y
tech
n
iq
u
e
f
o
r
w
ir
eless
r
ela
y
n
et
w
o
r
k
s
is
to
im
p
r
o
v
e
th
e
o
v
er
all
s
y
s
te
m
p
er
f
o
r
m
a
n
c
e
in
ter
m
s
o
f
eit
h
er
B
E
R
o
r
ac
h
iev
ab
le
d
ata
r
ate
w
it
h
lo
w
d
e
co
d
in
g
co
m
p
lex
it
y
an
d
d
elay
,
a
n
d
to
tr
an
s
m
i
t
an
d
d
ec
o
d
e
th
e
in
f
o
r
m
atio
n
s
y
m
b
o
ls
w
i
th
o
u
t
n
ee
d
i
n
g
C
SI
at
eith
er
s
id
e
o
f
th
e
co
m
m
u
n
icati
n
g
p
ar
ties
t
o
o
v
er
co
m
e
th
e
o
v
er
h
ea
d
a
s
s
o
ciate
d
w
it
h
es
ti
m
atin
g
c
h
an
n
el
in
f
o
r
m
a
tio
n
.
T
h
er
ef
o
r
e,
i
n
t
h
is
w
o
r
k
,
w
e
h
av
e
s
u
g
g
e
s
ted
a
d
is
tr
ib
u
ted
d
if
f
er
e
n
tial
b
ea
m
f
o
r
m
i
n
g
tec
h
n
iq
u
e
w
i
th
p
o
w
er
allo
ca
tio
n
to
b
e
u
s
ed
f
o
r
t
w
o
-
w
a
y
w
ir
ele
s
s
r
ela
y
n
et
w
o
r
k
s
.
T
h
e
p
r
o
p
o
s
ed
tech
n
iq
u
e
i
m
p
r
o
ve
s
th
e
o
v
er
all
s
y
s
te
m
p
er
f
o
r
m
a
n
ce
i
n
ter
m
s
o
f
B
E
R
w
it
h
lo
w
d
ec
o
d
in
g
co
m
p
lex
i
t
y
a
n
d
d
ela
y
w
it
h
o
u
t
r
eq
u
ir
in
g
C
SI
at
a
n
y
tr
an
s
m
itti
n
g
o
r
r
ec
eiv
in
g
an
te
n
n
a
.
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
9
2
3
-
5
9
3
1
5930
RE
F
E
R
E
NC
E
S
[1
]
S
.
A
lab
e
d
a
n
d
M
.
P
e
sa
v
e
n
to
,
“
A
si
m
p
le
d
istri
b
u
te
d
d
if
f
e
r
e
n
ti
a
l
tran
sm
it
b
e
a
m
f
o
r
m
in
g
tec
h
n
iq
u
e
f
o
r
t
w
o
-
w
a
y
w
irele
ss
re
la
y
n
e
t
w
o
rk
s,”
i
n
T
h
e
1
6
t
h
I
n
ter
n
a
ti
o
n
a
l
IT
G
W
o
rk
s
h
o
p
o
n
S
ma
rt
An
te
n
n
a
s
(
W
S
A
2
0
1
2
)
,
Dre
sd
e
n
,
G
e
r
m
a
n
y
,
p
p
.
2
4
3
-
2
4
7
,
M
a
r
.
2
0
1
2
.
[2
]
A
.
S
c
h
a
d
,
e
t
a
l.
,
“
Bi
-
d
irec
ti
o
n
a
l
d
if
fe
re
n
ti
a
l
b
e
a
m
f
o
r
m
in
g
f
o
r
m
u
lt
i
-
a
n
te
n
n
a
re
lay
in
g
,
”
4
0
th
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Aco
u
stics
,
S
p
e
e
c
h
a
n
d
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
(
ICAS
S
P)
,
p
p
.
2
8
8
4
-
2
8
8
8
,
2
0
1
5
.
[3
]
S
.
A
lab
e
d
,
“
P
e
rf
o
rm
a
n
c
e
a
n
a
l
y
sis
o
f
d
if
f
e
re
n
ti
a
l
b
e
a
m
f
o
rm
in
g
in
d
e
c
e
n
tralize
d
n
e
tw
o
rk
s
,
”
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
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l,
8
,
n
o
.
3
,
p
p
.
1
6
9
2
-
1
7
0
0
,
2
0
1
8
.
[4
]
S
.
A
lab
e
d
,
e
t
a
l.
,
“
No
n
-
c
o
h
e
re
n
t
d
istri
b
u
ted
sp
a
c
e
-
ti
m
e
c
o
d
in
g
tec
h
n
i
q
u
e
s
f
o
r
tw
o
-
w
a
y
w
irele
ss
re
l
a
y
n
e
t
w
o
rk
s,”
S
ig
n
a
l
Pro
c
e
ss
in
g
,
v
o
l.
9
3
,
n
o
.
1
2
,
p
p
.
3
3
7
1
-
3
3
8
1
,
2
0
1
3
.
[5
]
S
.
A
lab
e
d
,
e
t
a
l.
,
“
A
lo
w
c
o
m
p
le
x
it
y
d
e
c
o
d
e
r
f
o
r
q
u
a
si
-
o
rt
h
o
g
o
n
a
l
sp
a
c
e
-
ti
m
e
b
lo
c
k
c
o
d
e
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
W
ire
les
s Co
mm
u
n
ica
ti
o
n
,
v
o
l
.
1
0
,
n
o
.
3
,
p
p
.
9
8
8
-
9
9
4
,
2
0
1
1
.
[6
]
S
.
A
lab
e
d
,
e
t
a
l.
,
“
Distrib
u
ted
d
iff
e
re
n
ti
a
l
sp
a
c
e
–
ti
m
e
c
o
d
in
g
tec
h
n
i
q
u
e
s
f
o
r
tw
o
-
w
a
y
w
ir
e
les
s
r
e
la
y
n
e
t
w
o
rk
s,
”
in
Pro
c
e
e
d
in
g
s
o
f
t
h
e
Fo
u
rt
h
IE
EE
In
ter
n
a
ti
o
n
a
l
W
o
rk
sh
o
p
o
n
C
o
mp
u
t
a
ti
o
n
a
l
Ad
v
a
n
c
e
s
in
M
u
lt
i
-
S
e
n
so
r
Ad
a
p
t
ive
Pro
c
e
ss
in
g
(
CAM
S
AP
1
1
)
,
S
a
n
Ju
a
n
,
P
u
e
rt
o
Rico
,
p
p
.
2
2
1
-
2
2
4
,
De
c
.
2
0
1
1
.
[7
]
S
.
A
lab
e
d
,
e
t
a
l.
,
“
A
si
m
p
le
d
istri
b
u
ted
sp
a
c
e
-
ti
m
e
c
o
d
e
d
stra
teg
y
fo
r
tw
o
-
w
a
y
re
l
a
y
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
ic
a
ti
o
n
s
,
v
o
l
.
1
1
,
n
o
.
4
,
p
p
.
1
2
6
0
-
1
2
6
5
,
A
p
r
.
2
0
1
2
.
[8
]
S
.
A
lab
e
d
,
e
t
a
l.
,
“
Distrib
u
ted
Diff
e
r
e
n
ti
a
l
S
p
a
c
e
-
T
i
m
e
Co
d
in
g
f
o
r
Tw
o
-
Wa
y
R
e
la
y
Ne
t
w
o
rk
s
u
sin
g
A
n
a
lo
g
Ne
tw
o
rk
Co
d
in
g
,
”
T
h
e
2
1
st
E
u
ro
p
e
a
n
S
i
g
n
a
l
Pr
o
c
e
e
d
in
g
s
C
o
n
fer
e
n
c
e
(
EUS
IPCO'
1
3
)
,
M
a
rra
k
e
c
h
,
M
o
ro
c
c
o
,
p
p
.
1
-
5
,
2
0
1
3
.
[9
]
S
.
A
lab
e
d
,
“
P
e
rf
o
rm
a
n
c
e
A
n
a
l
y
sis
o
f
t
w
o
-
w
a
y
DF
Re
la
y
S
e
lec
ti
o
n
T
e
c
h
n
iq
u
e
s
,”
ICT
Exp
re
ss
,
v
o
l.
2
,
n
o
.
3
,
p
p
.
9
1
-
9
5
,
2
0
1
6
.
[1
0
]
A
d
e
e
b
S
a
lh
,
e
t
a
l.
,
“
A
d
a
p
ti
v
e
a
n
ten
n
a
se
lec
ti
o
n
a
n
d
p
o
w
e
r
a
ll
o
c
a
ti
o
n
in
d
o
w
n
li
n
k
m
a
ss
i
v
e
M
I
M
O
s
y
ste
m
s
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
7
,
n
o
.
6
,
pp
.
3
5
2
1
-
3
5
2
8
,
De
c
.
2
0
1
7
.
[1
1
]
S.
A
lab
e
d
,
“
P
e
rf
o
rm
a
n
c
e
A
n
a
l
y
sis
o
f
Bi
-
Dire
c
ti
o
n
a
l
Re
lay
S
e
lec
ti
o
n
S
trate
g
y
f
o
r
W
irele
s
s
Co
o
p
e
ra
ti
v
e
Co
m
m
u
n
ica
ti
o
n
s
,
”
EURA
S
IP
J
o
u
rn
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
9
,
n
o
.
1
,
p
p
.
1
-
1
1
,
2
0
1
9
.
[1
2
]
Ya
s
m
in
e
Tab
ra
,
e
t
a
l.
,
“
Hy
b
rid
M
V
DR
-
L
M
S
b
e
a
m
f
o
rm
in
g
f
o
r
m
a
ss
iv
e
M
IM
O
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
(
I
J
EE
CS
)
,
v
o
l.
1
6
,
n
o
.
2
,
pp
.
7
1
5
-
7
2
3
,
No
v
.
2
0
1
9
.
[1
3
]
W
.
Du
a
n
,
e
t
a
l.
,
“
Ef
f
e
c
ti
v
e
Re
so
u
rc
e
Util
iza
ti
o
n
S
c
h
e
m
e
s
f
o
r
De
c
o
d
e
-
a
n
d
-
F
o
rw
a
rd
Re
la
y
Ne
t
w
o
rk
s
W
it
h
NO
M
A
,
”
in
IEE
E
Acc
e
ss
,
v
o
l.
7
,
p
p
.
5
1
4
6
6
-
5
1
4
7
4
,
2
0
1
9
.
[1
4
]
J.
Ju
,
e
t
a
l.
,
“
P
e
rf
o
rm
a
n
c
e
A
n
a
l
y
s
is
f
o
r
Co
o
p
e
ra
ti
v
e
NO
M
A
W
it
h
Op
p
o
r
tu
n
isti
c
Re
la
y
S
e
lec
ti
o
n
,
”
in
IEE
E
Acc
e
ss
,
v
o
l.
7
,
p
p
.
1
3
1
4
8
8
-
1
3
1
5
0
0
,
2
0
1
9
.
[1
5
]
G
.
C
a
i,
e
t
a
l.
,
“
De
sig
n
a
n
d
a
n
a
ly
s
is
o
f
r
e
la
y
-
s
e
lec
ti
o
n
stra
teg
ies
f
o
r
tw
o
-
w
a
y
re
l
a
y
n
e
t
w
o
rk
-
c
o
d
e
d
DCSK
s
y
ste
m
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Veh
icu
l
a
r
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
6
7
,
n
o
.
2
,
p
p
.
1
-
1
3
,
2
0
1
7
.
[1
6
]
T
.
N.
Ng
u
y
e
n
,
e
t
a
l.
,
“
P
e
rf
o
r
m
a
n
c
e
En
h
a
n
c
e
m
e
n
t
f
o
r
En
e
rg
y
H
a
rv
e
stin
g
Ba
se
d
Tw
o
-
W
a
y
Re
la
y
P
ro
t
o
c
o
ls
in
W
irele
ss
A
d
-
Ho
c
Ne
tw
o
rk
s
W
it
h
P
a
rti
a
l
a
n
d
F
u
ll
Re
lay
S
e
l
e
c
ti
o
n
M
e
t
h
o
d
s
,
”
Ad
H
o
c
Ne
two
rk
s
,
v
o
l.
8
4
,
p
p
.
1
7
8
-
1
8
7
,
2
0
1
9
.
[1
7
]
X
.
W
e
n
,
e
t
a
l.
,
“
Ra
n
k
-
tw
o
b
e
a
m
f
o
r
m
in
g
f
o
r
sin
g
le
-
g
ro
u
p
m
u
lt
ica
stin
g
n
e
tw
o
rk
s
u
sin
g
OST
BC
,
”
T
h
e
7
t
h
IEE
E
S
e
n
so
r A
rr
a
y
a
n
d
M
u
lt
ich
a
n
n
e
l
S
ig
n
a
l
Pr
o
c
e
ss
in
g
W
o
rk
sh
o
p
(
S
AM
)
,
p
p
.
6
5
-
6
8
,
Ju
n
.
2
0
1
2
.
[1
8
]
D.
T
a
leb
,
e
t
a
l.
,
“
Op
ti
m
a
l
g
e
n
e
ra
l
-
ra
n
k
tran
s
m
it
b
e
a
m
f
o
rm
in
g
tec
h
n
iq
u
e
f
o
r
m
u
lt
ica
stin
g
se
r
v
ice
in
m
o
d
e
rn
w
irele
ss
n
e
t
w
o
rk
s
u
sin
g
S
TT
C,
”
Pro
c
e
e
d
in
g
s
o
f
th
e
1
9
t
h
In
ter
n
a
ti
o
n
a
l
IEE
E/
I
T
G
W
o
rk
sh
o
p
o
n
S
ma
rt
An
ten
n
a
s
(
W
S
A
2
0
1
5
)
,
Ilm
e
n
a
u
,
G
e
r
m
a
n
y
,
p
p
.
1
-
7
,
M
a
r
.
2
0
1
5.
[1
9
]
S
.
A
lab
e
d
,
“
A
c
o
m
p
u
tatio
n
a
ll
y
e
ff
ici
e
n
t
d
e
tec
to
r
f
o
r
M
IM
O
sy
s
tem
s
,
”
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
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
5
,
p
p
.
4
1
3
8
-
4
1
4
6
,
Oc
t
.
2
0
1
9
.
[2
0
]
A
.
M
.
El
sh
irk
a
si
,
e
t
a
l.
,
“
P
e
rf
o
r
m
a
n
c
e
e
v
a
lu
a
ti
o
n
o
f
2
-
p
o
rt
M
I
M
O
LT
E
-
U
ter
m
in
a
l
a
n
ten
n
a
with
u
se
r’s
h
a
n
d
e
ffe
c
t
,
”
Bu
ll
e
ti
n
o
f
E
lec
trica
l
En
g
in
e
e
rin
g
a
n
d
I
n
fo
rm
a
ti
c
s
,
v
o
l.
8
,
n
o
.
1
,
p
p
.
1
5
8
-
1
6
5
,
M
a
r
.
20
19
.
[2
1
]
D
.
H.
A
i,
“
Av
e
ra
g
e
Ch
a
n
n
e
l
Ca
p
a
c
it
y
o
f
Am
p
li
fy
-
a
n
d
-
f
o
rwa
rd
M
IM
O/F
S
O S
y
ste
m
s
Ov
e
r
A
t
m
o
sp
h
e
ric T
u
rb
u
len
c
e
Ch
a
n
n
e
ls
,
”
I
n
ter
n
a
t
io
n
a
l
J
o
u
r
n
a
l
o
f
E
lec
trica
l
a
n
d
Co
mp
u
ter
E
n
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
8
,
n
o
.
6
,
p
p
.
4
3
3
4
-
4
3
4
2
,
De
c
.
2
0
1
8
.
[2
2
]
M
.
I.
Yo
u
ss
if
,
e
t
a
l.
,
“
Im
a
g
e
m
u
lt
ip
lex
in
g
u
sin
g
re
sid
u
e
n
u
m
b
e
r
sy
ste
m
c
o
d
in
g
o
v
e
r
M
IM
O
-
OFDM
c
o
m
m
u
n
ica
ti
o
n
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
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
6
,
p
p
.
4
8
1
5
-
4
8
2
5
,
De
c
.
2
0
1
9
.
[2
3
]
S
.
P
y
la,
e
t
a
l.
,
“
P
e
rf
o
r
m
a
n
c
e
An
a
ly
sis
o
f
A
d
a
p
ti
v
e
F
il
ter
Ch
a
n
n
e
l
Esti
m
a
ted
M
IM
O
OFDM
C
o
m
m
u
n
ica
ti
o
n
S
y
st
e
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
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[2
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M
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B
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RAP
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RS
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a
m
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e
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n
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f
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g
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d
tec
h
n
o
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y
,
Am
e
ric
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n
Un
iv
e
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y
o
f
th
e
M
i
d
d
le
Eas
t,
Ku
w
a
it
a
n
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IEE
E
se
n
io
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m
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m
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e
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w
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e
d
a
lso
in
th
e
c
o
m
m
u
n
ica
ti
o
n
sy
ste
m
s
g
ro
u
p
a
t
Da
r
m
sta
d
t
Un
iv
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o
f
Tec
h
n
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lo
g
y
,
Da
r
m
sta
d
t,
Ge
r
m
a
n
y
f
ro
m
2
0
0
8
to
2
0
1
5
.
He
re
c
e
iv
e
d
h
is
P
h
D
d
e
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re
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in
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tri
c
a
l
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in
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g
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n
d
in
f
o
rm
a
ti
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tec
h
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l
o
g
y
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f
ro
m
Da
r
m
sta
d
t
Un
iv
e
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o
f
T
e
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h
n
o
l
o
g
y
,
Da
r
m
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G
e
r
m
a
n
y
.
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rin
g
th
e
las
t
1
7
y
e
a
rs,
h
e
h
a
s
w
o
rk
e
d
a
s
a
n
a
s
so
c
iate
p
ro
f
e
ss
o
r,
a
ss
istan
t
p
ro
f
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o
r,
(p
o
st
-
d
o
c
to
ra
l)
re
se
a
rc
h
e
r,
a
n
d
lec
tu
r
e
r
in
se
v
e
ra
l
u
n
iv
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e
s
in
G
e
rm
a
n
y
a
n
d
M
id
d
le
Eas
t
a
n
d
su
p
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rv
ise
d
ten
s
o
f
m
a
st
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n
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a
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d
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v
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ra
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P
h
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stu
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d
s
e
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r
a
l
a
w
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rd
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f
ro
m
IEE
,
IEE
E,
DA
AD
.
.
.
e
tc.,
su
c
h
a
s
th
e
b
e
st
p
a
p
e
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a
w
a
rd
f
ro
m
th
e
In
tern
a
ti
o
n
a
l
IEE
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S
A
a
n
d
w
a
s in
v
it
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d
to
m
a
n
y
c
o
n
f
e
re
n
c
e
s
a
n
d
w
o
rk
sh
o
p
s in
E
u
ro
p
e
,
US,
a
n
d
No
rth
A
f
rica
.
T
h
e
m
a
in
id
e
a
o
f
h
is
re
se
a
rc
h
is
to
d
e
v
e
lo
p
a
d
v
a
n
c
e
d
DSP
a
lg
o
rit
h
m
s
in
th
e
a
r
e
a
o
f
w
ir
e
les
s
c
o
m
m
u
n
ica
ti
o
n
s
in
c
lu
d
in
g
(M
a
ss
iv
e
)
M
IM
O
sy
ste
m
s,
d
istri
b
u
ted
sy
ste
m
s,
c
o
-
o
p
e
ra
ti
v
e
c
o
m
m
u
n
ica
ti
o
n
s,
re
la
y
n
e
tw
o
rk
s,
sp
a
c
e
-
ti
m
e
b
lo
c
k
a
n
d
trelli
s
c
o
d
in
g
,
d
if
fe
re
n
ti
a
l
a
n
d
b
li
n
d
tec
h
n
i
q
u
e
s,
c
h
a
n
n
e
l
c
o
d
i
n
g
,
tw
o
-
w
a
y
re
la
y
in
g
,
b
a
se
b
a
n
d
c
o
m
m
u
n
ica
ti
o
n
s,
m
u
lt
i
-
c
a
rrier
tran
s
m
issio
n
,
m
o
d
e
li
n
g
o
f
c
h
a
n
n
e
l
c
h
a
ra
c
teristics
,
a
d
a
p
ti
v
e
b
e
a
m
f
o
rm
in
g
,
se
n
so
r
a
rra
y
p
ro
c
e
ss
in
g
,
t
ra
n
sc
e
iv
e
r
d
e
sig
n
,
m
u
lt
i
-
u
se
r
a
n
d
m
u
lt
i
-
c
a
rrier
sy
ste
m
s,
c
o
n
v
e
x
o
p
ti
m
iza
ti
o
n
,
c
h
a
n
n
e
l
e
q
u
a
li
z
a
ti
o
n
,
a
n
d
o
t
h
e
r
k
in
d
s
o
f
d
isto
rti
o
n
a
n
d
i
n
terf
e
re
n
c
e
m
it
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g
a
ti
o
n
.
F
u
r
th
e
r
in
f
o
rm
a
ti
o
n
a
re
a
v
a
il
a
b
le
o
n
h
is
h
o
m
e
p
a
g
e
:
h
tt
p
:
//
d
rsa
m
e
ra
lab
e
d
.
w
i
x
site.c
o
m
/
sa
m
e
r
Is
sa
m
M
a
a
z
jo
in
e
d
Am
e
ric
a
n
Un
iv
e
rsit
y
o
f
th
e
M
id
d
le
Eas
t
a
s
a
n
a
ss
istan
t
p
ro
f
e
ss
o
r
o
f
e
lec
tri
c
a
l
a
n
d
c
o
m
p
u
ter
e
n
g
in
e
e
rin
g
in
2
0
1
7
.
He
re
c
e
iv
e
d
h
is
P
h
D
d
e
g
re
e
in
e
lec
tro
n
ics
a
n
d
c
o
m
m
u
n
ica
ti
o
n
e
n
g
in
e
e
rin
g
w
it
h
g
re
a
t
h
o
n
o
r
f
ro
m
Tele
c
o
m
P
a
risT
e
c
h
,
P
a
ris,
F
ra
n
c
e
,
i
n
2
0
1
5
.
Du
rin
g
th
e
las
t
f
e
w
y
e
a
rs,
h
e
h
a
s
w
o
rk
e
d
a
s
a
n
a
ss
istan
t
p
ro
f
e
s
so
r,
a
n
d
re
se
a
rc
h
e
n
g
in
e
e
r
in
se
v
e
r
a
l
c
o
m
p
a
n
ies
su
c
h
a
s
Ora
n
g
e
F
ra
n
c
e
a
n
d
w
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rk
e
d
o
n
se
v
e
r
a
l
Eu
ro
p
e
a
n
p
ro
jec
ts
su
c
h
a
s
S
HA
RIN
G
Ce
lt
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lu
s.
T
h
e
m
a
in
id
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o
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h
is
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se
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is
t
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n
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s
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s,
s
m
a
ll
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ll
s,
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IM
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sy
st
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m
s,
Ra
d
io
En
v
iro
n
m
e
n
tal
M
a
p
s
(REM
),
e
tc,
th
a
t
c
a
n
b
e
u
se
d
f
o
r
th
e
n
e
w
g
e
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ra
ti
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s
o
f
c
o
m
m
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ti
o
n
s
y
ste
m
s su
c
h
a
s 5
G
a
n
d
b
e
y
o
n
d
.
M
o
h
a
m
m
a
d
Al
-
R
a
b
a
y
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h
h
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ld
s
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tri
c
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ro
m
th
e
Un
iv
e
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y
o
f
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w
S
o
u
t
h
W
a
les
(UN
S
W
)
sin
c
e
th
e
y
e
a
r
2
0
1
1
.
A
m
a
st
e
r’s
d
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g
re
e
in
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o
m
m
u
n
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m
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f
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rd
a
n
Un
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y
o
f
S
c
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c
e
a
n
d
T
e
c
h
n
o
lo
g
y
(J
UST
)
in
2
0
0
3
.
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is
c
u
rr
e
n
tl
y
a
n
a
ss
istan
t
p
ro
f
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ss
o
r
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e
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tri
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g
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ric
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f
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id
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le
Eas
t
(A
UM)
–
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w
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it
,
sin
c
e
9
/2
0
1
8
.
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is
tea
c
h
in
g
v
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rio
u
s
c
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rse
s
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o
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th
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n
d
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r
g
ra
d
u
a
te
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d
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n
ts,
su
p
e
rv
isin
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th
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ir
g
ra
d
u
a
ti
o
n
p
r
o
jec
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a
n
a
c
a
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m
ic
a
d
v
iso
r
f
o
r
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le
c
tri
c
a
l
e
n
g
in
e
e
rin
g
stu
d
e
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ts,
a
n
d
a
m
e
m
b
e
r
o
f
m
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n
y
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m
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th
e
d
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rt
m
e
n
t
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re
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m
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tain
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o
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c
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ti
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n
a
n
d
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t.
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l
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y
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h
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lso
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d
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s
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n
a
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r
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t
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ri
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c
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S
u
lt
a
n
U
n
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rsity
(P
S
U),
Riy
a
d
h
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,
f
o
r
th
e
p
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d
b
e
tw
e
e
n
8
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a
n
d
8
/
2
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1
8
.
De
rin
g
h
is
ti
m
e
a
t
P
S
U h
e
tau
g
h
t
m
a
n
y
c
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m
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n
s a
n
d
n
e
tw
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rk
s d
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p
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rt
m
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n
t,
su
p
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rv
ise
d
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n
d
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rg
ra
d
u
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te
st
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d
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n
ts
d
u
rin
g
t
h
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ir
six
m
o
n
th
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train
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n
g
i
n
tern
s
h
ip
s
in
sid
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a
n
d
o
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tsi
d
e
KSA
,
a
n
d
p
a
rti
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ip
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ted
i
n
m
a
n
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train
in
g
wo
rk
sh
o
p
s
to
d
e
v
e
lo
p
h
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p
ro
f
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ss
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n
a
l
c
a
re
e
r,
a
n
d
to
su
p
p
o
rt
th
e
u
n
iv
e
rsity
e
ff
o
rts
to
w
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rd
g
a
in
in
g
th
e
i
n
tern
a
ti
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n
a
l
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n
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in
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rin
g
a
c
c
re
d
it
a
ti
o
n
A
BET
.
He
w
o
rk
e
d
a
s
a
n
a
ss
istan
t
p
ro
f
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s
so
r
a
t
P
rin
c
e
S
a
tt
a
m
b
in
Ab
d
u
laz
iz
Un
iv
e
rsit
y
(P
S
A
U),
Kh
a
rj
-
KSA
,
in
th
e
p
e
rio
d
b
e
tw
e
e
n
1
0
/
2
0
1
4
a
n
d
6
/2
0
1
5
.
His
c
u
rr
e
n
t
re
se
a
rc
h
is
in
th
e
f
ield
s
o
f
w
irele
ss
n
e
tw
o
rk
s,
a
n
d
c
o
o
p
e
ra
ti
v
e
w
irele
ss
c
o
m
m
u
n
ica
ti
o
n
s.
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