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.
1
,
F
e
br
ua
r
y
2020
,
pp.
80
~
89
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
.
v18i1.
13199
80
Jou
r
n
al
h
omepage
:
ht
tp:
//
jour
nal.
uad
.
ac
.
id/
index
.
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E
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alh
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k
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ay
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R
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M
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R
e
vis
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d
Nov
2
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20
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pted
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T
h
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a
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at
1
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s
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ed
w
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p
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mp
u
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er
Si
mu
l
a
t
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o
n
T
ec
h
n
o
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o
g
y
(CST
)
s
o
f
t
w
are.
C
o
mp
ar
i
s
o
n
an
a
l
y
s
es
b
et
w
een
t
h
e
s
i
m
u
l
a
t
ed
i
n
s
ert
i
o
n
l
o
s
s
an
d
refl
ect
i
o
n
co
eff
i
ci
e
n
t
o
f
RO
3
0
0
3
a
n
d
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4
s
u
b
s
t
r
at
e
s
h
av
e
b
een
carri
e
d
o
u
t
i
n
o
rd
er
t
o
s
h
o
w
t
h
e
effi
ci
e
n
cy
o
f
t
h
e
p
ro
p
o
s
ed
fi
l
t
er
d
es
i
g
n
.
Bas
ed
o
n
t
h
e
o
b
t
a
i
n
e
d
re
s
u
l
t
s
,
t
h
e
p
ro
p
o
s
e
d
fi
l
t
er
d
es
i
g
n
ach
i
ev
e
s
s
i
g
n
i
fi
can
t
fi
l
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er
s
i
ze
re
d
u
c
t
i
o
n
co
mp
are
d
t
o
o
t
h
er
b
an
d
-
p
a
s
s
fi
l
t
er
s
.
K
e
y
w
o
r
d
s
:
B
a
nd
-
pa
s
s
F
il
ter
M
ult
i
-
laye
r
ha
ir
pin
R
e
duc
e
d
s
ize
S
ize
r
e
duc
ti
on
Th
i
s
i
s
a
n
o
p
en
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
:
Qa
z
wa
n
Abdullah
,
F
a
c
ult
y
of
E
nginee
r
ing
T
e
c
hnology,
Unive
r
s
it
i
T
un
Hus
s
e
in
Onn
M
a
lays
ia,
86400
P
a
r
it
R
a
ja,
J
ohor
,
M
a
lays
ia
.
E
mail:
ga
z
wa
n20062015@gmail.
c
om
1.
I
NT
RODU
C
T
I
ON
I
n
r
e
c
e
nt
de
c
a
de
s
,
the
r
e
qui
r
e
ment
f
o
r
c
ompac
t
e
d
s
ize
a
nd
high
-
e
f
f
icie
nc
y
mi
c
r
owa
ve
f
il
ter
s
is
incr
e
a
s
ing
r
a
pidl
y
in
dif
f
e
r
e
nt
c
omm
unica
ti
on
a
ppli
c
a
ti
ons
[1
-
6]
.
R
e
li
a
ble
theo
r
e
ti
c
a
l
de
s
igni
ng
a
nd
s
tr
uc
tur
e
of
mi
c
r
owa
ve
f
il
ter
s
a
r
e
s
a
ti
s
f
ying
r
e
c
e
nt
a
nd
e
xc
it
ing
dif
f
iculti
e
s
to
r
e
a
li
z
e
e
xtr
a
or
dinar
y
r
e
quir
e
m
e
nts
a
nd
a
ppli
c
a
ti
ons
[
7,
8]
.
F
il
ter
ing
tec
hnology
e
ntails
high
-
pe
r
f
or
manc
e
,
c
ompac
t
s
iz
e
,
li
ghtwe
ight
a
nd
les
s
c
os
t
[
9
,
10]
.
I
n
o
r
de
r
to
s
a
ti
s
f
y
thes
e
r
e
quir
e
ments
,
numer
ous
types
of
plana
r
mi
c
r
os
tr
ip
f
il
ter
s
,
li
ke
r
e
s
ona
tor
f
il
ter
s
,
ope
n
-
loop
r
e
s
ona
tor
f
i
lt
e
r
s
,
a
nd
s
teppe
d
i
mpeda
nc
e
r
e
s
ona
tor
f
il
ter
s
we
r
e
int
r
oduc
e
d
[
11
,
12]
.
B
ut
,
plana
r
mi
c
r
os
tr
ip
f
il
ter
s
a
r
e
a
ppli
e
d
on
a
s
ing
le
mi
c
r
os
tr
ip
s
ubs
tr
a
te
laye
r
that
us
ua
ll
y
c
om
pr
is
e
s
a
big
s
ize
[
13]
.
M
ult
il
a
ye
r
ba
nd
-
pa
s
s
s
tr
u
c
tur
e
s
olves
thi
s
pr
obl
e
m
[
14
,
15]
.
F
o
r
the
las
t
de
c
a
de
,
the
s
ubjec
t
c
onc
e
r
ne
d
s
igni
f
ica
nt
int
e
r
e
s
t
a
nd
mul
ti
laye
r
s
tr
uc
tur
e
methods
ha
ve
be
e
n
int
r
oduc
e
d
in
o
r
de
r
t
o
r
e
duc
e
the
s
ize
a
nd
incr
e
a
s
e
the
ba
ndwidths
of
the
mi
c
r
os
t
r
ip
f
i
lt
e
r
s
[
16
-
24]
.
T
his
s
tudy
pr
opos
e
s
a
de
s
ign
of
t
wo
-
por
t
ne
two
r
k
ba
nd
-
pa
s
s
f
il
ter
ope
r
a
ti
ng
a
t
12
.
475
GH
z
f
or
s
a
telli
tes
Ku
ba
nd
a
ppli
c
a
ti
ons
.
T
he
ba
nd
-
pa
s
s
f
il
ter
li
mi
ts
the
pa
s
s
-
ba
nd
be
twe
e
n
c
e
r
tain
lowe
r
a
nd
uppe
r
-
f
r
e
que
nc
y
li
mi
ts
,
in
whic
h
the
s
ignal
is
a
tt
e
nua
ti
ng
whe
ther
lowe
r
(
ba
nd
-
pa
s
s
)
or
highe
r
(
ba
n
d
-
s
top)
in
c
ompar
is
on
t
o
r
e
maining
f
r
e
que
nc
y
ba
nds
[
25
,
2
6]
.
T
he
m
icr
os
tr
ip
de
s
ign
a
ppr
oa
c
h
is
s
e
lec
ted
i
n
whic
h
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
c
ompac
t
s
iz
e
mic
r
os
tr
ip
fi
v
e
poles
hair
pin
band
-
pas
s
fi
lt
e
r
us
ing
thr
e
e
-
laye
r
s
...
.
(
Qaz
w
an
A
bdull
a
h)
81
the
pa
r
a
ll
e
l
c
oupli
ng
li
ne
s
model
is
us
e
d
to
s
how
t
he
be
ha
vior
of
the
f
il
ter
on
the
mul
ti
laye
r
s
ubs
tr
a
t
e
.
A
λ
/4
im
pe
da
nc
e
tr
a
ns
f
or
mer
wa
s
us
e
d
to
c
onne
c
t
e
a
c
h
p
a
ir
of
pa
r
a
ll
e
l
c
oupled
li
ne
s
.
T
he
ba
s
ic
p
r
inciples
of
mi
c
r
owa
ve
f
il
te
r
s
,
de
s
ign
a
r
r
a
nge
ments
a
nd
pe
r
f
or
manc
e
e
va
luations
we
r
e
s
tudi
e
d
in
thi
s
r
e
s
e
a
r
c
h.
T
he
outcome
o
f
thi
s
s
tud
y
ha
s
a
s
ha
r
p
f
r
e
que
nc
y
r
e
s
pons
e
,
lowe
r
ins
e
r
ti
on
los
s
a
nd
de
c
e
nt
r
e
f
lec
ti
on
los
s
c
ompar
e
d
to
p
r
e
vious
wor
ks
.
T
he
pa
pe
r
is
o
r
ga
nize
d
a
s
f
oll
ows
:
the
c
a
lcula
ti
on
of
f
il
ter
dim
e
ns
ion
a
s
s
howe
d
in
s
e
c
ti
on
two,
f
il
te
r
de
s
ig
n
c
onf
igur
a
ti
on
a
nd
methodology
a
r
e
pr
e
s
e
nted
i
n
s
e
c
ti
on
thr
e
e
.
E
M
s
im
ulation
r
e
s
ult
s
a
r
e
d
is
c
us
s
e
d
a
nd
a
n
a
lyze
d
in
the
f
our
th
s
e
c
ti
on
a
nd
f
inally,
the
c
onc
l
us
ion
of
the
wor
k
is
d
r
a
wn
in
s
e
c
ti
on
f
our
.
2.
S
YST
E
M
DE
S
I
GN
E
xplaining
F
il
ter
c
a
lcula
ti
on
s
tar
ts
by
c
onve
r
ti
ng
l
ow
pa
s
s
to
ba
ndpa
s
s
f
il
ter
pr
oto
type.
A
mi
c
r
os
tr
ip
ha
ir
pin
ba
ndpa
s
s
f
il
ter
is
buil
t
to
ob
tain
a
f
r
a
c
ti
ona
l
ba
ndwidth
(
F
B
W
)
=
0.
044
a
t
a
mi
d
-
ba
nd
f
r
e
que
nc
y
f
0
=
12.
475
GH
z
.
A
f
ive
poles
(
n
=
5)
C
he
bys
he
v
low
-
pa
s
s
s
y
s
tem
with
pa
s
s
-
ba
nd
r
ippl
e
s
of
0.
1d
dB
is
s
e
lec
ted.
T
he
low
-
pa
s
s
s
ys
tem
pa
r
a
mete
r
s
a
r
e
p
r
ovided
f
o
r
s
c
a
led
low
-
pa
s
s
c
u
t
of
f
f
r
e
que
nc
y
w
hich
a
r
e
;
Ωc
=
1,
g
0
=
1.
0
,
g
1
=
g
5
=
1.
1468
,
g
2
=
g
4
=
1
.
3712,
a
nd
g
3
=
1.
9750.
T
he
s
ubs
e
que
nt
s
tep
in
de
s
igni
ng
the
f
il
ter
is
f
ind
ing
the
d
im
e
ns
ions
of
c
oupled
m
icr
os
tr
ip
li
ne
s
that
e
mul
a
te
the
r
e
quir
e
d
c
ha
r
a
c
ter
is
ti
c
s
a
s
s
hown
in
T
a
ble
1
.
F
o
r
the
f
ir
s
t
c
oupli
ng
s
e
c
ti
on
J
01
Y
0
=
√
π
2
F
B
W
go
g
1
(
1
)
f
or
int
e
r
media
te
c
oupli
ng
s
e
c
ti
on
J
k
+
1
,
k
Y
0
=
π
F
B
W
2
1
√
g
k
g
k
+
1
k
=
1
to
n
−
1
(
2
)
f
or
f
ini
a
l
c
oupli
ng
s
e
c
ti
on
J
n
,
n
+
1
Y
0
=
√
π
2
F
B
W
g
n
g
n
+
1
(
3
)
t
o
f
ind
e
ve
n
-
a
nd
odd
mode
im
pe
da
nc
e
s
(
z
0e
)
j
,
j
+
1
=
1
Y
0
[
1
+
J
j
,
j
+
1
Y
0
+
(
J
j
,
j
+
1
Y
0
)
2
]
j
=
0
to
n
(
4
)
(
z
0o
)
j
,
j
+
1
=
1
Y
0
[
1
−
J
j
,
j
+
1
Y
0
+
(
J
j
,
j
+
1
Y
0
)
2
]
j
=
0
to
n
(
5
)
T
a
ble
1.
E
ve
n
-
mode
a
nd
odd
-
mode
c
ha
r
a
c
ter
is
ti
c
s
im
pe
da
nc
e
s
j
,
+
1
0
0
,
+
1
00
,
+
1
0
0.468
85.93
39.6092
1
0.287
65.16
43.37
2
0.173
58.1839
46.88
T
he
a
id
of
c
omput
e
r
de
s
ign
AD
S
(
a
dva
nc
e
d
De
s
ign
S
ys
tem)
c
a
n
be
us
e
d
to
c
a
lcula
te
the
dim
e
ns
ions
of
e
a
c
h
r
e
s
ona
tor
us
ing
the
odd
a
nd
e
ve
n
mode
va
lues
in
T
a
ble
1.
T
he
c
ha
r
a
c
ter
is
ti
c
im
pe
da
nc
e
Z
0
typ
ica
ll
y
is
a
s
s
umed
a
s
50
Ohms
.
E
a
c
h
s
tage
of
length
is
c
h
os
e
n
to
be
guided
wa
ve
length
(
)
whe
r
e
i
t
c
or
r
e
s
ponds
to
a
n
e
lec
tr
ica
l
length
(
E
e
f
f
)
a
s
90
0
.
F
r
om
the
s
c
he
matic
de
s
ign
us
ing
the
s
pe
c
ial
f
unc
ti
on
“
L
ine
C
a
lc”
,
the
dim
e
ns
ions
of
e
a
c
h
s
tage
a
r
e
c
a
lcula
ted,
f
or
m
a
ter
ials
R
O3003.
T
he
c
a
lcula
ted
dim
e
ns
ions
a
r
e
t
he
n
us
e
d
to
de
s
ign
a
nd
s
im
ulate
us
ing
C
S
T
s
of
twa
r
e
a
s
s
ho
wn
in
F
igu
r
e
1
a
nd
F
igur
e
2.
2.
1.
De
s
ign
t
h
e
p
r
op
os
e
d
b
a
n
d
-
p
as
s
f
il
t
e
r
T
he
thr
e
e
-
laye
r
a
r
c
hit
e
c
tur
e
of
the
r
e
duc
e
d
s
ize
ba
nd
-
pa
s
s
f
il
ter
pr
im
a
r
il
y
c
ons
is
ts
of
a
c
or
e
mate
r
ial
(
R
O3003)
,
g
r
ound
plane
a
nd
e
poxy
mate
r
ial
whic
h
is
us
e
d
to
f
il
l
the
s
pa
c
ing
be
twe
e
n
the
c
or
e
mat
e
r
ial
a
nd
the
gr
ound.
T
he
phys
ica
l
s
tr
uc
tur
e
f
or
p
r
opos
e
d
mul
ti
laye
r
f
il
te
r
c
ons
tr
uc
ti
on
is
pr
e
s
e
nted
a
s
in
F
igur
e
3.
Us
ing
thr
e
e
laye
r
s
pr
int
e
d
c
ir
c
uit
boa
r
d
(
P
C
B
)
,
t
he
m
ult
il
a
ye
r
c
ons
tr
uc
ti
on
is
c
r
e
a
ted
a
s
f
ol
lows
:
T
he
f
ir
s
t
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
.
1
,
F
e
br
ua
r
y
2020
:
80
-
89
82
laye
r
is
c
oppe
r
f
o
il
f
o
ll
owe
d
by
the
s
e
c
ond
laye
r
whic
h
is
made
of
e
poxy
mate
r
ial.
F
inally
,
the
c
or
e
mate
r
ial
that
c
ontains
the
uppe
r
a
nd
lowe
r
r
e
s
ona
tor
s
is
c
ons
tr
uc
ted
a
s
the
thi
r
d
laye
r
of
the
P
C
B
boa
r
d.
A
thr
e
e
-
laye
r
ha
ir
pin
f
il
te
r
s
tr
uc
tu
r
e
is
de
s
igned
ba
s
e
d
on
pa
r
a
ll
e
l
-
c
oupled
li
ne
mi
c
r
os
tr
ip
f
il
ter
s
.
T
he
ke
y
c
onc
e
pt
is
obtaining
good
c
oupli
ng
e
f
f
e
c
ts
via
f
oldi
ng
the
r
e
s
ona
tor
s
out
of
a
pa
r
a
ll
e
l
-
c
oupled
tr
a
ns
mi
s
s
ion
li
ne
.
T
o
a
c
c
ompl
is
h
r
obus
t
c
o
upli
ng
be
twe
e
n
r
e
s
ona
tor
s
,
a
djac
e
nt
r
e
s
ona
tor
s
a
r
e
ove
r
la
ppe
d
on
dif
f
e
r
e
nt
laye
r
s
.
T
he
f
il
ter
dim
e
ns
ions
a
r
e
opti
mi
z
e
d
f
or
r
e
s
pons
e
im
pr
ove
ment.
T
he
length
o
f
ha
ir
pin
r
e
s
ona
tor
s
be
c
ome
ve
r
y
s
hor
t
be
c
a
us
e
the
f
il
ter
is
ope
r
a
ti
ng
a
t
high
f
r
e
que
nc
y,
thus
,
ha
i
r
pin
s
tr
uc
tur
e
is
the
opti
mum
s
ha
pe
f
or
de
s
igni
ng
thi
s
f
il
ter
[
19
]
.
T
he
f
r
a
mew
or
k
o
f
the
r
e
s
ona
tor
s
is
il
lus
tr
a
ted
in
F
igur
e
3
,
whe
r
e
r
e
s
ona
tor
s
1,
3
a
nd
5
a
r
e
lo
c
a
ted
on
the
s
ur
f
a
c
e
of
the
thi
r
d
laye
r
diele
c
tr
ic
,
while
r
e
s
ona
tor
s
2
a
nd
4
a
r
e
pos
it
ioned
on
the
r
e
ve
r
s
e
s
ur
f
a
c
e
of
the
diele
c
tr
ic.
Adja
c
e
nt
r
e
s
ona
tor
s
li
ne
s
a
r
e
loca
ted
on
a
dif
f
e
r
e
nt
va
r
iation
of
ove
r
lapping
be
c
a
us
e
the
r
e
s
ona
tor
s
a
r
e
im
pleme
nted
in
a
two
-
laye
r
s
tr
uc
tur
e
to
a
c
hieve
f
il
ter
de
s
ign
r
e
quir
e
ments
.
T
he
f
il
te
r
de
s
ign
s
pe
c
if
ica
ti
ons
a
r
e
s
umm
a
r
ize
d
in
T
a
ble
2
c
ompar
ing
th
e
m
with
s
im
ulation
va
lues
.
T
he
f
il
ter
c
or
e
mate
r
ial
is
r
e
a
li
z
e
d
by
us
ing
R
oge
r
s
(
R
O3003)
s
ubs
tr
a
te
ha
ving
r
e
lative
pe
r
mi
tt
ivi
t
y
(
εr
)
of
3.
T
he
dim
e
ns
ions
of
the
c
or
e
mate
r
ial
of
the
f
il
ter
ha
ve
be
e
n
opti
mi
z
e
d
s
e
ve
r
a
l
ti
mes
to
obtain
the
r
e
quir
e
d
r
e
s
pons
e
that
f
ulf
il
ls
the
de
s
ign
s
pe
c
if
ica
ti
ons
.
F
igur
e
s
4
(
a
)
a
nd
(
b
)
s
hows
the
opti
mi
z
e
d
phys
ica
l
layout
of
the
uppe
r
a
nd
bott
om
r
e
s
ona
tor
s
of
the
f
il
ter
.
T
he
tot
a
l
dim
e
ns
ions
f
or
the
f
il
ter
a
r
e
9.
5
85×
14.
935×
1.
155
mm
3
.
T
a
ble
3
s
hows
the
phys
ica
l
dim
e
ns
ions
of
the
f
il
ter
a
f
ter
the
opti
mi
z
a
ti
on
pr
oc
e
s
s
.
F
igur
e
1.
the
c
a
lcula
ti
on
of
f
il
ter
dim
e
ns
ions
in
A
DS
F
igur
e
2.
T
he
r
e
s
pons
e
of
f
il
ter
d
im
e
ns
ions
in
AD
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
c
ompac
t
s
iz
e
mic
r
os
tr
ip
fi
v
e
poles
hair
pin
band
-
pas
s
fi
lt
e
r
us
ing
thr
e
e
-
laye
r
s
...
.
(
Qaz
w
an
A
bdull
a
h)
83
F
igur
e
3.
M
ult
il
a
ye
r
c
ons
tr
uc
ti
on
of
the
pr
opos
e
d
ba
nd
-
pa
s
s
f
il
ter
T
a
ble
2
.
S
im
ulation
r
e
s
ult
s
us
ing
C
S
T
a
nd
f
i
lt
e
r
de
s
ign
s
pe
c
if
ica
ti
ons
P
a
r
a
me
te
r
s
S
im
ul
a
ti
on V
a
lu
e
s
F
il
te
r
S
pe
c
if
ic
a
ti
ons
L
ow
e
r
c
ut
-
of
f
f
r
e
que
nc
y (
f
C
)
,
G
H
z
12.206
12.2
U
ppe
r
c
ut
-
of
f
f
r
e
que
nc
y (
f
L
)
,
G
H
z
12.629
12.75
I
ns
e
r
ti
on l
os
s
(
S
21)
, dB
-
2.297
>
-
3
R
e
tu
r
n l
os
s
(
S
11)
, dB
-
21.51
<
-
20
B
a
ndw
id
th
, M
H
z
429
550
C
e
nt
e
r
f
r
e
que
nc
y
12.449
12.475
F
igur
e
4.
T
he
phys
ica
l
s
tr
uc
tur
e
o
f
:
(
a
)
the
uppe
r
r
e
s
ona
tor
s
,
(
b)
bot
tom
r
e
s
ona
tor
s
3
(
a
)
(
b)
Evaluation Warning : The document was created with Spire.PDF for Python.
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S
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N
:
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E
L
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M
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KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
1
,
F
e
br
ua
r
y
2020
:
80
-
89
84
T
a
ble
3
.
P
hys
ica
l
dim
e
ns
ion
a
f
ter
opti
mi
z
a
ti
on
P
a
r
a
me
te
r
V
a
lu
e
(
mm
)
F
e
e
de
r
l
e
ngt
h, l
f
3.4675
F
e
e
de
r
w
id
th
, w
f
1.65
W
id
th
of
r
e
s
ona
to
r
, w
1.50
G
a
p be
twe
e
n r
e
s
ona
to
r
s
on t
op
la
ye
r
, gt
1.15
G
a
p be
twe
e
n r
e
s
ona
to
r
s
on i
nne
r
l
a
ye
r
, gi
1.1
3.
RE
S
UL
T
S
A
ND
AN
AL
YSI
S
T
he
f
il
ter
model
is
de
s
igned
a
nd
modele
d
with
the
he
lp
C
S
T
M
icr
owa
ve
S
tudi
o
(
C
S
T
M
W
S
)
s
im
ulator
.
F
o
r
a
c
hieving
the
tar
ge
t
s
pe
c
i
f
ica
ti
on
a
s
tabula
ted
in
T
a
ble
2
,
the
f
il
ter
s
c
a
tt
e
r
ing
pa
r
a
met
e
r
s
we
r
e
c
omput
e
d.
T
he
s
im
ulate
d
mul
ti
laye
r
ha
ir
pin
ba
n
d
-
pa
s
s
f
il
ter
e
xhibi
ts
low
ins
e
r
ti
on
los
s
of
-
2.
3
d
B
a
nd
a
r
e
f
lec
ti
on
c
oe
f
f
icie
nt
of
be
tt
e
r
than
-
21
dB
a
s
de
p
icte
d
in
F
igu
r
e
5
.
S
ome
f
u
r
t
he
r
d
im
e
ns
ion
opti
mi
z
a
ti
on
is
ne
e
de
d
to
a
c
hieve
a
be
tt
e
r
r
e
f
lec
ti
on
c
oe
f
f
icie
nt
a
nd
the
e
xa
c
t
ba
ndwidth.
Othe
r
f
a
c
tor
s
that
may
c
ontr
ibut
e
to
s
im
ulation
e
r
r
o
r
s
a
r
e
due
to
the
mate
r
ial
los
s
,
s
ub
s
tr
a
te
los
s
tange
nt
a
nd
the
a
dhe
s
ive
e
poxy
that
is
us
e
d
to
joi
n
the
f
il
ter
laye
r
s
.
How
e
ve
r
,
r
e
ga
r
ding
th
e
de
s
ign
s
pe
c
if
ica
ti
ons
a
nd
mul
ti
laye
r
f
il
ter
s
tr
uc
tur
e
dis
c
r
e
pa
nc
ies
,
the
a
c
hieve
d
S
-
pa
r
a
mete
r
r
e
s
ult
s
a
r
e
s
ti
ll
a
c
c
e
ptable
.
F
igur
e
5.
S
im
ulate
d
S
-
pa
r
a
mete
r
s
of
the
f
il
te
r
us
in
g
R
03003
s
ubs
tr
a
te
3.
1.
P
ar
am
e
t
r
ic
s
t
u
d
ies
T
his
ba
nd
-
pa
s
s
f
il
ter
de
s
ign
ha
s
s
e
ve
r
a
l
a
djus
table
pa
r
a
mete
r
s
that
ne
e
d
to
be
s
tudi
e
d.
T
h
is
pr
ovides
a
f
ur
ther
s
tudy
of
the
f
il
ter
be
ha
vior
a
nd
c
ompr
e
h
e
ns
ion
of
it
s
f
unc
ti
ona
li
ty
a
nd
pe
r
f
or
manc
e
.
T
he
r
e
f
or
e
,
thi
s
s
e
c
ti
on
will
int
r
oduc
e
s
ome
pa
r
a
metr
ic
s
tudi
e
s
a
nd
a
na
lys
e
s
that
ha
ve
be
e
n
c
a
r
r
ied
out
us
ing
the
s
we
e
p
pa
r
a
metr
ic
f
unc
ti
on
of
the
e
lec
tr
omagne
ti
c
s
im
ulat
ion
s
of
twa
r
e
C
S
T
M
icr
owa
ve
S
tudi
o.
F
or
the
a
im
of
pe
r
f
or
manc
e
c
ompar
is
on,
a
F
la
me
R
e
tar
da
nt
4
(
F
R
4)
s
ubs
tr
a
te
with
diele
c
tr
ic
p
a
r
a
mete
r
(
εr
)
of
4
.
6
is
a
ls
o
uti
li
z
e
d
a
s
the
c
or
e
mate
r
ial
of
the
f
il
ter
.
C
ha
nging
the
c
or
e
ma
ter
ial
of
the
mul
ti
laye
r
ha
ir
p
in
f
il
ter
f
r
om
R
O3003
s
ubs
tr
a
t
e
to
F
R
4
s
ubs
tr
a
te
ha
d
a
f
f
e
c
ted
the
f
il
ter
be
ha
vior
.
F
igur
e
6
s
hows
the
S
-
pa
r
a
mete
r
c
ompar
is
on
of
the
two
diele
c
tr
ic
s
ubs
tr
a
tes
a
s
the
c
or
e
mate
r
ial
of
the
f
il
ter
.
B
y
c
ompar
ing
the
s
im
ulation
r
e
s
ult
s
of
the
de
s
ign
us
ing
R
O3003
a
nd
F
R
4,
it
c
a
n
e
a
s
il
y
be
obs
e
r
ve
d
the
a
dva
ntage
of
us
ing
a
s
ubs
tr
a
te
with
lowe
r
diel
e
c
tr
ic
c
ons
tant
a
nd
los
s
tange
nt
.
R
oge
r
s
R
O3
003
s
ubs
tr
a
te
pe
r
f
or
med
be
tt
e
r
than
F
R
4
s
ubs
tr
a
te
by
im
pr
ov
ing
the
f
i
lt
e
r
r
e
s
pons
e
(
lowe
r
ins
e
r
ti
on
los
s
a
nd
higher
r
e
f
lec
ti
on
c
oe
f
f
icie
nt
.
T
he
e
f
f
e
c
t
of
incr
e
a
s
ing
the
r
e
s
ona
tor
length
(
L
)
on
the
f
il
te
r
S
-
pa
r
a
mete
r
s
a
nd
ba
ndwidth
pe
r
f
or
manc
e
is
thor
oughly
e
xa
mi
ne
d.
T
he
lengths
of
the
r
e
s
ona
tor
s
a
r
e
va
r
ied
f
r
om
the
o
r
igi
na
l
lengt
h
(
L
)
to
L
+
0.
2
a
nd
L
+
0.
3
while
the
r
e
s
ona
tor
s
widths
(
W
)
a
r
e
ke
pt
c
ons
tant.
B
y
incr
e
a
s
ing
the
le
ngth
of
the
r
e
s
ona
tor
s
,
the
ba
ndwidth
r
e
s
pons
e
of
the
f
il
te
r
s
hif
ts
to
the
lef
t
a
nd
vice
ve
r
s
a
.
F
igu
r
e
s
7
a
nd
8
il
lus
tr
a
te
the
e
f
f
e
c
t
of
incr
e
a
s
ing
the
lengths
o
f
the
r
e
s
ona
tor
s
on
the
loca
ti
on
o
f
the
ba
ndwidth.
I
t
c
a
n
be
obs
e
r
ve
d
f
r
om
F
igur
e
9
that
the
r
e
f
lec
ti
on
c
oe
f
f
icie
nt
r
e
s
pons
e
of
the
f
il
te
r
de
c
r
e
a
s
e
s
,
a
nd
the
ins
e
r
ti
on
los
s
dr
ops
whe
n
the
r
e
s
ona
tor
lengths
a
r
e
incr
e
a
s
e
d.
10
1
0
.
5
11
1
1
.
5
12
1
2
.
5
13
1
3
.
5
14
-4
5
-4
0
-3
5
-3
0
-2
5
-2
0
-1
5
-1
0
-5
0
F
re
q
u
e
n
c
y
(G
H
z
)
S-p
a
ra
m
e
t
e
rs
(d
B)
S1
1
S2
1
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
c
ompac
t
s
iz
e
mic
r
os
tr
ip
fi
v
e
poles
hair
pin
band
-
pas
s
fi
lt
e
r
us
ing
thr
e
e
-
laye
r
s
...
.
(
Qaz
w
an
A
bdull
a
h)
85
F
igur
e
6.
P
e
r
f
or
manc
e
c
ompar
is
on
o
f
s
im
ulate
d
S
-
pa
r
a
mete
r
s
of
the
f
i
lt
e
r
us
ing
R
O3003
a
nd
F
R
4
s
ubs
tr
a
tes
a
s
c
or
e
mate
r
ials
F
igur
e
7.
R
e
f
lec
ti
on
c
oe
f
f
icie
nt
s
hif
ti
ng
(
S
11
)
by
va
r
ying
the
length
of
the
r
e
s
ona
tor
us
ing
R
O3003
s
ubs
tr
a
te
F
igur
e
8
.
R
e
f
lec
ti
on
c
oe
f
f
icie
nt
s
hif
ti
ng
(
S
11
)
by
va
r
ying
the
width
of
the
r
e
s
ona
tor
us
ing
R
O3003
s
ubs
tr
a
te
F
igur
e
9
.
I
ns
e
r
ti
on
los
s
s
hif
ti
ng
(
S
21)
by
va
r
ying
t
he
length
of
the
r
e
s
ona
tor
us
ing
R
O3003
s
ubs
tr
a
te
F
or
a
s
s
e
s
s
ing
the
im
pa
c
ts
of
the
r
e
s
ona
tor
widt
h
on
s
c
a
tt
e
r
ing
pa
r
a
mete
r
be
ha
vior
of
the
f
il
te
r
,
the
widths
of
the
r
e
s
ona
tor
s
we
r
e
va
r
ied
a
nd
e
a
c
h
ti
me
the
s
im
ulate
d
r
e
s
ult
s
we
r
e
c
omput
e
d.
S
i
mi
lar
to
the
r
e
s
ona
tor
length,
the
widths
of
the
r
e
s
ona
tor
s
a
r
e
va
r
ied
f
r
om
the
or
igi
na
l
width
(
W
)
to
W
-
0.
1a
nd
W
-
0.
3
while
the
r
e
s
ona
tor
s
lengths
(
L
)
a
r
e
ke
pt
c
ons
tant.
B
y
de
c
r
e
a
s
ing
the
width
o
f
the
r
e
s
ona
tor
s
,
the
ba
ndwidth
r
e
s
pons
e
of
the
f
il
te
r
s
hif
ts
to
the
r
ight
a
nd
vice
ve
r
s
a
.
T
he
s
im
ulate
d
r
e
s
ult
s
in
F
igur
e
s
8
a
nd
10
r
e
ve
a
ls
that
the
e
f
f
e
c
t
of
incr
e
a
s
ing
the
width
of
the
r
e
s
ona
tor
s
on
the
loca
ti
on
of
the
ba
ndwidth.
How
e
ve
r
,
incr
e
a
s
ing
the
r
e
s
ona
tor
widths
will
not
c
a
us
e
much
e
f
f
e
c
t
on
r
e
f
lec
ti
on
c
oe
f
f
icie
nt
(
S
11)
a
nd
ins
e
r
ti
on
los
s
(
S
21)
pe
r
f
or
manc
e
,
but
only
c
a
us
e
s
ba
ndwidth
s
hif
t
to
the
r
ight
.
B
y
incr
e
a
s
ing
the
wa
ve
length
(
λ
)
,
the
phys
ica
l
s
ize
of
the
f
il
ter
wil
l
incr
e
a
s
e
be
c
a
us
e
it
ha
s
be
e
n
c
ons
ider
e
d
that
the
length
of
the
f
e
e
de
r
s
is
λ
/4
a
nd
the
dis
tanc
e
be
twe
e
n
the
r
e
s
ona
tor
s
a
nd
the
e
dge
of
the
f
il
ter
on
the
uppe
r
a
nd
the
bott
om
s
ides
is
λ
/
4
a
s
we
ll
.
Anothe
r
e
f
f
e
c
t
of
incr
e
a
s
ing
the
wa
ve
length
is
to
de
c
r
e
a
s
e
the
magnitude
of
the
r
e
tur
n
los
s
(
S
11)
a
nd
not
much
c
ha
nge
in
the
va
lue
of
the
ins
e
r
ti
on
los
s
(
S
21)
.
F
igur
e
s
11
a
nd
12
s
how
the
e
f
f
e
c
t
o
f
incr
e
a
s
ing
the
wa
ve
length
a
nd
it
s
e
f
f
e
c
t
on
both
the
r
e
tur
n
los
s
a
nd
the
ins
e
r
ti
on
los
s
r
e
s
pe
c
ti
ve
ly.
All
thes
e
a
na
lys
e
s
ha
ve
be
e
n
done
by
us
ing
the
s
we
e
p
pa
r
a
mete
r
f
u
nc
ti
on
in
the
s
im
ulation
s
of
twa
r
e
(
C
S
T
)
to
e
a
s
e
the
s
tudy
of
the
e
f
f
e
c
ti
ve
ne
s
s
of
c
ha
nging
one
o
f
the
pa
r
a
mete
r
s
of
the
f
il
ter
r
a
ther
t
ha
n
us
ing
the
nor
mal
method
(
c
ha
nge
the
dim
e
ns
ion
one
a
t
a
ti
me
a
nd
s
im
ulate
.
10
1
0
.
5
11
1
1
.
5
12
1
2
.
5
13
1
3
.
5
14
-4
5
-4
0
-3
5
-3
0
-2
5
-2
0
-1
5
-1
0
-5
0
F
re
q
u
e
n
c
y
(G
H
z
)
S-p
a
ra
m
e
t
e
rs
(d
B)
S1
1
R
O
3
0
0
3
S1
1
F
R
4
S2
1
R
O
3
0
0
3
S2
1
F
R
4
10
1
0
.
5
11
1
1
.
5
12
1
2
.
5
13
1
3
.
5
14
-2
5
-2
0
-1
5
-1
0
-5
0
F
re
q
u
e
n
c
y
(G
H
z
)
S1
1
(d
B)
L
L
+
0
.
2
L
+
0
.
3
10
1
0
.
5
11
1
1
.
5
12
1
2
.
5
13
1
3
.
5
14
-3
5
-3
0
-2
5
-2
0
-1
5
-1
0
-5
0
F
re
q
u
e
n
c
y
(G
H
z
)
S1
1
(d
B)
W
W
-0
.
1
W
-0
.
3
10
1
0
.
5
11
1
1
.
5
12
1
2
.
5
13
1
3
.
5
14
-5
0
-4
0
-3
0
-2
0
-1
0
0
F
re
q
u
e
n
c
y
(G
H
z
)
S2
1
(d
B)
L
L
+
0
.
2
L
+
0
.
3
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
.
1
,
F
e
br
ua
r
y
2020
:
80
-
89
86
F
igur
e
10.
I
ns
e
r
ti
on
los
s
s
hif
ti
ng
(
S
21)
by
va
r
ying
the
width
of
the
r
e
s
ona
tor
us
ing
R
O3003
s
ubs
tr
a
te
F
igur
e
11.
R
e
tur
n
los
s
(
S
11)
by
va
r
ying
the
wa
ve
le
ngth
(
λ
)
F
igur
e
12.
I
ns
e
r
ti
on
los
s
(
S
21)
by
va
r
y
ing
the
wa
v
e
length
(
λ
)
4.
CONC
L
USI
ON
I
n
thi
s
pa
pe
r
,
a
c
ompac
t
mul
ti
laye
r
ha
ir
pin
mi
c
r
os
t
r
ip
ba
nd
-
pa
s
s
f
il
ter
ba
s
e
d
on
pa
r
a
l
lel
-
c
oupled
li
ne
r
e
s
ona
tor
s
f
or
Ku
-
ba
nd
a
ppli
c
a
ti
ons
is
de
s
ign
e
d
a
nd
modele
d
with
the
he
lp
of
C
S
T
mi
c
r
owa
v
e
s
tudi
o
s
of
twa
r
e
.
T
he
mul
ti
laye
r
ha
ir
pin
f
il
te
r
int
r
oduc
e
d
a
s
igni
f
ica
nt
s
ize
r
e
duc
ti
on
a
nd
be
tt
e
r
pe
r
f
or
manc
e
c
ompar
e
d
to
o
ther
ba
nd
-
pa
s
s
f
il
ter
s
na
mely
,
c
ombi
ne
f
il
ter
,
int
e
r
-
digi
tal
f
il
ter
,
a
nd
pa
r
a
ll
e
l
-
c
oupled
li
ne
f
il
ter
.
T
he
s
im
ulate
d
ins
e
r
ti
on
los
s
a
nd
r
e
f
lec
ti
on
c
o
e
f
f
icie
nt
r
e
s
ult
s
s
how
a
good
matc
h
with
the
r
e
quir
e
d
s
pe
c
if
ica
ti
ons
of
thi
s
s
tudy.
Us
ing
the
s
we
e
p
pa
r
a
mete
r
f
unc
ti
on
of
the
C
S
T
s
of
twa
r
e
,
s
igni
f
ica
nt
a
n
a
lys
is
a
nd
pa
r
a
metr
ic
s
tudy
o
f
the
f
il
te
r
wa
s
pe
r
f
or
med.
T
he
pr
opos
e
d
f
il
ter
de
s
ign
a
c
hieve
s
a
good
f
il
ter
s
ize
r
e
duc
ti
on
a
nd
the
pa
r
a
metr
ic
s
tudi
e
s
int
r
oduc
e
a
s
im
p
le
tec
hnique
of
c
ontr
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T
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ipl
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R
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gr
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GS/
1/2018/
T
K04/UM
P
/02/
11
(
R
D
U190133)
.
RE
F
E
RE
NC
E
S
[1
]
I.
C.
H
u
n
t
er,
et
a
l
.
,
“
Mi
cr
o
w
a
v
e
fi
l
t
er
s
-
ap
p
l
i
cat
i
o
n
s
an
d
t
ech
n
o
l
o
g
y
,”
IE
E
E
Tr
a
n
s
a
c
t
i
o
n
s
o
n
M
i
cr
o
wa
ve
Th
e
o
r
y
a
n
d
Tech
n
i
q
u
es
,
v
o
l
.
5
0
,
n
o
.
3
,
p
p
.
7
9
4
-
8
0
5
,
Mar
2
0
0
2
.
[2
]
J
.
N
i
,
“
D
e
v
el
o
p
me
n
t
o
f
t
u
n
a
b
l
e
a
n
d
mi
n
i
a
t
u
re
m
i
cro
w
av
e
fi
l
t
er
s
fo
r
m
o
d
er
n
w
i
rel
e
s
s
c
o
mmu
n
i
ca
t
i
o
n
s
,”
Ph
.
D
.
d
i
s
s
.
,
E
n
g
i
n
eeri
n
g
&
Ph
y
s
i
cal
Sci
e
n
ces
,
H
er
i
o
t
-
W
at
t
U
n
i
v
er
s
i
t
y
,
2
0
1
4
.
[3
]
M.
K
.
A
l
k
h
afa
j
i
,
et
al
.
,
“
D
e
s
i
g
n
o
f
a
s
e
l
ect
i
v
e
fi
l
t
er
-
a
n
t
en
n
a
w
i
t
h
l
o
w
i
n
s
ert
i
o
n
l
o
s
s
an
d
h
i
g
h
s
u
p
p
res
s
i
o
n
s
t
o
p
b
an
d
fo
r
W
i
M
A
X
ap
p
l
i
cat
i
o
n
s
,”
In
t
er
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
S
en
s
o
r
Net
w
o
r
k
s
a
n
d
D
a
t
a
Co
m
m
u
n
i
ca
t
i
o
n
s
,
v
o
l
.
5
,
n
o
.
3
,
p
p
.
1
-
7
,
2
0
1
6
.
[4
]
S
.
E
.
J
as
i
m
an
d
M
.
A
.
J
u
s
o
h
,
“D
es
i
g
n
Bro
ad
Ba
n
d
w
i
d
t
h
M
i
cro
w
av
e
Ba
n
d
p
as
s
Fi
l
t
er
o
f
1
0
G
h
z
O
p
era
t
i
n
g
Freq
u
e
n
cy
U
s
i
n
g
H
fs
s
,
”
P
r
o
cee
d
i
n
g
s
o
f
1
1
9
t
h
Th
e
IIE
R
In
t
e
r
n
a
t
i
o
n
a
l
Co
n
f
er
e
n
ce,
P
u
t
r
a
j
a
y
a
,
M
a
l
a
ys
i
a
,
p
p
.
3
1
-
34
,
S
ep
2
0
1
7
.
[5
]
D
.
Marp
au
n
g
,
et
a
l
.
,
“
L
o
w
-
p
o
w
er,
ch
i
p
-
b
as
e
d
s
t
i
m
u
l
at
ed
Br
i
l
l
o
u
i
n
s
cat
t
eri
n
g
m
i
cro
w
av
e
p
h
o
t
o
n
i
c
fi
l
t
er
w
i
t
h
u
l
t
rah
i
g
h
s
el
ec
t
i
v
i
t
y
,”
O
p
t
i
ca
,
v
o
l
.
2
,
n
o
.
2
,
p
p
.
7
6
-
8
3
,
2
0
1
5
.
[6
]
I.
A
zad
,
et
a
l
.
,
“
D
es
i
g
n
an
d
p
e
rfo
rma
n
ce
an
a
l
y
s
i
s
o
f
2
.
4
5
G
H
z
mi
cr
o
w
a
v
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b
a
n
d
p
as
s
fi
l
t
er
w
i
t
h
r
ed
u
ced
h
armo
n
i
cs
,”
In
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
E
n
g
i
n
ee
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n
g
R
es
e
a
r
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h
a
n
d
D
ev
el
o
p
m
e
n
t
,
v
o
l
.
5
,
n
o
.
1
1
,
p
p
.
5
7
-
6
7
,
Feb
2
0
1
3
.
[7
]
R.
J
.
Camero
n
,
et
a
l
,
“
Mi
cr
o
w
a
v
e
Fi
l
t
er
s
f
o
r
C
o
mmu
n
i
cat
i
o
n
S
y
s
t
ems
:
Fu
n
d
ame
n
t
a
l
s
,
D
e
s
i
g
n
,
A
n
d
A
p
p
l
i
ca
t
i
o
n
s
,
”
2nd
e
d
.
,
J
o
h
n
W
i
l
e
y
&
So
n
s
,
In
c,
2
0
1
8
.
[8
]
L
.
T
.
Ph
u
o
n
g
,
et
al
,
“Res
earch
,
d
es
i
g
n
an
d
fa
b
ri
ca
t
i
o
n
o
f
a
mi
cro
w
a
v
e
a
ct
i
v
e
fi
l
t
er
fo
r
n
an
o
s
a
t
el
l
i
t
e'
s
rece
i
v
er
fro
n
t
-
en
d
s
a
t
s
-
b
a
n
d
,
”
T
E
LKO
M
NIKA
Te
l
eco
m
m
u
n
i
ca
t
i
o
n
C
o
m
p
u
t
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n
g
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l
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c
s
a
n
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r
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,
v
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l
.
1
7
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o
.
1
,
p
p
.
23
-
3
1
,
Feb
2
0
1
9
.
[9
]
J.
Z
ai
d
i
,
et
al
.
,
“H
i
g
h
-
Per
fo
rma
n
ce
Co
mp
ac
t
Mi
cr
o
w
a
v
e
Fi
l
t
er
s
fo
r
Sp
ace
A
p
p
l
i
c
at
i
o
n
s
,
”
P
r
o
cee
d
i
n
g
s
o
f
2
0
1
2
9
th
In
t
e
r
n
a
t
i
o
n
a
l
B
h
u
r
b
a
n
Co
n
f
e
r
en
ce
o
n
A
p
p
l
i
e
d
S
ci
e
n
ces
&
Tech
n
o
l
o
g
y
(IB
C
A
S
T)
,
p
p
.
3
7
9
-
3
8
2
,
2
0
1
2
.
[1
0
]
Y
.
X
.
J
i
,
et
al
.
,
“
Co
m
p
act
a
n
d
h
i
g
h
-
p
er
fo
rma
n
ce
b
an
d
p
a
s
s
fi
l
t
er
b
as
e
d
o
n
a
n
i
m
p
ro
v
ed
h
y
b
r
i
d
re
s
o
n
at
o
r
u
s
i
n
g
b
eel
i
n
e
co
m
p
act
mi
c
r
o
s
t
ri
p
res
o
n
at
o
r
cel
l
(BCMRC)
,”
Jo
u
r
n
a
l
o
f
E
l
ec
t
r
o
m
a
g
n
et
i
c
W
a
ve
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
2
5
,
n
o
.
1
1
,
p
p
.
1
5
2
5
-
1
5
3
5
,
J
an
2
0
1
1
.
[1
1
]
D
.
M.
Po
zar,
“
Mi
cro
w
a
v
e
E
n
g
i
n
eeri
n
g
,
”
4
th
ed
.
J
o
h
n
W
i
l
ey
&
So
n
s
,
In
c.
,
N
o
v
2
0
1
1
.
[1
2
]
K
.
G
u
p
t
a,
“Rev
i
ew
o
f
Pl
a
n
ar
Mi
cr
o
s
t
ri
p
Fi
l
t
ers
F
o
r
w
i
rel
es
s
co
mmu
n
i
ca
t
i
o
n
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
S
ci
e
n
t
i
f
i
c
R
es
e
a
r
c
h
E
n
g
i
n
eer
i
n
g
&
Tech
n
o
l
o
g
y
(IJ
S
R
E
T)
,
E
A
T
H
D
2
0
1
5
Co
n
f
er
en
ce
P
r
o
cee
d
i
n
g
,
p
p
.
7
7
-
83
,
2
0
1
5
.
[1
3
]
R.
E
.
Co
l
l
i
n
,
“
Fo
u
n
d
at
i
o
n
s
fo
r
Mi
cro
w
av
e
E
n
g
i
n
eer
i
n
g
,
”
2
nd
E
d
i
t
i
o
n
,
W
i
l
ey
-
I
E
E
E
Pres
s
,
J
a
n
2
0
0
1
.
[1
4
]
M.
H
.
W
en
g
,
et
al
.
,
“Mi
n
i
at
u
ri
ze
d
mu
l
t
i
l
ay
er
h
a
i
rp
i
n
b
an
d
p
as
s
fi
l
t
er
w
i
t
h
t
u
n
ab
l
e
t
ra
n
s
mi
s
s
i
o
n
zero
s
,
”
M
i
cr
o
w
a
ve
a
n
d
O
p
t
i
c
a
l
Tec
h
n
o
l
o
g
y
Let
t
er
s
,
v
o
l
.
4
1
,
n
o
.
1
,
p
p
.
5
3
-
5
5
,
Feb
2
0
0
4
.
[1
5
]
D
.
T
o
š
i
ć
an
d
M
.
Po
t
reb
i
ć
,
“
Co
m
p
act
M
u
l
t
i
l
ay
er
Ban
d
p
as
s
Fi
l
t
er
w
i
t
h
M
o
d
i
fi
e
d
H
ai
r
p
i
n
Res
o
n
a
t
o
r
s
,”
Jo
u
r
n
a
l
o
f
M
i
c
r
o
e
l
ect
r
o
n
i
c
s
,
E
l
ec
t
r
i
c
Co
m
p
o
n
en
t
s
a
n
d
M
a
t
er
i
a
l
s
,
v
o
l
.
4
2
,
n
o
.
2
,
p
p
.
1
2
3
-
1
3
0
,
2
0
1
2
.
[1
6
]
Y
.
J
en
an
d
M.
L
i
n
,
“D
es
i
g
n
an
d
Fab
r
i
cat
i
o
n
o
f
a
N
arro
w
Ban
d
p
as
s
Fi
l
t
er
w
i
t
h
L
o
w
D
ep
en
d
en
c
e
o
n
A
n
g
l
e
o
f
In
ci
d
en
ce,
”
Co
a
t
i
n
g
s
,
v
o
l
.
8
,
n
o
.
7
,
p
p
.
2
3
1
-
2
3
8
,
J
u
n
2
0
1
8
.
[1
7
]
H
.
O
rai
zi
a
n
d
N
.
A
za
d
i
-
t
i
n
at
,
“O
p
t
i
mu
m
D
e
s
i
g
n
o
f
N
o
v
el
U
W
B
Mu
l
t
i
l
ay
er
Mi
cro
s
t
r
i
p
H
a
i
rp
i
n
Fi
l
t
er
s
w
i
t
h
H
armo
n
i
c
S
u
p
p
res
s
i
o
n
a
n
d
Im
p
ed
a
n
ce
Ma
t
c
h
i
n
g
,
”
In
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
n
t
en
n
a
s
a
n
d
P
r
o
p
a
g
a
t
i
o
n
,
v
o
l
.
2
0
1
2
,
Sep
2
0
1
2
.
[1
8
]
X
.
G
u
,
et
al
.
,
“
A
Co
m
p
act
H
ai
r
p
i
n
Ba
n
d
p
as
s
Fi
l
t
er
U
s
i
n
g
Mu
l
t
i
l
a
y
er
St
r
i
p
l
i
n
e
F
o
l
d
ed
Q
u
ar
t
er
-
W
a
v
el
e
n
g
t
h
Res
o
n
at
o
rs
,
”
M
i
cr
o
wa
ve
a
n
d
O
p
t
i
c
a
l
Tech
n
o
l
o
g
y
Let
t
er
s
,
v
o
l
.
5
4
,
n
o
.
1
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18
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2020
:
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Evaluation Warning : The document was created with Spire.PDF for Python.