Int
ern
at
i
onal
Journ
al of Ele
ctrical
an
d
Co
mput
er
En
gin
eeri
ng
(IJ
E
C
E)
Vo
l.
11
,
No.
1
,
Febr
uar
y
2021
, pp.
458
~
470
IS
S
N: 20
88
-
8708
,
DOI: 10
.11
591/
ijece
.
v11
i
1
.
pp
458
-
470
458
Journ
al h
om
e
page
:
http:
//
ij
ece.i
aesc
or
e.c
om
Social
-
si
ne cosin
e algo
rith
m
-
based
cross l
ayer
re
s
ource
allocatio
n in
wire
less netw
or
k
Pra
veen
a
T
.
,
Nag
araj
a
G
.
S
.
Depa
rtment
o
f
C
om
pute
r
Scie
n
ce a
nd
Engi
n
ee
rin
g,
RV Col
le
g
e
o
f
E
ngin
ee
ring
,
In
dia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Feb
26
, 20
20
Re
vised
Ju
l
2
2, 2020
Accepte
d
Aug 13,
2020
Cross
lay
er
res
ourc
e
al
lo
ca
t
ion
in
th
e
wire
le
s
s
net
works
is
appr
oac
h
ed
tra
ditiona
lly
e
ither
b
y
comm
unic
a
ti
ons
net
wo
rks
or
informati
on
the
o
r
y
.
The
m
aj
or
issue
in
net
working
is
the
al
locati
on
of
li
m
it
ed
re
source
s
from
the
users
of
net
work.
In
tr
ad
it
ional
lay
e
red
net
work,
th
e
re
source
are
al
lo
ca
t
ed
at
m
edi
um
ac
ce
ss
cont
rol
(MA
C)
and
the
net
work
lay
ers
uses
the
comm
unic
at
i
on
li
nks
in
bi
t
p
i
pes
for
d
el
iv
eri
n
g
the
da
ta
at
fixed
rate
wi
th
the
o
cc
asion
al
r
andom
err
ors.
Henc
e,
th
is
pap
er
pre
sen
ts
th
e
cro
ss
-
lay
er
resourc
e
allocati
on
in
wire
le
ss
net
work
base
d
on
the
proposed
socia
l
-
sin
e
cosine
a
lgori
th
m
(SS
C
A).
The
proposed
SS
C
A
is
designe
d
b
y
in
te
gr
at
in
g
socia
l
ski
dr
ive
r
(SS
D)
and
sine
cosine
al
gori
th
m
(SCA
).
Als
o,
for
furthe
r
ref
ini
ng
the
reso
urc
e
al
lo
ca
t
ion
s
che
m
e,
the
p
rop
osed
SS
CA
uses
the
f
it
n
ess
base
d
on
ene
rg
y
and
fa
irne
ss
in
which
m
ax
-
m
in,
har
d
-
fa
irne
ss
,
p
roporti
ona
l
fai
rne
ss
,
m
ixe
d
-
bia
s
and
the
m
a
ximum
through
put
is
conside
re
d.
Based
o
n
ene
rg
y
and
fa
irn
es
s,
the
cro
ss
-
layer
opti
m
izat
ion
e
nti
t
y
m
ake
s
the
dec
ision
o
n
resourc
e
a
ll
o
ca
t
i
on
to
m
it
iga
t
e
th
e
sum
rat
e
of
ne
twork.
The
p
erf
orm
anc
e
of
resourc
e
allocati
on
base
d
on
pro
posed
m
odel
is
eva
lu
at
ed
base
d
on
ene
r
g
y
,
throughput
,
and
the
fai
rne
ss
.
T
he
deve
lop
ed
m
odel
ac
h
ie
ves
t
he
m
axi
m
al
ene
rg
y
of
258213,
m
axi
m
al
throughput
of
3.
703,
and
the
m
axi
m
al
fai
rne
ss
of
0.
868,
respe
c
ti
v
e
l
y
.
Ke
yw
or
d
s
:
Cros
s
-
la
ye
r op
t
i
m
iz
ation
Energy
Re
so
urce al
loc
at
ion
Sine c
os
ine
alg
or
it
hm
So
ci
al
s
ki driv
er
This
is an
open
acc
ess ar
ticle un
der
the
CC
B
Y
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
Pr
a
veen
a
T.,
Dep
a
rtm
ent o
f C
om
pu
te
r
Scie
nce a
nd E
ng
i
ne
erin
g,
RV Colle
ge
of
En
gin
eeri
ng,
Be
ng
al
uru,
Ka
rn
at
a
ka
, In
dia
.
Em
a
il
:
pr
avee
n
at
@r
vce
.e
du.in
1.
INTROD
U
CTION
In
the
la
st
few
decad
es
,
the
wireless
com
m
un
ic
at
ion
s
ha
ve
bee
n
gro
w
n
rap
i
dly
in
the
wo
rl
dw
i
de.
Howe
ver,
the
up
c
om
ing
wi
r
el
ess
com
m
un
ic
at
ion
has
prov
i
ded
va
rio
us
ser
vices
of
hi
gh
-
qual
it
y
vo
i
ce
to
the
wireless
m
ultim
edia
fo
r
e
ver
y
wh
e
re
at
low
co
st
[1
]
.
T
he
wireless
network
is
al
so
sa
id
to
be
I
nter
na
ti
on
al
Mob
il
e
Tel
eco
m
m
un
ic
at
ion
s
2000
(I
MT
-
2000)
f
or
prov
i
din
g
the
se
rv
ic
es
us
in
g
m
ult
i
m
e
dia
m
ob
il
e
to
at
ta
in
t
h
e
h
i
g
h
b
i
t
r
a
t
e
o
f
a
b
o
u
t
2
M
b
/
s
[
2
]
.
T
o
f
u
l
f
i
l
l
u
s
e
r
r
e
q
u
i
r
e
m
e
n
t
s
,
t
h
e
s
e
r
v
i
c
e
p
r
o
v
i
d
e
r
i
n
c
l
u
d
e
s
v
a
r
i
o
u
s
t
e
c
h
n
i
q
u
e
s
,
l
i
k
e
c
r
o
s
s
-
l
a
y
e
r
d
e
s
i
g
n
a
n
d
c
o
-
o
p
e
r
a
t
i
v
e
r
e
l
a
y
i
n
g
i
n
t
h
e
w
i
r
e
l
e
s
s
c
o
m
m
u
n
i
c
a
t
i
o
n
s
y
s
t
e
m
s
.
T
h
e
c
o
-
o
p
e
r
a
t
i
v
e
r
e
l
a
y
i
n
g
i
s
u
t
i
l
i
z
e
d
t
o
i
m
p
r
o
v
e
t
h
e
c
o
v
e
r
a
g
e
o
f
b
a
s
e
s
t
a
t
i
o
n
(
B
S
)
a
n
d
t
h
e
s
y
s
t
e
m
c
a
p
a
c
i
t
y
i
n
w
i
r
e
l
e
s
s
co
m
m
u
n
i
c
a
t
i
o
n
n
e
t
w
o
r
k
[
3
,
4
].
W
h
i
l
e
v
a
r
y
i
n
g
t
h
e
c
h
a
n
n
e
l
-
s
t
a
t
e
i
n
f
o
r
m
a
t
i
o
n
(
C
S
I
)
a
n
d
q
u
e
u
e
-
s
t
a
t
e
i
n
f
o
r
m
a
t
i
o
n
(
Q
S
I
)
i
n
w
i
r
e
l
e
s
s
n
e
t
w
o
r
k
,
t
h
e
n
o
d
e
s
a
c
c
e
p
t
t
h
e
i
r
r
e
c
e
p
t
i
o
n
a
n
d
t
h
e
t
r
a
n
s
m
i
s
s
i
o
n
p
a
r
a
m
e
t
e
r
s
w
i
t
h
p
o
w
e
r
c
o
n
s
t
r
a
i
n
t
s
a
n
d
t
h
e
q
u
a
l
i
t
y
o
f
s
e
r
v
i
c
e
(
Q
o
S
)
n
e
e
d
s
[
5
]
,
b
u
t
s
t
i
l
l
t
h
e
c
h
a
n
n
e
l
s
u
n
d
e
r
g
o
t
i
m
e
v
a
r
y
i
n
g
m
u
l
t
i
p
a
t
h
f
a
d
i
n
g
.
A
d
d
i
t
i
o
n
a
l
l
y
,
t
h
e
i
n
f
l
e
x
i
b
i
l
i
t
y
a
n
d
t
h
e
s
u
b
-
o
p
t
i
m
a
l
i
t
y
r
e
s
u
l
t
s
i
n
i
n
e
f
f
i
c
i
e
n
t
r
e
s
o
u
r
c
e
i
n
t
h
e
w
i
r
e
l
e
s
s
n
e
t
w
o
r
k
s
[
6
,
7
].
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
So
ci
al
-
sine
c
os
ine a
l
gorit
hm
-
ba
s
ed
cro
s
s la
yer res
ou
rce
a
l
locatio
n
in
wi
r
el
ess n
et
work
(
Pravee
na T.
)
459
The
res
ource
m
anag
em
ent
and
the
al
l
ocati
on
are
ve
ry
diff
ic
ult
for
t
he
wireless
net
w
orks
w
her
e
the
sp
ect
ral
re
so
urces
a
re
prov
i
ded
by
se
ve
ral
us
e
rs.
I
n
the
la
ye
red
ne
tworki
ng
struc
ture,
e
ve
ry
la
ye
r
is
op
e
rated
a
s
we
ll
as
design
e
d
separ
at
el
y
[
6].
So
m
e
of
the
r
eso
ur
ce
al
locat
ion
sc
hem
es
e
m
plo
ye
d
fo
r
m
ob
il
e
com
m
un
ic
at
ion
s
yst
em
s
are
serv
ic
e
le
vel
a
gr
eem
ents
an
d
the
Q
oS
pa
ra
m
et
ers.
He
re,
the
QoS
par
a
m
et
ers
con
ta
ini
ng
ob
je
ct
ive
m
easur
es,
li
ke
tra
nsfer
delay
,
pack
et
loss
rati
o,
guar
anteed
bit
rate,
delay
va
riat
io
n
a
nd
so
on.
T
hus,
the
im
pr
oved
s
ubj
ect
ive
qual
it
y
per
ce
ptr
on
is
ve
ry
sig
nific
ant
to
the
pro
vi
der
s
f
or
m
ai
ntainin
g
and
incre
asi
ng
the
cu
stom
er
needs.
Howe
ve
r,
the
res
ourc
e
al
locat
ion
i
nc
lud
es
al
gorith
m
s
and
strat
eg
ie
s
in
order
to
c
on
tr
ol
the
par
am
et
er
s,
li
ke
channel
al
locat
ion
,
tra
nsm
it
po
we
r,
m
odulati
on
sc
he
m
e,
data
ra
te
s,
error
cod
i
ng
schem
e
and
so
on.
In
ge
ner
al
,
t
he
sche
du
li
ng
appr
oach
es
use
the
num
ber
of
hops,
tra
nsm
issi
on
distan
ce,
d
el
ay
, ch
a
nnel
con
di
ti
on
[8
]
.
Cros
s
-
la
ye
r
op
tim
iz
at
ion
is
br
oa
dly
util
iz
ed
fo
r
pro
vid
i
ng
QoS
pro
visio
ni
ng
in
wireles
s
m
ultim
edia
com
m
u
nicat
ion
[
9,
10
]
in
th
e
wireless
m
ul
tim
edia
com
mu
nicat
io
ns
[9,
10
]
.
The
cr
os
s
-
la
ye
r
sc
hem
e
works
with
co
nve
ntio
nal
net
work
m
od
el
t
o
im
pr
ove
the
syst
em
p
erfor
m
ance,
but
the
desig
n
pr
i
nciple
m
ay
cause
high
com
plexity
and
se
ver
al
op
tim
iz
at
ion
issues
[
9
,
1
1
]
.
Ac
cordin
gly,
the
eff
ic
ie
nt
cr
os
s
-
la
ye
r
te
chn
iq
ue
s
are
introd
uced
to
r
edu
ce
the
ad
diti
on
al
requeste
d
inf
or
m
at
ion
f
r
om
bo
th
t
he
pract
ic
al
and
t
he
theo
reti
cal
po
i
nt
of
view
[9
]
.
C
urr
ently
,
the
cr
oss
-
la
ye
r
arc
hitec
ture
is
de
sig
ne
d
to
im
pr
ove
the
syst
e
m
perform
ance
in
m
od
e
r
n
wireless
netw
orks,
a
nd
in
a
dd
it
io
n,
the
c
r
os
s
-
la
ye
r
i
nter
act
ion
patte
r
ns
are
sup
ported
with
prot
oc
ol
sta
ck
beyo
nd
3G
m
ob
il
e
c
omm
un
ic
at
ion
syst
em
s
[
12
-
1
3
]
.
I
n
[1
4
]
,
the
cr
os
s
-
la
ye
r
res
ource
al
loc
at
io
n
wa
s
est
ablished
b
y
consi
der
i
ng bo
th the d
at
a li
nk
lay
er and
t
he ph
ysi
cal
lay
er.
This
pa
pe
r
pre
sents
an
ap
pro
ach
f
or
cr
os
s
l
ay
er
res
ource
a
ll
ocati
on
based
on
SSC
A.
Here,
the
cr
os
s
-
la
ye
r
desi
gn
sha
res
t
he
in
f
or
m
at
ion
t
hroug
h
l
ay
er
bo
unda
ries
f
or
dete
rm
ini
ng
the
data
rec
ei
ves
from
the
othe
r
la
ye
rs.
He
nce,
the
cr
os
s
-
la
ye
r
desig
n
is
util
i
zed
f
or
sh
a
rin
g
the
sta
tus,
para
m
et
ers,
an
d
the
ot
her
i
nform
at
io
n
to
ot
her
f
our
la
ye
rs.
By
c
hangin
g
t
he
c
hannel
c
onditi
on
s
,
t
he
cr
os
s
-
la
ye
r
opti
m
izati
on
e
ntit
y
updates
the
decisi
on
on
the
basis
of
new
i
nput
data
.
In
t
his
case,
t
he
res
ource
al
l
ocati
on
strat
eg
y
is
per
f
or
m
ed
base
d
on
pro
pose
d
S
SCA,
w
hich
is
desi
gn
e
d
ne
w
ly
by
com
bin
ing
SS
D
a
nd
S
SA
.
Th
e
fitne
s
s
f
un
ct
io
n
f
or
best
resou
rce
al
loca
ti
on
is
evaluat
ed
on
the
basis
of
e
nergy
an
d
fairn
es
s.
T
he
fairn
e
ss
pa
ram
et
ers,
l
ike
m
ax
-
m
in
,
hard
-
fair
ness,
m
axi
m
u
m
thr
ough
pu
t,
pr
oport
ion
al
f
ai
rn
es
s, a
nd m
axi
m
u
m
thr
oughput are
consi
der
e
d.
The
m
ajo
r
c
on
t
rib
ution o
f
th
e
pap
e
r
is:
-
Propose
d
SSC
A
-
base
d
reso
urc
e
allocatio
n:
The
cr
os
s
-
l
ay
er
resour
ce
al
locat
ion
fra
m
ewo
r
k
nam
ed
SSCA
-
base
d
a
ll
ocati
on
is
pro
po
s
ed
f
or
al
loc
at
ing
t
he
resou
rces
e
ff
ect
ivel
y.
The
locat
io
n
of
sea
rc
h
a
ge
nts
is u
pd
at
e
d usin
g
the
f
it
nes
s fu
nction by c
onsi
der
i
ng f
ai
r
ness
and e
nergy.
The
pa
per
is
arr
a
ng
e
d
acco
rd
i
ng
to
f
ollo
wing
se
ries:
s
ect
ion
2
el
a
borates
e
xisti
ng
m
et
h
od
s
of
resou
rce
al
locat
ion
with
chall
eng
e
s
of
m
et
ho
ds
that
rem
ain
as
m
otivati
on
for
resea
rch.
The
syst
e
m
mo
del
of
resou
rce
al
locat
ion
is
portray
ed
in
sect
ion
3
and
the
dev
el
op
e
d
m
et
ho
d
of
res
ource
al
lo
cat
ion
is
exp
la
ined
in
sect
ion
4. Th
e
resu
lt
s
of the
m
e
tho
ds are
de
li
ber
at
ed
i
n
sec
ti
on
5.
At last
, se
ct
ion
6
c
oncl
ud
e
s the
work.
2.
MOTI
VA
TI
O
N
This
sect
ion
presents
the
li
te
ratur
e
s
urvey
of
se
ver
al
m
eth
ods
util
iz
ed
f
or
res
ource
al
locat
ion
a
nd
the ch
al
le
ng
es
of
the
e
xisti
ng
works ar
e
discuss
e
d.
2.1.
Li
tera
t
u
re sur
vey
Seve
ral
m
et
ho
ds
relat
ed
t
o
cr
os
s
la
ye
r
res
ou
rce
al
locat
io
n
t
echn
i
qu
e
s
are
descr
i
bed,
a
nd
analy
zed
as
fo
ll
ows
:
Ma
le
ki
an
d
Mi
r
j
al
il
y
[1
5
]
de
velo
pe
d
c
om
pr
ehe
nsi
ve
cr
os
s
-
la
ye
r
re
source
al
lo
cat
ion
a
ppr
oac
h
for
pro
vid
in
g fair
ne
ss,
r
o
bustness
and
balancin
g, an
d
the
thro
ughput m
axi
m
iz
a
ti
on
.
He
re,
th
e
powe
r
co
nsum
ptio
n
was
f
ound
be
tt
er,
but
othe
r
m
et
rics,
lik
e
m
ax
-
m
in
and
pro
portio
nal
fair
ne
ss
was
not
co
nsi
der
e
d.
Tsen
g
,
et
al
.
[
16
]
dev
el
oped
sing
le
-
in
pu
t
m
ul
ti
ple
-
ou
t
put
(S
IM
O)
t
hat
consi
der
the
a
ng
le
betwee
n
jamm
er
and
cha
nnel
ve
ct
or
i
n
the
ante
nn
a
s
patia
l
dom
ai
n.
A
fter
t
ha
t,
the
new
best
so
luti
on
for
a
n
t
i
-
j
a
m
m
i
n
g
c
r
o
s
s
l
a
y
e
r
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
w
a
s
d
e
r
i
v
e
d
.
H
e
r
e
,
p
e
a
k
s
i
g
n
a
l
-
to
-
n
o
i
s
e
r
a
t
i
o
(
P
S
N
R
)
w
a
s
i
m
pr
ov
e
d,
but
the
m
et
ho
d
fa
il
ed
t
o
consi
der
oth
e
r
al
go
rit
hm
s
fo
r
b
et
te
r
syst
e
m
per
f
or
m
ance.
Jung
,
et
al
.
[17
]
pr
es
ente
d
an
a
ppr
oach
was
introd
uced
for
the
wireless
vid
eo
tra
nsm
issi
on
.
He
re
,
two
m
et
rics
wer
e
co
ns
id
ered
f
or
m
ea
su
ri
ng
relat
ive
diff
e
r
ence
of
eac
h
forw
a
r
d
error
cor
recti
on
(FEC
)
blo
c
k
to
qu
al
it
y
of
use
r
exp
e
rience
.
Her
e,
the
com
pu
ta
ti
on
al
com
plexi
ty
was
gr
eat
ly
red
uce
d,
but
the
un
e
qu
al
err
or
protect
ion
(
UEP)
re
so
urce
al
locat
ion
are
no
t
co
ns
i
der
e
d
fo
r
hybri
d
aut
om
atic
rep
eat
request
tran
sm
issi
on
,
a
nd
m
ulti
cast
vid
e
o
pa
ckets.
Kordbac
he
h
,
et
al.
[18
]
em
plo
ye
d
ro
bu
st
cro
ss
la
ye
r
routing
a
nd
the
rad
i
o
re
so
urce
al
locat
ion
in
the
wireless
ad
-
hoc
netw
orks
.
In
this
case,
th
e
per
f
or
m
ance
gain
was
fou
nd
bette
r,
ho
we
ver,
the
op
ti
m
i
zat
ion
pro
blem
is still
dif
ficult
bec
au
se
of
non
-
co
nv
exity
.
Xu
,
et
al.
[19
]
pr
ese
nted
secur
it
y
-
based
energy
eff
ic
i
ent
f
or
m
ulti
-
ho
m
ing
net
w
orks.
Her
e
,
the
secur
it
y
-
e
na
bled
res
ource
al
locat
ion
wa
s
fo
rm
ulate
d
as
the
m
axi
m
izati
on
issue
of
dro
pp
i
ng
probabil
it
y,
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
11
, No
.
1,
Febr
uar
y
2021
:
458
-
470
460
pack
et
de
la
y,
and
the
a
vaila
bi
li
ty
of
powe
r
c
on
s
um
ption
.
T
he
m
e
tho
d
fail
ed
to
so
l
ve
the
m
ulti
-
eves
pro
blem
.
Senth
il
kum
ar
and
Me
e
naks
hi
[3
]
de
velo
ped
t
he
ap
proach
for
res
ource
al
locat
io
n
strat
egy
f
or
m
ulti
-
destinat
io
n
rel
ay
syst
e
m
s
in
the
cel
lular
do
wn
li
nk.
T
he
Q
oS
re
quirem
ents
util
iz
e
d
in
t
his
w
ork
is
m
i
nim
u
m
data
rate
re
quirem
ents,
m
axim
u
m
delay
thr
esh
old,
a
nd
t
he
zer
o
over
flow
s
.
Howe
ver,
the
m
et
ho
d
did
not
analy
ze
both
dow
nlink
an
d
upli
nk
pe
rfo
rm
a
n
ce.
X
u
a
nd
Zh
ua
ng
[
20
]
presente
d
cro
ss
-
la
ye
r
res
ource
al
locat
ion
f
or
the
het
eroge
ne
ou
s
wireless
ne
twork
.
Her
e
,
the
re
source
a
ll
ocati
on
was
su
bject
e
d
to
s
erv
ic
e
ou
ta
ge
pro
babi
li
t
y,
co
ns
trai
nts
in
delay
,
syst
em
rati
o
ba
ndwi
dth
,
and
the
total
powe
r
c
ons
um
pt
ion
.
The
e
nergy
ef
fici
ency
was
i
ncr
ease
d
in
t
hi
s
work,
but
the
cr
os
s
-
ti
er
inte
rf
e
re
nce
wa
s
no
t
c
onsider
ed
f
or
band
width
al
locat
ion
at
th
e
heter
oge
ne
ou
s
wireless
acc
ess.
Tse
ng
,
et
al.
[
21
]
pres
ented
an
ap
pr
oach
f
or
resou
rce
al
locat
ion
cr
os
sin
g
the
app
li
cat
io
n
an
d
physi
cal
la
ye
rs
fo
r
upl
ink
MU
-
MIM
O
OFDMA
sy
stem
s.
This
a
ppr
oac
h
achie
ves
bette
r
im
pr
ovem
e
nt
in
ave
ra
ge
pea
k
-
si
gnal
-
to
-
noise
-
rati
o
(
PSN
R
),
but
t
he
us
e
r
gro
up
i
ng w
as
no
t a
naly
zed
.
2.2
.
Chall
enges
The
c
halle
nge
that
has
bee
n
identifie
d
by
analy
zi
ng
t
he
pr
e
vious
c
ross
la
ye
r
res
ourc
e
al
locat
ion
te
chn
iq
ues
are
li
ste
d
be
lo
w.
-
The
c
halle
nges
face
d
by
cr
oss
-
la
ye
r
desig
n
is
the
c
oex
ist
e
nce
pro
blem
,
wh
ic
h
m
eans
it
is
ver
y
com
ple
x
for
integ
rati
ng
var
i
ou
s
c
r
os
s
-
l
ay
er
desig
ns
to
un
if
orm
,
becau
se
of
the
s
pec
ific
com
m
un
icati
on
sta
ndar
d
of
each c
ro
s
s
-
la
ye
r desig
n [
13
].
-
Anothe
r
chall
e
ng
e
fa
ced
by
cro
ss
la
ye
r
des
ign
is
ov
e
r
hea
d
cause
d
by
cr
os
s
la
ye
r
sign
a
li
ng
.
T
he
cro
s
s
-
la
ye
r
sh
a
red th
e inform
at
ion
a
m
on
g
the
node
s is v
e
ry c
om
pl
ex
a
nd ch
al
le
ngin
g [
13
].
-
Stand
a
r
dizat
ion
pr
ov
i
des
the
un
i
qu
e
ve
hicle
to
sm
oo
th
s
ever
al
c
ro
s
s
-
la
ye
r
desig
n
s
ol
u
ti
ons
in
m
obil
e
com
m
un
ic
at
ion
net
works,
but
the
sp
eci
ficat
ion
,
in
vestig
at
ion
,
dev
el
opm
ent,
and
t
he
sta
nd
a
rd
iz
at
io
n
of
cro
ss
-
la
ye
r
ent
it
ie
s
fail
ed
to
m
eet
the
req
ui
rem
ent
of
cro
s
s
-
la
ye
r
optim
i
zat
ion
s
as
wel
l
as
the
dyna
m
ic
interact
ion patt
ern
s
b
et
ween p
ro
t
o
col lay
ers
rem
ai
ns
open c
halle
ng
e
[
12
].
-
Un
li
ke
si
ng
le
-
carrier
netw
ork,
the
m
ulti
-
carrier
netw
ork
serv
es
var
i
ous
us
ers
at
the
par
ti
cular
ti
m
e;
therefo
re,
t
he m
ul
ti
-
carrier
sc
hedulin
g desig
n for the
bu
rsty t
raffic
is the
hec
ti
c chall
eng
e
[
6
].
-
In
[
15
]
,
Com
pr
e
he
ns
ive
cr
oss
-
la
ye
r
resou
r
ce
al
locat
ion
m
od
el
is
dev
i
sed
for
fau
lt
t
olera
nt
to
po
l
ogy
con
t
ro
l
i
n
t
he
wireless
m
esh
netw
orks.
H
er
e,
the
m
et
ho
d
fail
ed
to
c
on
si
der
the
fair
nes
s
an
d
t
he
e
ne
r
gy
m
od
el
tog
et
he
r
for
res
ource al
locat
ion
am
on
g
the
m
ulti
ple l
ay
ers.
3.
SY
STE
M MO
DEL
This
sect
io
n
pr
esents
the
syst
e
m
m
od
el
f
or
cro
ss
la
ye
r
res
ource
al
locat
io
n
in
CDM
A
-
ba
sed
wireless
as
-
hoc
netw
ork.
Let
us
c
onsider
the
ene
r
gy
co
ns
trai
ne
d
Cognit
ive
Ra
dio
or
t
hogonal
fr
e
qu
e
ncy
div
isi
on
m
ul
ti
ple
acce
ss
(CR
OFDMA)
with
M
com
m
un
ic
at
ing
pai
rs.
Here,
both
t
he
tra
ns
m
it
te
r
u
and
the
receive
r
v
are
represente
d
as
n
K
,
.
.
.
,
2
,
1
:
.
If
v
u
,
then
the
transm
issio
n
syst
em
is
c
on
si
der
e
d
as
the
tim
e
slott
ed
O
FD
M
A
syst
em
at
t
he
par
ti
cular
ti
m
e
interval
L
.
H
ere,
th
e
slot
s
ynch
ronizat
ion
is
at
ta
ined
usi
ng
beaconin
g
a
pp
ro
ac
h.
F
or
e
ve
r
y
tim
e
slot,
the
pa
rtic
ular
ti
m
e
inter
val
is
gi
ve
n
for
ac
hieving
sync
hro
nizat
ion
t
o
perform
sp
ect
ru
m
detect
ion
a
nd
r
eso
urce
al
locat
ion
.
H
ow
ever,
inter
-
ca
rri
er
interfere
nc
e
(I
CI
)
pro
du
c
ed
by
the
fr
e
qu
e
ncy
offset
of
side
lob
e
s
per
ta
ini
ng
to
the
trans
m
itter
u
.
In
the
ph
ysi
cal
la
ye
r,
the
fr
eq
ue
ncy
-
ba
s
e
d
Ra
yl
ei
gh
fa
ding
c
hannel
is
c
on
si
der
e
d
f
or
div
id
i
ng
w
hole
sp
ect
r
um
into
N
subcar
riers
for
gu
a
ra
nteei
ng
ever
y
s
ubcar
rier
by
e
xperie
nc
ing
Ra
yl
ei
gh
fad
i
ng.
T
he
s
ubcar
rier
set
pr
e
sent
in
t
ran
sm
i
tt
er
an
d
recei
ve
r
pai
r
u
is
de
note
d
a
s,
N
G
u
,
.
.
.
,
2
,
1
.
Let
us
c
ons
ider
u
l
v
u
G
l
M
v
u
H
H
,
,
,
:
,
,
wh
ic
h
r
epr
ese
nts
the
subca
rr
ie
r
f
adin
g
c
o
-
e
ff
ic
i
ent
m
at
rix,
where,
the
te
rm
l
v
u
H
,
de
no
te
s
t
he
s
ub
-
channel
c
oeffici
ent
gain
fro
m
u
to
v
at
the s
ub
ca
rr
ie
r
l
, and
is e
xpress
ed
as,
2
,
,
e
I
H
l
v
u
l
v
u
(1)
wh
e
re,
the
te
r
m
e
I
l
v
u
,
ref
e
r
to
the
trans
fer
functi
on.
He
re,
the
te
r
m
H
us
es
the
bl
oc
k
fa
ding
cha
nnel
of
siz
e
L
that
rem
ai
ns
inv
aria
nt
thr
oug
h
bl
ocks
an
d
t
he
unc
orrelat
ed
ove
r
su
cce
ss
ive
blo
c
ks.
Th
e
no
ise
c
onsid
ere
d
her
e
is
ad
diti
ve
wh
it
e
ga
us
si
an
noise
(
A
WG
N
)
with
the
var
ia
nce
2
,
l
u
at
receiver
u
ov
e
r
sub
carrier
l
.
The
n,
the
tra
ns
m
iss
ion
powe
r
a
ll
ocati
on
m
atr
ix
is
in
dicat
ed
as
u
l
u
l
u
G
l
K
u
q
q
Q
,
;
0
,
for
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
So
ci
al
-
sine
c
os
ine a
l
gorit
hm
-
ba
s
ed
cro
s
s la
yer res
ou
rce
a
l
locatio
n
in
wi
r
el
ess n
et
work
(
Pravee
na T.
)
461
the
entire
us
e
rs
in
K
ov
e
r
avail
a
ble
subcar
rier
set
u
K
u
G
V
,
wh
ere
t
he
te
r
m
l
u
q
de
no
te
s
the
power
al
lo
cat
ed
to s
ub
ca
rr
ie
r
at
tran
sm
it
te
r
u
. For ea
ch
transm
it
te
r,
the
powe
r
v
ect
or is
give
n by,
N
u
u
u
u
g
g
g
g
,.
..
,
,
:
2
1
(2)
The
e
ne
rg
y
c
onsu
m
ption
pe
r
inf
or
m
at
ion
r
at
e
to
ac
hieve
high
e
nergy
e
f
fici
ency
f
or
th
e
tran
sm
i
tt
er
receiver
pai
r
at
each
ti
m
e slot is de
no
te
d by,
u
u
G
l
l
u
G
l
s
u
l
u
u
u
u
a
g
g
a
g
E
:
,
(3)
wh
e
re,
the
te
r
m
l
u
a
ref
er
to
t
he
data
rate
of
th
l
subcar
rier.
T
he
powe
r
al
locat
e
d
over
th
l
su
bca
rr
ie
r
f
or
th
u
transm
itter is r
epr
ese
nted
as
l
u
g
, a
nd the te
rm
s
u
g
sign
i
fies the
rece
iving p
ower
.
4.
PROP
OSE
D RESO
URCE
ALLOC
ATIO
N ALGO
RIT
HM
This
sect
io
n
il
lustrate
s
the
pro
posed
SSCA
al
go
rit
hm
fo
r
resour
ce
al
l
oc
at
ion
in
wirele
ss
netw
ork.
The
c
ro
s
s
-
la
ye
r
opti
m
iz
at
ion
is
the
com
bin
at
ion
of
j
oi
nt
sche
du
li
ng
a
nd
res
ource
al
locat
ion
i
n
wi
reles
s
netw
ork
al
ong
with
m
edium
acce
ss
co
ntr
ol
(MAC)
,
ph
ysi
c
al
la
ye
r
an
d
th
e
ap
plica
ti
on
l
ay
er
are
i
nclu
de
d
in
the
un
ifie
d
cro
ss
-
la
ye
r
optim
iz
ation
.
He
re,
the
cr
os
s
-
la
ye
r
op
ti
m
izati
on
al
gorith
m
gets
que
ue
sta
te
inf
or
m
at
ion
(
QS
I
)
a
nd
c
ha
nn
el
sta
te
interfe
ren
ce
(CS
I)
f
r
om
MAC
and
ph
ysi
cal
la
ye
r.
Con
se
qu
e
ntly
,
the
oth
e
r
input
par
am
et
ers,
li
ke
energy
and
fa
irness
,
the
cr
oss
-
la
ye
r
optim
i
zat
ion
entit
y
m
akes
the
decisi
on
o
n
resou
rce
al
loca
ti
on
to
m
axi
m
i
ze
the
s
um
rate
of
net
wor
k.
By
var
yi
ng
the
cha
nn
el
c
ondi
ti
on
s,
t
he
c
ross
-
la
ye
r
op
ti
m
iz
ation
e
ntit
y
updates
the
decisi
on
bas
ed
on
ne
w
in
put
data.
Her
e
,
t
he
no
vel
res
ou
rce
al
locat
io
n
s
trat
egy
i
s
d
e
v
e
l
o
p
e
d
u
s
i
n
g
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
,
w
h
i
c
h
w
i
l
l
b
e
n
e
w
l
y
d
e
s
i
g
n
e
d
b
y
i
n
t
e
g
r
a
t
i
n
g
S
S
D
[
2
2
]
a
n
d
S
S
A
[
2
3
].
A
l
s
o
,
f
o
r
f
u
r
t
h
e
r
r
e
f
i
n
i
n
g
t
h
e
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
s
c
h
e
m
e
,
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
u
s
e
s
t
h
e
f
i
t
n
e
s
s
b
a
s
e
d
o
n
e
n
e
r
g
y
[
19
]
and
f
ai
r
ness
w
her
e
t
he
h
a
r
d
-
f
ai
rn
ess
,
pro
por
ti
on
al
fair
ness
,
m
ixed
-
bias
m
ax
-
m
in,
an
d
m
axim
u
m
thro
ughp
ut
is
con
sidere
d.
T
he
blo
c
k
dia
gr
a
m
of
the
pro
pose
d
S
SCA
-
ba
sed
res
ource
a
ll
ocati
on
i
n
th
e
wireless
net
work
is
sh
ow
n
in
Fi
gur
e
1.
Figure
1. Sc
he
m
at
ic
v
ie
w
of t
he
c
ro
s
s lay
er
r
eso
ur
ce al
lo
cat
ion
us
i
ng the
pro
posed
so
ci
al
-
sine
co
si
ne
al
go
rithm
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
11
, No
.
1,
Febr
uar
y
2021
:
458
-
470
462
4.1.
Cro
s
s la
yer
optimi
z
at
ion
Cros
s
-
la
ye
r
optim
iz
at
ion
m
od
el
co
ns
ist
s
of
di
ff
e
ren
t
la
y
ers
a
nd
di
ff
e
r
ent
pa
ram
et
ers.
T
he
th
ree
la
ye
rs
prese
nt
i
n
t
he
c
ro
s
s
-
la
ye
r
op
ti
m
iz
ation.
T
he
a
da
ptive m
od
ulati
on
a
nd
c
odin
g
(A
M
C)
a
nd
CSI
-
re
f
eren
c
e
sign
al
(CS
I
-
RS
)
feedbac
k
are
avail
able
i
n
ph
ysi
cal
layer,
w
her
eas
the
s
ub
carrier
assi
gnm
ent,
adap
ti
ve
power
con
t
ro
l,
a
ut
oma
ti
c
rep
eat
re
quest
(
ARQ
),
f
orwa
rd
er
ror
c
orrecti
on
(
FEC)
,
an
d
qu
al
it
y
of
ser
vice
in
the
MAC
la
ye
r
al
on
g
wit
h
the
ada
ptive
transm
issi
on
ra
te
in
the
network
la
ye
r.
I
n
tra
diti
o
nal
OSI,
the
stric
t
bounda
ries
are prese
nt am
ong
the lay
ers i
n
w
hich
the
da
ta
are
pro
vid
e
d
in the give
n partic
ula
r
la
ye
r
and
e
ve
ry lay
er g
i
ves
the
in
dep
e
nde
nt
so
l
utio
n
w
it
h
the
own
op
ti
m
iz
ed
ada
ptati
on
,
but
i
t
is
ver
y
c
om
plex
to
fu
l
f
il
l
all
the
re
quirem
en
ts,
li
ke
data
rat
e,
bit
e
rror
rat
e,
an
d
t
he
la
te
ncy
f
or
va
rio
us
ser
vices.
I
n
t
he
dynam
ic
wireless
netw
orks,
the
QSI
a
nd
CS
I
va
ry
wit
h
t
he
ti
m
e,
hen
c
e
the
netw
ork
node
a
da
pts
the
receptio
n
a
nd
the tra
ns
m
issi
o
n param
et
ers
to sati
sfy t
he power
constrai
nt
an
d
the
Q
oS
ne
eds [
5
,
24
]
.
4.2
.
Prop
os
ed
s
ocial
-
sine c
os
ine
algorithm
for
resource
a
ll
oc
at
i
on
The
pr
opos
e
d
SSCA
is
the
co
m
bin
at
ion
of
S
SD
with SSA.
The
SS
D
al
gor
it
h
m
is
insp
ired
by
va
rio
us
evo
l
ution
a
ry
optim
iz
at
ion
app
r
oac
hes
to
m
i
nim
iz
e
the
SV
Ms
par
am
et
er
s
with
the
aim
t
o
en
han
ce
the
syst
e
m
perform
ance.
The
m
ai
n
aim
of
SS
D
is
to
searc
h
in
the
sp
ace
f
or
op
ti
m
al
or
ne
ar
-
op
ti
m
al
so
l
utions.
This
m
et
ho
d
is
ver
y
e
ff
ic
ie
nt
for
gen
e
rati
ng
i
m
pr
oved
feat
ur
es
to
ta
c
kle
m
ul
ti
-
obj
ect
ive
optim
iz
at
ion
issues.
More
ov
e
r,
the
m
et
ho
d
can
so
lve
the
highly
non
-
li
nea
r
prob
le
m
s
wit
h
com
plex
co
ns
trai
nts
.
The
SC
A
al
gorithm
is
the
popula
ti
on
-
ba
sed
optim
iz
ati
on
an
d
t
her
e
is
no
gu
a
ra
ntee
f
or
fin
ding
t
he
so
luti
on
with
s
ing
l
e
run.
T
his
ap
proach
is
util
iz
e
d
f
or
c
reati
ng
var
io
us
rand
om
s
olu
ti
on
s
a
nd
fluctuate
th
e
m
towar
ds
th
e
bes
t
so
luti
on
base
d
on
sine
f
unct
ion
.
Her
e
,
vari
ou
s
ra
ndom
a
nd
a
dap
ti
ve
va
riables
are
c
om
bin
ed
in
or
der
to
e
m
ph
asi
ze
the
exp
l
oitat
ion
and
e
xplo
rati
on
of
the
sea
r
ch
sp
ac
e.
T
he
m
erit
s
of
the
al
go
rit
hm
ar
e
that
the
al
g
or
it
hm
ex
hib
it
s
bette
r
c
onve
rg
e
nc
e
sp
ee
d,
m
ini
m
al
err
or,
a
nd
m
ini
m
a
l
com
pu
ta
ti
on
al
tim
e.
Hen
ce
, in
te
gr
at
ing
SS
D
in
SSA
produces
b
et
te
r
so
l
ution wit
h
the
im
pr
ov
e
d sy
stem
p
erfo
r
m
ance.
The
de
velo
pe
d
SSCA
for
cr
oss
la
ye
r
reso
ur
ce
al
locat
ion
is
il
lustrate
d
in
t
his
sect
ion
.
T
he
pr
op
os
e
d
SSCA
is
the
c
om
bin
at
ion
of
SSD
[2
2
]
wit
h
SS
A
[
2
3
]
,
a
nd
t
hus
at
ta
ins
the
ad
va
ntage
s
of
SS
D
in
S
SA
.
The
SS
D
al
gorithm
is
insp
ir
ed
by
var
i
ou
s
ev
olu
ti
onary
op
ti
m
iz
ation
a
ppr
oach
es
to
m
ini
m
iz
e
the
SV
Ms
par
am
et
ers
wit
h
t
he
ai
m
to
enh
a
nce
the
syst
e
m
per
f
or
m
an
ce.
T
he
m
ai
n
a
i
m
of
S
SD
is
t
o
sea
rc
h
in
the
sp
ace
for
optim
al
o
r
near
-
opti
m
al
s
olu
ti
ons.
T
his m
et
ho
d
is ver
y
eff
ic
ie
nt f
or ge
ner
at
in
g
im
pr
ov
e
d
feat
ur
es t
o
ta
ckle
m
ul
ti
-
obj
ect
ive
op
ti
m
iz
a
ti
on
issues.
M
or
e
ov
er,
the
m
et
ho
d
can
so
l
ve
th
e
highly
non
-
li
near
pro
blem
s
with
com
plex
co
ns
trai
nts.
T
he
SC
A
al
gorithm
is
the
popula
ti
on
-
base
d
opti
m
i
zat
ion
a
nd
t
here
is
no
guara
nt
ee
for
fin
ding
the
s
olu
ti
on
with
sin
gle
run.
This
appr
oach
is
util
iz
ed
fo
r
c
rea
ti
ng
va
rio
us
ra
ndom
so
luti
ons
a
nd
fluctuate
t
hem
towa
rd
s
the
be
st
s
olu
ti
on
bas
ed
on
sine
fun
ct
ion
.
He
re,
va
rio
us
ra
ndom
and
ada
ptive
va
riables
are
com
bin
ed
in
orde
r
to
e
m
ph
asi
ze
the
exp
l
oitat
ion
a
nd
e
xplorati
on
of
the
sea
rch
sp
ace.
T
he
m
erit
s
of
the
al
gorithm
are
that
the
al
go
rithm
exh
ibit
s
bette
r
conve
rg
e
nce
spe
ed,
m
ini
m
al
err
or,
an
d
m
ini
m
al
com
pu
ta
ti
on
al
tim
e.
Hen
ce
,
integ
rati
ng
S
SD
i
n
SS
A
produces
bette
r
so
luti
on
with
the
im
pr
ov
e
d
syst
e
m
perform
ance.
The
a
dv
a
ntage
s
of
th
e
pro
pos
ed
m
et
ho
d
are
bette
r
co
nver
ge
nce
spe
ed
,
m
i
nim
a
l
err
or,
m
i
nim
a
l
com
pu
t
at
ion
ti
m
e and
it
pro
duces
bette
r
s
ol
ution wit
h t
he
im
pr
ov
e
d
syst
e
m
p
erf
orm
ance.
4.2.1
.
So
lu
tio
n
encodi
ng
The
s
olu
ti
on
e
ncodin
g
is
t
he
represe
ntati
on
that
is
ide
ntifie
d
with
the
de
ve
lop
e
d
m
od
el
.
Assum
e
d
nu
m
ber
of
t
r
ansm
itters
an
d
m
nu
m
ber
of
subcar
riers
f
ro
m
wh
ic
h
s
op
tim
al
so
luti
on
is
c
ho
se
n
by
the
dev
el
op
e
d
m
od
el
su
ch
th
at
s
value
rangin
g
from
b
s
1
,
res
pec
ti
vely
.
Her
e,
th
e
so
luti
on
requ
ires
for
decidin
g w
hi
ch
tran
sm
it
te
r
to b
e all
ocate
d
in
wh
ic
h
s
ubcar
rier.
4.2.2
.
Ob
jecti
ve
m
od
el
li
ng
The
fitnes
s
functi
on
is
eval
uated
in
order
to
ob
ta
in
the
bette
r
resu
lt
.
The
optim
al
so
luti
on
i
s
determ
ined
fro
m
the
pr
evio
us
it
erati
on
as
ea
ch
so
luti
on
to
ob
ta
in
the
bette
r
lo
cat
ion.
Th
e
obj
ect
ive
fun
ct
ion
of the
de
velo
pe
d
a
ppr
oach is
form
ulate
d
in t
erm
s o
f
e
nergy, and
fair
ness,
and
is e
xpresse
d by,
R
u
u
u
F
D
f
1
1
(4)
wh
e
re,
the
te
r
m
u
D
denotes
the
transm
i
tt
er
u
,
the
fairn
ess
is
rep
rese
nted
as
u
F
an
d
the
nu
m
ber
of
transm
itter is ind
ic
at
ed
as
R
.
a.
Fairnes
s
f
or
re
so
urce
al
locat
i
on
:
T
he
fai
rn
e
ss
par
am
et
ers,
li
ke
h
ar
d
-
fair
ne
ss
u
J
,
m
ax
-
m
in
fairn
ess
u
P
,
pro
port
ion
al
fa
irness
u
B
, m
ixed
-
bias
u
T
and the m
axim
u
m
thr
oughput
u
X
[2
5
]
are
gi
ven
belo
w,
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
So
ci
al
-
sine
c
os
ine a
l
gorit
hm
-
ba
s
ed
cro
s
s la
yer res
ou
rce
a
l
locatio
n
in
wi
r
el
ess n
et
work
(
Pravee
na T.
)
463
b.
Hard
-
fair
ness:
It
is
al
s
o
te
r
m
ed
as
rou
nd
r
ob
i
n
(RR)
-
ba
sed
res
ource
al
locat
ion.
It
is
util
iz
ed
f
or
al
locat
ing
tim
e
or
fr
e
quency
betwee
n
the
pote
ntial
cand
id
at
es
with
resp
e
ct
to
any
m
et
ri
c.
Si
m
ple
tim
e
div
isi
on
m
ultip
le
xing
(
TDM
)
is
the
best
exam
ple
fo
r
RR
scheduler
wh
e
re
eve
ry
node
is
gi
ven
as
the tim
e slot to
tran
sm
it
in
the
r
e
gu
la
r
inter
va
ls. Th
e
exp
ress
ion
f
or
ha
rd f
ai
rn
ess
is
denote
d
as
,
u
s
e
r
s
of
C
o
u
n
t
A
J
S
u
(5)
wh
e
re,
the ter
m
S
A
ind
ic
at
es the
m
axi
m
u
m
n
um
ber
o
f use
rs who e
qual
ly
shared
the
res
our
ces.
c.
Ma
x
-
m
in
fair
ne
ss:
In
Ma
x
-
m
in
fair
ness,
the
le
ss
num
ber
of
res
ource
s
al
locat
ed
to
eve
ry
no
d
e
i
s
increase
d.
I
n
ot
her
w
ords,
th
e
gap
is
m
inim
iz
ed
a
m
on
g
m
axi
m
u
m
and
m
ini
m
u
m
nu
m
ber
of
assigne
d
resou
rces to
ea
ch user
.
u
u
g
u
c
P
l
bu
m
i
n
m
a
x
(6)
wh
e
re,
the
tra
nsm
it
power
of
relay
helping
t
he
source
u
on
s
ub
ca
rr
ie
r
is
de
no
te
d
a
s
(
)
,
a
nd
the
data
rat
e
is represe
nted as
u
c
.
d.
Pr
op
or
ti
onal
f
ai
rn
ess:
It
im
plem
ents
t
i
m
e
-
ena
bled
fairness
and
pro
vid
es
the
go
od
tra
deoff
am
ong
fairn
e
ss
a
nd
ne
twork
th
rou
ghpu
t
with
res
pe
ct
to
m
ax
-
m
in
fairn
e
ss.
He
re,
the
nodes
with
th
e
lo
we
r
data
rate
ta
ke
m
or
e
tim
e
than
those
with
the
hi
gher
data
rates
,
wh
ic
h
le
ads
t
o
reduce
d
net
w
ork
th
rou
ghput
.
The pr
oport
io
na
l fairn
e
ss is e
xpresse
d
a
s,
h
u
B
1
(7)
wh
e
re,
t
he
te
r
m
rep
rese
nts
t
he
c
har
act
erist
ic
wh
ic
h
pri
ori
ty
is
assigne
d
to
0
,
an
d
the
pro
portio
nalit
y
factor i
s in
dica
te
d
as
h
,
0
h
.
e.
Mi
xed
-
bias:
Mi
xed
-
bias
ai
m
s
to
al
locat
e
the
portion
of
total
capaci
ty
avail
able
at
the
node
th
rou
gh
strongly
biase
d
poli
cy
,
and
rests
are
em
pl
oyed
as
the
fa
irer
poli
cy
.
Th
e
expressio
n
of
m
ixed
-
bias
is
giv
e
n by,
2
1
1
p
p
u
W
W
T
(8)
wh
e
re,
the ter
m
s
1
p
and
2
p
rep
rese
nts the
prop
or
ti
on
al
it
y fact
or,
0
,
2
1
p
p
and
0
.
f.
Ma
xim
u
m
thro
ug
hput:
It
is
con
ce
r
ned
onl
y
with
re
sourc
es
al
locat
ion
f
or
m
axim
iz
ing
the
th
rou
ghpu
t.
Her
e
, th
e
no
de t
hat trans
m
it
s m
or
e d
at
a,
gets
access to
r
es
ources
f
ir
st t
o o
btain
high s
um
-
thr
ough
pu
t.
4.2.3.
Algori
t
h
mi
c st
eps
of
the
dev
el
op
ed
S
SCA
-
b
as
e
d
allocati
on
The
pro
po
se
d
SSCA
is
desi
gned
by
inte
gr
a
ti
ng
SC
A
in
S
SD
.
He
re,
t
he
update
e
qu
at
io
n
of
SSD
is
m
od
ifie
d
us
in
g
the
up
date
equ
at
io
n
of
SC
A
al
gorithm
.
The
m
od
ific
at
ion
m
akes
the
so
luti
on
up
date
to
be
m
or
e
eff
ic
ie
nt,
and
it
fu
rthe
r
i
m
pr
oves
the
conve
rg
e
nce
of
the
op
ti
m
iz
a
ti
on
al
gorithm
.
T
he
ste
ps
f
ollo
wed
i
n
the d
e
velo
pe
d
al
gorithm
are
il
lustrate
d belo
w:
Step
1
:
I
niti
al
i
zat
ion
:
The
fir
st
ste
p
of
the
pro
po
se
d
S
SC
A
al
gorithm
is
the
init
ia
li
zat
i
on
of
the
posit
ion
of
search
a
ge
nts
in
w
hich,
t
he
total
nu
m
ber
of
a
gen
ts
a
re
identifie
d
by
the
us
e
r.
T
he
l
ocati
on
of
age
nts
is
represe
nted
as
,
z
X
t
v
1
;
(9)
wh
e
re
,
t
X
rep
rese
nts the
ag
e
nts
po
sit
io
n
at
ti
m
e
t
, and
t
he nu
m
ber o
f varia
bles are de
no
te
d
a
s
.
Step
2
:
O
bj
e
ct
ive
f
un
ct
io
n
e
valuati
on:
The
fitness
is
cal
culat
ed
f
or
ea
ch
s
olu
ti
on
on
the
basis
of
f
it
ness
functi
on
de
picte
d
in
(4).
T
he
fitness
f
unct
io
n
is
co
ns
ide
re
d
as
the
m
axim
iz
at
ion
functi
on
,
a
nd
s
olu
ti
on
wit
h
m
axi
m
u
m
f
it
ness
is co
ns
i
der
e
d
as
the
best s
ol
ution
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
11
, No
.
1,
Febr
uar
y
2021
:
458
-
470
464
Step
3
:
Update
the
so
luti
on
ba
sed
on
SSC
A
al
go
rithm
:
Af
te
r
evaluati
ng
the
obj
e
ct
ive
f
un
ct
io
n,
t
he
sol
ution
unde
rgoes p
os
i
ti
on
update
on
the b
a
sis o
f SS
CA.
T
he u
pd
at
e eq
uation o
f S
SD
velocit
y
t
k
is ex
pr
es
sed
as,
t
t
t
k
X
X
1
(10)
w
he
n
5
.
0
2
m
,
t
t
t
t
t
t
X
m
X
m
e
X
X
1
1
1
s
i
n
s
i
n
(11)
t
t
t
t
t
t
X
m
m
X
m
e
m
e
X
X
1
1
1
1
1
s
i
n
s
i
n
s
i
n
s
i
n
(12)
t
t
t
t
m
m
e
m
m
e
X
X
1
1
1
1
1
s
i
n
s
i
n
s
i
n
s
i
n
1
(13)
wh
e
re,
the
te
r
m
k
denotes
the
velocit
y
of
X
,
a
nd
the
un
if
orm
l
y
distrib
uted
ra
ndom
nu
m
ber
s
are
i
nd
ic
at
e
d
as
1
m
and
2
m
rangin
g
fr
om
0
t
o
1.
The
te
rm
repre
sents
the
best
so
luti
on
of
th
agen
t,
an
d
the
te
r
m
ind
ic
at
es
th
e
m
ean
gl
ob
al
s
olu
ti
on
for
w
hole
popula
ti
on
.
The
a
bove
e
quat
ion
s
hows
the
update
e
qu
at
ion
of
SSD,
w
hic
h
is
integ
rated
with
update
e
qu
at
ion
of
SCA
.
H
ence,
t
he
upda
te
equ
at
io
n
of
SCA
by
ta
king
the
conditi
on
5
.
0
4
Y
is ex
pr
ess
ed
b
y,
t
t
t
v
t
X
Y
Y
Y
X
X
3
2
1
1
s
i
n
(14)
a
ssu
m
e
t
t
X
I
,
t
t
t
v
t
X
Y
Y
Y
X
X
3
2
1
1
s
i
n
(15)
t
t
t
v
t
X
Y
Y
Y
Y
Y
X
X
2
1
2
3
1
1
s
i
n
s
i
n
(16)
t
t
v
t
Y
Y
Y
Y
Y
X
X
2
3
1
2
1
1
s
i
n
s
i
n
1
(17)
t
t
v
t
Y
Y
Y
X
Y
Y
X
2
3
1
1
2
1
s
i
n
s
i
n
1
1
(18)
w
h
e
r
e
,
t
h
e
t
e
r
m
r
e
p
r
e
s
e
n
t
s
t
h
e
l
o
c
a
t
i
o
n
o
f
c
u
r
r
e
n
t
s
o
l
u
t
i
o
n
a
t
ℎ
i
t
e
r
a
t
i
o
n
,
r
e
f
e
r
t
o
t
h
e
t
a
r
g
e
t
p
o
s
i
t
i
o
n
,
d
e
n
o
t
e
s
t
h
e
a
b
s
o
l
u
t
e
v
a
l
u
e
,
a
n
d
t
h
e
r
a
n
d
o
m
n
u
m
b
e
r
s
a
r
e
d
e
n
o
t
e
d
a
s
1
,
2
,
3
a
r
e
t
h
e
r
a
n
d
o
m
n
u
m
b
e
r
s
,
r
e
s
p
e
c
t
i
v
e
l
y
.
S
ubsti
tuti
ng (1
8) in
(13
),
t
t
t
t
v
t
m
m
e
m
m
e
Y
Y
Y
Y
Y
X
X
1
1
1
1
2
1
2
3
1
1
1
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
1
s
i
n
(19)
t
t
t
t
v
t
m
m
e
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
X
X
1
1
1
1
2
1
2
3
1
1
1
2
1
1
1
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
1
s
i
n
1
(20)
1
1
2
1
2
3
1
1
1
1
1
2
1
1
1
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
1
m
m
e
Y
Y
Y
Y
Y
m
m
e
m
m
e
Y
Y
X
X
t
t
t
t
v
t
(21)
1
1
2
1
2
3
1
1
1
2
1
1
1
1
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
s
i
n
1
1
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
m
m
e
X
t
t
t
t
(22)
1
1
2
1
2
3
1
1
1
2
1
1
1
2
1
1
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
s
i
n
1
s
i
n
1
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
m
m
e
Y
Y
X
t
t
t
t
(23)
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
So
ci
al
-
sine
c
os
ine a
l
gorit
hm
-
ba
s
ed
cro
s
s la
yer res
ou
rce
a
l
locatio
n
in
wi
r
el
ess n
et
work
(
Pravee
na T.
)
465
1
1
2
1
2
3
1
1
1
2
1
2
1
1
1
1
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
s
i
n
1
s
i
n
s
i
n
s
i
n
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
Y
Y
m
m
e
X
t
t
t
t
(24)
1
1
2
1
2
3
1
1
1
2
1
1
1
2
1
1
s
i
n
s
i
n
1
s
i
n
1
s
i
n
s
i
n
s
i
n
s
i
n
s
i
n
s
i
n
s
i
n
1
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
m
m
e
Y
Y
X
t
t
t
t
(25)
wh
e
re,
1
=
−
.
H
er
e,
the
te
rm
o
denotes
cu
rr
e
nt
it
erati
on,
Z
ref
er
to
the
m
axi
m
al
it
era
ti
ons
,
x
represe
nts the c
onsta
nt.
3
X
X
X
t
(26)
wh
e
re,
∅
,
,
de
note
s
the
th
ree
best
so
l
uti
ons,
an
d
re
pr
e
sents
the
b
est
s
olu
ti
on.
1
0
;
1
t
t
e
e
the v
al
ue of
2
1
,
m
m
ran
gi
ng fro
m
0
t
o 1
.
w
he
n
5
.
0
2
m
,
1
1
2
1
2
3
1
1
1
2
1
1
1
2
1
1
c
o
s
c
o
s
1
s
i
n
1
s
i
n
c
o
s
c
o
s
s
i
n
c
o
s
c
o
s
s
i
n
1
m
m
e
Y
Y
Y
Y
Y
m
m
e
Y
Y
m
m
e
Y
Y
X
t
t
t
t
(27)
The
te
rm
refe
rs
to
the
a
bili
ty
of
SSCA
for
bette
r
s
ol
ution.
T
he
ab
ov
e
e
qu
at
io
n
sp
eci
fies
the
update
d
eq
uation
of
t
he
pro
posed
S
SCA
,
wh
ic
h
in
tu
rn
us
ed
to
perf
orm
cro
ss
la
ye
r
resou
rce
al
locat
io
n
eff
ect
ively
.
Step
4
:
Com
pute
the
feasi
bili
t
y:
Af
te
r
e
valua
ti
ng
the
upda
te
d
po
sit
io
n,
t
he
obj
ect
ive
f
un
ct
ion
of
each
so
l
utio
n
is com
pu
te
d
a
nd
the
s
olu
ti
on
yi
el
din
g
m
axim
u
m
f
it
ness
is consi
der
e
d
as
best s
olu
ti
on.
Step
5
:
Term
inati
on
:
The
ste
ps
from
2
to
4
a
re
re
peated
un
t
il
the
sp
eci
fied
it
erati
on
m
et
o
r
the
be
st
so
lut
ion
is
ob
ta
ine
d. Al
gorithm
1
r
ep
rese
nts the
p
se
udo
cod
e
of
de
velo
ped
SSC
A
al
gorithm
.
Algori
th
m
1.
Pseudo c
od
e
of
the
dev
el
oped
SSCA
-
base
d al
locat
ion
Input: Position of search agents
z
X
t
1
;
Output: Best position
Procedure:
Begin
Initialize the agent’s position and velocities
Assume the fitn
ess function is minimum
While the stopping criteria are failed to met do
For all agents do
Calculate the fitness function using equation (4)
Arranged the agents using fitness value
Compute the mean global solution and previous best solution
Update th
e agent’s location using equation (27)
End if
End for
Check the feasibility of the solutions
Return the best solution
1
t
t
End while
Optimal solution is obtained
End
5.
RESU
LT
S
A
ND
DI
SCUS
S
ION
S
The
a
naly
sis
of
c
ross
-
la
ye
r
resou
rce
al
locat
ionusi
ng
t
he
pr
opos
e
d
SSCA
-
base
d
al
locat
ion
i
s
el
aborated i
n
t
his secti
on to
prove t
he
ef
fecti
ven
e
ss
of the
pro
posed
m
od
el
.
5.1
.
Experim
en
ta
l
set
-
up
The
pro
posed
m
et
ho
d
is
e
xe
cuted
in
4GB
RAM,
W
i
ndows
8
OS
with
In
te
l
c
or
e
i
-
3
process
or
an
d
the im
ple
m
ent
at
ion
is
done
in
MATL
AB.
5.2.
Eva
lu
at
i
on
m
etrics
T
h
e
p
e
r
f
o
r
m
a
n
c
e
r
e
v
e
a
l
e
d
b
y
t
h
e
d
e
v
e
l
o
p
e
d
a
p
p
r
o
a
c
h
i
s
e
v
a
l
u
a
t
e
d
u
s
i
n
g
e
n
e
r
g
y
,
t
h
r
o
u
g
h
p
u
t
a
n
d
t
h
e
f
a
i
r
n
e
s
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
11
, No
.
1,
Febr
uar
y
2021
:
458
-
470
466
5.3.
Co
m
pa
r
ati
ve m
eth
od
s
The
pe
rfor
m
ance
increased
by
the
dev
el
ope
d
m
e
tho
d
is
ev
al
uated
by
c
om
par
ing
the
propos
e
d
wit
h
existi
ng
m
et
ho
ds
,
li
ke
w
at
erfi
ll
ing
m
et
ho
d
[
1
6
]
,
Sec
ur
it
y
a
war
e
ene
rg
y
ef
fici
ent
al
locat
ion
[
19
]
,
dist
ribu
te
d
energy ef
fici
en
t al
locat
ion
[2
4
]
, r
es
pecti
vely
.
5.3.1
.
Analysis
ba
sed
on n
um
ber of
users
Figure
2
s
how
s
the
c
om
par
at
iv
e
of
t
he
devel
op
e
d
S
SCA
-
base
d
al
locat
io
n
with
resp
ect
to
e
nergy
,
thr
oughput
an
d
the
fair
ness
with
resp
ect
to
us
ers.
Fi
gure
2
(
a
)
repre
sents
the
com
par
at
ive
a
naly
sis
of
the
pro
pose
d
S
SCA
-
base
d
al
locat
ion
in
te
rm
s
of
ene
rg
y.
Wh
en
t
he
c
ount
of
us
e
r
is
2,
th
e
energy
ob
ta
i
ned
by
the
existi
ng
w
at
erf
il
li
ng
m
eth
od,
S
ecu
rity
awar
e
e
nergy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distri
bu
te
d
ene
rg
y
e
ff
ic
ie
nt
al
locat
ion
is
3294
3W,
3315
7W,
an
d
31
168W,
w
hile
the
pro
po
se
d
SSC
A
-
base
d
al
locat
ion
obta
ine
d
bette
r
energy
of
3
21
73,
res
pecti
ve
ly
.
Wh
e
n
the
co
unt
of
use
r
is
6,
the
energy
obta
ined
by
the
pr
opos
e
d
SSC
A
-
base
d
al
locat
ion
is
3829
3W,
w
hile
the
pe
rcen
ta
ge
of
im
pr
ovem
e
nt
re
ported
by
the
pro
posed
m
et
ho
d
in
c
ompari
s
on
with
the
exiti
ng
w
at
erf
il
li
ng
m
e
tho
d,
an
d
secu
rity
awar
e
energy
effi
ci
en
t
al
locat
i
on,
distrib
uted
ener
gy
eff
ic
ie
nt all
oca
ti
on
is
3567
8W,
3792
0W, a
nd 33
999W,
re
sp
ect
ively
.
Figure
2
(
b)
re
pr
ese
nts
the
c
om
par
at
ive
analy
sis
of
the
pro
po
s
ed
S
SCA
-
ba
sed
al
locat
io
n
in
te
rm
s
of
thr
oughput
by
var
yi
ng
the
us
ers
.
Wh
e
n
the
co
un
t
of
use
r
is
6,
the
thr
ough
pu
t
obt
ai
ned
by
the
existi
ng
w
at
erf
il
li
ng
m
et
hod,
Secu
rity
awar
e
ene
r
gy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distribu
te
d
e
nergy
e
ff
ic
ie
nt
al
locat
ion
is
3
.
2
1
3
m
b
p
s
,
3
.
2
4
1
m
b
p
s
,
a
n
d
3
.
2
4
7
m
b
p
s
,
w
h
i
l
e
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
-
b
a
s
e
d
a
l
l
o
c
a
t
i
o
n
o
b
t
a
i
n
e
d
b
e
t
t
e
r
thr
ough
p
ut
of
3.292m
bp
s,
res
pecti
vely
.
Wh
e
n
the
c
ount
of
us
er
is
8,
the
t
hro
ughput
ob
ta
ined
by
the
pr
opos
e
d
S
SCA
-
base
d
al
locat
ion
is
3.445m
bp
s,
w
hile
the
pe
rce
ntage
of
im
pr
ov
em
ent
re
ported
by
the
pro
posed
m
et
ho
d
i
n
c
o
m
p
a
r
i
s
o
n
w
i
t
h
t
h
e
e
x
i
t
i
n
g
w
at
erf
il
li
ng
m
e
t
h
o
d
,
S
e
c
u
r
i
t
y
a
w
a
r
e
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
,
a
n
d
d
i
s
t
r
i
b
u
t
e
d
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
i
s
3
.
3
2
0
m
b
p
s
,
3
.
3
9
2
m
b
p
s
,
a
n
d
3
.
4
1
4
m
b
p
s
,
r
e
s
p
e
c
t
i
v
e
l
y
.
W
h
e
n
t
h
e
n
u
m
b
e
r
o
f
u
s
e
r
i
s
1
0
,
t
h
e
t
h
r
o
u
g
h
p
u
t
o
b
t
a
i
n
e
d
b
y
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
-
b
a
s
e
d
a
l
l
o
c
a
t
i
o
n
i
s
3
.
6
0
8
m
b
p
s
,
w
h
i
l
e
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
i
m
pr
ovem
ent
rep
ort
ed
by
the
pro
po
se
d
m
et
ho
d
in
c
om
par
ison
with
the
exi
ti
ng
w
at
er
fill
ing
m
e
tho
d,
Sec
ur
it
y
awar
e
ene
r
gy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distri
bu
te
d
e
nergy
e
ff
ic
ie
nt
al
locat
ion
is
3.3
96m
bp
s
,
3.5
40
m
bps,
a
nd
3.577m
bp
s,
r
es
pecti
vely
.
Figure
2
(
c
)
re
presents
t
he
co
m
par
at
ive
analy
sis
of
the
pro
po
s
ed
SSCA
-
ba
sed
al
locat
io
n
in
te
rm
s
of
fairn
e
ss
by
vary
ing
t
he
us
er
s.
Wh
e
n
the
c
ount
of
us
e
r
is
6,
the
fair
ness
obta
ined
by
the
existi
ng
w
at
e
rfi
ll
ing
m
e
t
h
o
d
,
S
e
c
u
r
i
t
y
a
w
a
r
e
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
,
a
n
d
d
i
s
t
r
i
b
u
t
e
d
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
i
s
0
.
7
6
0
,
0
.
7
7
0
,
a
n
d
0
.
7
8
8
,
w
h
i
l
e
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
-
b
a
s
e
d
a
l
l
o
c
a
t
i
o
n
o
b
t
a
i
n
e
d
b
e
t
t
e
r
f
a
i
r
n
e
s
s
o
f
0
.
8
4
9
,
r
e
s
p
e
c
t
i
v
e
l
y
.
W
h
e
n
the
co
un
t
of
us
e
r
is
8,
t
he
f
ai
rn
e
ss
obta
ined
by
the
existi
ng
w
at
er
fill
ing
m
et
ho
d,
S
ec
ur
it
y
aw
are
e
nergy
ef
f
ic
ie
nt
al
locat
ion
,
a
nd
distribu
te
d
en
erg
y
ef
fici
ent
al
locat
ion
is
0.776,
0.855,
a
nd
0.8
60,
w
hile
the
propose
d
SSCA
-
base
d
al
locat
ion
obta
ined
bette
r
fairn
ess
of
0.861,
re
sp
ect
i
vely
.
W
he
n
th
e
count
of
us
e
r
is
10
,
the
fai
rn
es
s
ob
ta
ine
d
by
t
he
e
xisti
ng
w
at
erf
il
li
ng
m
eth
od,
secu
rity
awar
e
e
ne
rg
y
eff
ic
ie
nt
al
loc
at
ion
,
a
nd
dist
rib
uted
energy
ef
fici
en
t
al
locat
ion
is
0.805,
0.8
63,
and
0.8
66,
w
hi
le
the
pro
pose
d
S
SCA
-
ba
sed
al
locat
ion
obt
ai
ned
bette
r
fai
rn
e
ss
of 0.8
68, res
pe
ct
ively
.
5.3.2
.
Anal
ys
is
ba
se
d
on
tr
ansmi
tt
ers
Figure
3
s
ho
ws
t
he
c
om
par
at
ive
of
the
dev
el
op
e
d
SS
CA
-
base
d
al
lo
cat
ion
i
n
te
rm
s
of
e
nergy,
thr
oughput
a
nd
the
fai
rn
es
s
with
resp
ect
to
transm
it
te
rs.
Figure
3
(
a
)
re
pr
ese
nts
t
he
c
om
par
at
ive
an
al
ysi
s
of
the
pro
po
s
ed
SSCA
-
base
d
a
ll
oca
ti
on
in
te
rm
s
of
energy.
W
he
n
the
c
ount
of
tra
ns
m
i
tt
er
is
5,
the
energy
ob
ta
ine
d
by
t
he
existi
ng
w
at
erf
il
li
ng
m
et
h
od,
S
ecu
rity
awar
e
ene
r
gy
e
ff
ic
ie
nt
al
locat
ion
,
a
nd
distri
bu
te
d
energy
ef
fici
ent
al
locat
io
n
is
3333
6W,
31604W,
a
nd
31420W,
w
hile
the
propose
d
S
SCA
-
base
d
al
l
ocati
on
ob
ta
ine
d
bette
r
energy
of
31709W,
res
pecti
ve
ly
.
W
he
n
th
e
count
of
tra
nsm
itter
is
20,
th
e
energy
ob
ta
i
ned
by
the
pro
po
se
d
SSCA
-
base
d
al
locat
ion
is
39110W,
wh
il
e
the
per
ce
ntage
of
i
m
pr
ovem
ent
rep
ort
ed
by
the
pro
posed
m
et
ho
d
in
c
omparis
on
with
th
e
exiti
ng
w
at
er
fill
ing
m
et
ho
d,
and
Secu
rity
awar
e
e
nergy
ef
fici
ent
al
locat
ion
,
d
ist
rib
uted
e
nergy
eff
ic
ie
nt all
oca
ti
on
is
3582
3W,
3866
2W, a
nd 39
557W,
re
sp
ect
ively
.
Figure
3
(
b)
re
pr
ese
nts
the
c
om
par
at
ive
analy
sis
of
the
pro
po
s
ed
S
SCA
-
ba
sed
al
locat
io
n
in
te
rm
s
of
thr
oughput
by
var
yi
ng
the
t
ran
sm
it
te
rs.
Wh
en
the
c
ount
of
transm
it
te
r
is
10
,
the
thr
oughput
obta
ined
by
the
existi
ng
w
at
erf
il
li
ng
m
eth
od,
S
ecu
rity
awar
e
e
nergy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distri
bu
te
d
ene
rg
y
e
ff
ic
ie
nt
al
locat
ion
is
3.019m
bp
s,
3.0
39m
bp
s,
a
nd
3.
134m
bp
s,
w
hile
the
pr
opos
e
d
SSCA
-
ba
sed
al
locat
ion
ob
ta
ined
bette
r
thr
ough
pu
t
of
3.2
18m
bp
s
,
res
pecti
ve
ly
.
Wh
en
t
he
count
of
transm
it
te
r
is
15
,
the
thr
oughput
obta
ine
d
by
the
pro
pos
ed
SSC
A
-
base
d
al
locat
ion
is
3.265m
bp
s,
wh
il
e
the
pe
rc
entage
of
im
pr
ovem
ent
rep
ort
ed
by
the
pro
posed
m
et
ho
d
in
co
m
par
ison
with
the
exiti
ng
w
at
erf
il
li
ng
m
eth
od,
Secu
rity
awar
e
e
nergy
eff
ic
ie
nt
al
locat
ion
,
a
nd
distrib
uted
e
ne
rg
y
ef
fici
ent
a
ll
ocati
on
is
3.0
97
m
bp
s
,
3.1
57
m
bp
s,
an
d
3.2
08m
bp
s,
re
sp
ect
ively
.
Wh
e
n
the
num
b
er
of
transm
itter
is
25
,
the
thr
ough
pu
t
obta
ined
by
the
pro
posed
S
SCA
-
base
d
al
locat
ion
i
s
3.609
m
bp
s,
wh
il
e
the
pe
rc
entage
of
im
pr
ovem
ent
rep
ort
ed
by
the
propose
d
m
et
ho
d
in
com
par
is
on
with
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
So
ci
al
-
sine
c
os
ine a
l
gorit
hm
-
ba
s
ed
cro
s
s la
yer res
ou
rce
a
l
locatio
n
in
wi
r
el
ess n
et
work
(
Pravee
na T.
)
467
the
e
xiti
ng
w
a
te
rf
il
li
ng
m
et
ho
d,
Sec
uri
ty
awar
e
ene
r
gy
e
ff
ic
ie
nt
a
ll
ocat
ion
,
an
d
distri
bu
te
d
e
nergy
e
ff
ic
ie
nt
al
locat
ion
is
3.444m
bp
s,
3.49
7m
bp
s,
a
nd
3.5
57
m
bp
s
, r
e
sp
e
ct
ively
.
Figure
3
(
c
)
re
presents
t
he
co
m
par
at
ive
analy
sis
of
the
pro
po
s
ed
SSCA
-
ba
sed
al
locat
io
n
in
te
rm
s
of
fairn
e
ss
by
va
r
yi
ng
the
tra
nsm
itters.
Wh
en
the
co
un
t
of
tra
ns
m
itter
is
15
,
the
fair
ness
obt
ai
ned
by
the
ex
ist
ing
w
at
erf
il
li
ng
m
e
t
h
o
d
,
S
e
c
u
r
i
t
y
a
w
a
r
e
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
,
a
n
d
d
i
s
t
r
i
b
u
t
e
d
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
i
s
0
.
7
8
5
,
0
.
8
0
3
,
a
n
d
0
.
8
0
9
,
w
h
i
l
e
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
-
b
a
s
e
d
a
l
l
o
c
a
t
i
o
n
o
b
t
a
i
n
e
d
b
e
t
t
e
r
f
a
i
r
n
e
s
s
o
f
0
.
8
1
1
.
W
h
e
n
t
he
c
ou
nt
of
transm
itter
is
20,
the
fai
rn
es
s
obta
ine
d
by
the
existi
ng
w
at
erf
il
li
ng
m
eth
od,
Sec
ur
it
y
awar
e
ene
rg
y
eff
ic
ie
nt
a
l
l
o
c
a
t
i
o
n
,
a
n
d
d
i
s
t
r
i
b
u
t
e
d
e
n
e
r
g
y
e
f
f
i
c
i
e
n
t
a
l
l
o
c
a
t
i
o
n
i
s
0
.
7
9
5
,
0
.
8
1
1
,
a
n
d
0
.
8
1
2
,
w
h
i
l
e
t
h
e
d
e
v
e
l
o
p
e
d
m
o
d
e
l
o
b
t
a
i
n
e
d
f
a
i
r
n
e
s
s
o
f
0
.
8
1
8
,
r
e
s
p
e
c
t
i
v
e
l
y
.
W
h
e
n
t
h
e
c
o
u
n
t
o
f
t
r
a
n
s
m
i
t
t
e
r
i
s
2
5
,
t
h
e
f
a
i
r
n
e
s
s
o
b
t
a
i
n
e
d
b
y
t
h
e
exi
sti
ng
w
at
erf
il
li
ng
m
et
hod,
Sec
uri
ty
awar
e
e
nergy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distri
bu
te
d
ene
r
gy
eff
ic
ie
nt
al
locat
ion
is
0.824, 0
.83
7,
a
nd 0.85
5,
w
hile t
he devel
ope
d
S
SCA
-
base
d al
locat
ion
obta
ined fai
r
ness o
f 0.
868.
(a)
(b)
(c)
Figure
2. Com
par
at
ive
analy
s
is of the
de
velo
ped m
et
ho
d,
a)
en
e
rg
y,
b) th
r
oughput, c
) fai
rn
ess
(a)
(b)
(c)
Figure
3. Com
par
at
ive
analy
s
is of the
de
v
el
oped
m
et
ho
d,
a)
en
e
rg
y,
b) th
r
oughput, c
) fai
rn
ess
5.3.3
.
Analysis
ba
se
d
on
sub
carrie
rs
Figure
4
il
lustr
at
es
the
com
par
at
ive
of
the
de
velo
ped
SSC
A
-
base
d
al
locat
i
on
with
res
pec
t
to
ene
rg
y,
thr
oughput
a
nd
the
fai
rn
es
s
with
resp
ect
to
subcar
riers
.
F
igure
4
(
a
)
repr
esents
the
c
omparati
ve
analy
sis
of
the
propose
d
SSCA
-
base
d
a
ll
ocati
on
i
n
te
rm
s
of
e
nergy.
Wh
e
n
the
c
ount
of
s
ubcar
r
ie
r
is
16,
t
he
energy
ob
ta
ine
d
by
t
he
existi
ng
w
at
erf
il
li
ng
m
et
h
od,
S
ecu
rity
awar
e
ene
r
gy
e
ff
ic
ie
nt
al
locat
ion
,
a
nd
distri
bu
te
d
ene
r
gy
ef
fici
ent
al
locat
io
n
is
2120
0W,
18025W,
a
nd
18433W,
w
hile
the
propose
d
S
SCA
-
base
d
al
l
ocati
on
ob
ta
ine
d
b
e
t
t
e
r
e
n
e
r
g
y
o
f
2
2
0
9
8
W
,
r
e
s
p
e
c
t
i
v
e
l
y
.
W
h
e
n
t
h
e
c
o
u
n
t
o
f
s
u
b
c
a
r
r
i
e
r
i
s
1
2
8
,
t
h
e
e
n
e
r
g
y
o
b
t
a
i
n
e
d
b
y
t
h
e
p
r
o
p
o
s
e
d
S
S
C
A
-
b
a
s
e
d
a
l
l
o
c
a
t
i
o
n
i
s
1
3
4
3
7
7
W
,
w
h
i
l
e
t
h
e
p
e
r
c
e
n
t
a
g
e
o
f
i
m
p
r
o
v
e
m
e
n
t
r
e
p
o
r
t
e
d
b
y
the
pro
posed
m
et
ho
d
in
co
m
par
ison
with
the
exiti
ng
w
at
erf
il
li
ng
m
eth
od,
a
nd
Sec
uri
ty
awar
e
ene
rg
y
eff
ic
ie
nt
al
locat
ion
,
distrib
uted ene
rg
y e
ff
ic
ie
nt al
locat
ion
is
12
9883
W,
1252
26W,
a
nd
127958
W,
res
pecti
vel
y.
Figu
re
4
(
b)
re
pr
ese
nts
the
c
om
par
at
ive
analy
sis
of
the
pro
po
s
ed
S
SCA
-
ba
sed
al
locat
io
n
in
te
rm
s
of
thr
oughput
by
var
yi
ng
t
he
s
ub
ca
rr
ie
rs.
W
hen
the
c
ount
of
subca
rr
ie
r
is
32,
the
thr
oughput
ob
ta
i
ned
by
the
existi
ng
w
at
erf
il
li
ng
m
eth
od,
S
ecu
rity
awar
e
e
nergy
eff
ic
ie
nt
al
loca
ti
on
,
a
nd
distri
bu
te
d
ene
rg
y
e
ff
ic
ie
nt
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