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.
10
,
No.
3
,
June
2020,
pp. 3
200~
3207
IS
S
N:
20
88
-
8708
,
DOI: 10
.11
591/
ijece
.
v10
i
3
.
pp3200
-
32
07
3200
Journ
al h
om
e
page
:
http:
//
ij
ece.i
aesc
or
e.c
om/i
nd
ex
.ph
p/IJ
ECE
Stu
dy of
the
o
pe
ration
al S
NR whil
e constr
ucting
p
olar
c
odes
Red
a
Be
nk
houy
a
1
,
I
driss
C
ha
n
a
2
,
Y
ou
sse
f
H
ad
i
3
1,
3
MIS
C,
Facul
t
y
of
Sci
ences,
Ibn
Tofail
Univer
sit
y
,
Moroc
co
2
ISIC E
ST
-
LM
MI E
NS
AM
,
Moula
y
Ism
ai
l
Uni
ver
sit
y
,
Morocc
o
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Ma
y
30
, 201
9
Re
vised
Dec
14
,
20
19
Accepte
d
J
an
8
, 2020
Channe
l
cod
ing
is
comm
only
base
d
on
prote
c
ti
ng
informa
ti
on
to
be
comm
unic
at
ed
ac
ross
an
unre
liable
m
edi
um
,
b
y
addi
ng
pat
t
ern
s
of
red
undancy
int
o
the
tra
nsm
ission
pat
h
.
Also
re
fer
red
to
as
for
ward
err
o
r
cont
rol
codi
ng
(
FECC),
the
tech
nique
is
wide
l
y
used
to
ena
b
le
c
orre
cting
or
at
l
ea
st
d
etec
t
in
g
bit
err
ors
in
d
ig
it
a
l
comm
unicati
on
s
y
stems
.
I
n
thi
s
pap
er
we
stud
y
an
origi
nal
FECC
known
as
pola
r
codi
ng
which
has
pro
ven
to
m
ee
t
the
t
y
p
ic
a
l
use
ca
ses
of
th
e
nex
t
gene
r
at
ion
m
obil
e
st
anda
rd
.
T
his
work
is
m
oti
vat
ed
b
y
th
e
suita
b
il
i
t
y
of
p
ola
r
cod
es
for
th
e
new
coming
w
ir
eless
era.
Henc
e,
we
inves
ti
gat
e
th
e
per
fo
rm
anc
e
of
pola
r
code
s
in
te
rm
s
of
bit
err
or
rat
e
(BER)
for
s
eve
ra
l
code
word
le
ngths
and
cod
e
rat
es
.
W
e
first
per
form
a
discre
t
e
sea
rch
t
o
find
the
best
o
per
ati
o
n
al
signa
l
-
to
-
noise
ratio
(
SN
R)
at
two
diffe
ren
t
code
r
a
te
s,
whi
le
var
y
in
g
the
bloc
k
le
ng
t
h.
W
e
f
ind
in
ou
r
extensive
sim
ula
ti
ons
tha
t
the
BER
bec
om
es
m
ore
sensiti
ve
to
oper
ational
SN
R
(OS
NR)
as
long
as
we
inc
r
eas
e
the
bloc
k
le
n
gth
and
code
r
at
e
.
Fina
lly
,
we
no
te
th
at
increa
sing
b
loc
kl
en
gth
a
chi
ev
es
an
SN
R
gai
n,
whi
le
inc
r
ea
sing
code
ra
te
ch
anges
the
OS
NR
do
m
ai
n.
Thi
s
tra
d
e
-
off
sorted
out
m
ust
be
ta
ken
int
o
conside
r
at
i
on
while
designi
ng
pola
r
c
odes
for
high
-
throughput
appl
i
ca
t
ion.
Ke
yw
or
d
s
:
Bhatt
acharyy
a
p
aram
et
er
Po
la
r
codes
SN
R
Su
ccessi
ve
ca
nc
el
la
ti
on
decodin
g
Copyright
©
202
0
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed
.
Corres
pond
in
g
Aut
h
or
:
Re
da
Be
nk
houy
a,
MISC, Fa
culty
of S
ci
e
nces,
Ibn
T
ofai
l U
niv
ersit
y,
Av.
de
L'
Un
i
ve
rsité
, K
é
nitra,
Morocc
o
.
Em
a
il
: red
a.b
e
nkhouya
@g
m
ai
l.com
1.
INTROD
U
CTION
O
ve
r
la
st
ye
ars,
wireless
ap
plica
ti
on
s
ha
ve
be
en
gro
wing
fa
st
and
re
qu
i
rin
g
m
or
e
chall
eng
in
g
co
di
ng
schem
es.
Re
ce
ntly
,
po
la
r
co
de
s
wer
e
pro
ve
n
to
be
capaci
ty
achievin
g
f
or
bi
nar
y
discrete
m
e
m
or
yl
ess
chan
nel
(B
-
DMC
).
Co
m
bin
ed
with
hi
gh
or
der
m
odulati
on
,
pola
r
cod
e
is
po
werf
ul
cand
i
date
for
the
ne
xt
generati
on
m
ob
il
e
sta
nd
ard,
w
her
e
high
tra
ns
m
issi
on
power
ef
fici
ency
an
d
ba
nd
width
e
ff
ic
ie
nc
y
are
require
d
[
1].
Fo
rt
unat
el
y,
both
po
la
r
e
ncodi
ng
a
nd
dec
oding
are
of
lo
w
com
plexity
,
so
need
m
ini
m
u
m
tim
e
and
sp
ac
e,
and
this
m
at
ch
gr
ee
n
ene
rg
y
re
quir
e
m
ent
[2
]
.
The
per
f
orm
ance
of
pola
r
co
des
e
nab
le
s
thei
r
ap
plica
ti
on
in
va
r
yi
ng
channels,
wh
ic
h
ta
ckles
the
unive
rsal
cov
e
ra
ge
re
qu
irem
ent.
On
the
oth
er
side,
com
plex
us
e
scena
rios
r
esult
in h
et
er
oge
neous netw
orks w
her
e
pola
r
c
od
es can fin
d
thei
r
s
uitable
appli
cat
ion
s. The
refor
e
, th
ese
co
de
s h
a
ve
beco
m
e
on
e
popula
r
to
pic
an
d
dr
a
w
n
intens
ive
at
te
ntion
s
f
ro
m
bo
th
acad
e
m
ia
and
ind
ust
ry.
Re
cent
r
esear
c
h
pro
gr
esses
on
po
la
r
c
od
e
s
ca
n
be
m
ai
nly
cat
egorized
into
tw
o
tre
nds:
1)
ad
va
nced
de
c
od
i
ng
al
gorith
m
s
fo
r
po
la
r
c
od
es
, a
nd
2) ef
fici
ent hard
war
e
im
ple
m
entat
ion
m
eth
ods
f
or
pola
r c
od
e
s
[
2]
.
Po
la
r
co
des
ar
e
li
near
blo
c
k
cod
es
that
rel
y
on
a
po
la
riz
at
i
on
phen
om
e
non.
T
he
ad
ve
nt
of
pola
r
cod
e
s
is
based
on
the
cha
nn
el
po
la
riz
at
ion
theo
ry.
T
he
c
or
e
i
dea
of
p
ol
ar
co
ding
is
t
o
s
plit
a
giv
e
n
vecto
r
channel
into
m
ulti
ple
cor
relat
ed
bit
channels
and
to
us
e
onl
y
the
go
od
one
s,
in
the
sense
that
they
are
either
ex
trem
el
y
no
isy
or
noise
le
ss.
The
n,
one
ca
n
em
plo
y
a
se
par
at
e
seq
ue
ntial
decoder
on
each
sub
-
cha
nn
e
l
.
Po
la
r
c
od
es h
a
ve
pe
rfor
m
ed
sta
te
-
of
-
the
-
art
cod
e
s
of
la
r
ge
r
blo
ck
le
ng
t
hs
an
d
c
ode
rates.
Po
la
r
co
des
ca
n
al
so
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
Study
of the
op
eratio
na
l
SNR
whil
e co
ns
truct
ing
polar
code
s
(
Red
a
Be
nkhou
y
a
)
3201
be
us
e
d
f
or
s
ource
c
od
i
ng,
but
this
us
e
will
no
t
be
discuss
ed
in
this
pa
pe
r.
I
n
the
le
vel
of
the
oret
ic
al
analy
sis
and
de
velo
pme
nt,
substa
ntial
recent
resea
r
ch
pro
gress
ha
s
been
ac
hie
ved
a
nd
re
por
te
d.
A
by
no
m
eans
com
plete
l
ist
of
re
fere
nces
i
s
[3,
4]
,
see
al
so
[5]
an
d
th
e
ref
ere
nces
t
her
ei
n.
T
he
ai
m
of
this
paper
is
to
dem
on
strat
e
how
the
c
od
e
changes
with
the
OSNR
an
d
the
blo
c
k
le
ng
t
h
as
well
as
the
co
de
r
at
e
fo
r
the
ad
diti
ve
w
hite
G
aus
sia
n
no
ise
(AWGN
)
cha
nn
el
.
Sin
ce
it
is
no
t
known
w
hat
im
p
act
has
the
O
S
NR
on
the
BER
perf
orm
ance
of
pola
r
co
des,
t
his
pa
per
ai
m
s
to
open
t
he
relat
ed
discuss
i
on.
As
con
cl
ud
e
d
i
n
[
6]
al
l
po
la
r
co
de
c
onstr
uctions
are
equ
al
ly
good
in
A
WGN
if
t
he
O
SN
R
is
optim
iz
ed
for
the
be
st
perf
orm
ance.
Th
us
in
ou
r
w
ork
we
m
ay
us
e
si
m
ple
al
gorithm
on
ly
,
nam
el
y
Bhatt
acharyy
a
bounds
bas
e
d
co
ns
tr
uc
ti
on
.
The
rea
der
s w
a
nting
to g
o
dee
per
int
o
the
cu
r
ren
t
stu
dy
m
ay
exp
e
rim
ent
se
par
at
el
y
the
or
t
hogonal
f
reque
ncy
-
div
isi
on
m
ultip
le
xing
(
OFD
M)
[7
-
24]
an
d
e
xp
l
oit
our
ap
proac
h
to
get
the
ef
fect
of
s
uch
m
od
ulati
on
te
chn
iq
ue
on
t
he
pe
rfo
rm
ance
of
t
he
co
de
const
ru
ct
io
n.
Obviously
,
O
F
DM
is
sti
ll
an
ultim
at
e
cand
idate
f
or
wireless
ap
plica
ti
on
s,
since
it
al
lows
res
olv
i
ng
the
well
-
kn
own
pro
blem
of
s
pectr
um
u
nd
e
r
util
iz
at
ion
[25]
.
The
rem
ai
nd
er
o
f
t
his
pa
per
is
ou
tl
ine
d
as f
ol
lows
.
Sect
io
n
2
de
scrib
es
pol
ar
co
des
t
hat
w
e
st
ud
y
in
t
his w
ork
.
In
Sect
i
on
3
w
e
rev
ie
w
a
sim
plest
co
ns
tr
uction
t
o
sel
ect
the
bit
-
cha
nnel
s
ov
e
r
w
hich
t
he
inform
at
ion
bits
are
transm
itted.
T
he
dec
oder
a
dopte
d
is
int
r
od
uced
i
n
Sect
io
n
4
.
A
fter
ward
s,
sim
ulati
on
r
esults
are
pro
vi
ded
in
S
ect
ion
5
.
Fina
ll
y, con
cl
usi
on
s and
f
ut
ur
e
works
fo
ll
ow in Sec
ti
on
6
.
2.
POLA
R CO
D
ING
Let
(
,
)
NK
be
a
li
near
bo
c
k
co
de,
w
her
e
2
n
N
is
the
cod
e
le
ngth,
n
is
an
ar
bitrary
inte
ger,
K
is
the
co
de
dim
e
ns
io
n,
the
c
od
e
rate
of
su
c
h
co
ding
sc
hem
e
is
de
fine
d
by
R
K
N
,
0
KN
.
A
bi
nar
y
po
la
r
co
de
is
c
om
plete
ly
sp
ec
ifie
d
by
a
tri
pl
e
(
,
,
)
F
NK
,
w
her
e
F
,
F
NK
is
the
set
of
the
f
r
ozen
bit
ind
ic
es.
Th
e
rem
ai
nin
g
K
el
e
m
ents
are
cal
le
d
the
in
form
at
ion
bits
in
di
ces.
Let
n
f
o
i
s
n
F
F
F
be
the
n
-
f
old
K
roneck
e
r
pro
du
ct
of
A
rika
n’s
st
and
a
r
d
po
la
rizi
ng
ke
rnel
11
01
F
.
T
he
m
a
trix
n
F
deno
te
s
the
n
-
th
te
nsor
powe
r
of
F
an
d
cou
l
d
be
e
valu
at
ed
by
a
pply
ing
the
Kro
nec
ker
pro
duct
rec
ur
si
vely
acco
r
ding
to
(
1
)
nn
F
F
F
.
The
n for a
vecto
r of
i
nform
at
ion
b
it
s
u
of
le
ng
th
K
, a
c
ode
word is
gen
e
ra
te
d
as
x
G
u
(1)
w
he
re
()
C
n
GF
is
the
ge
ner
at
or
m
at
rix
of
pola
r
cod
e
w
hich
pi
cks
a
sp
eci
fic
subset
of
K
r
ows
of
the
NN
m
at
rix,
an
d
0
,
1
,
,
1
\
FF
C
N
corres
ponds
to
the
set
of
non
-
f
ro
ze
n
bit
ind
ic
es.
Im
plici
tl
y,
with
res
pect
to
cl
assic
al
NN
m
at
r
ix
base
d
enc
oding
,
the
frozen
bits
F
are
set
to
zero
an
d
we
f
ollow
th
i
s
conve
ntion
thr
oughout
the
pa
per.
Co
ns
ide
r
a
cha
nn
el
W
is
us
ed
f
or
t
ra
ns
m
itti
ng
the
i
nfor
m
at
ion
bet
ween
input
an
d
outpu
t.
Let
12
(
,
,
,
)
N
x
x
x
x
be
the
in
pu
ts
vector
a
nd
1
(
,
,
)
N
y
y
y
be
the
ou
t
pu
ts
vecto
r
.
Give
n
a
bi
nar
y
-
in
pu
t
c
hannel
:
W
X
Y
with
0
,1
X
,
the
Bh
at
ta
char
yy
a
pa
ram
et
er
()
ZW
can
be
us
e
d
to
m
easur
e
the
err
or
pe
rfor
m
ance
of
the
ch
ann
el
.
In
gen
e
r
al
,
we
can
ch
oose
the
posit
io
ns
of
the
inf
orm
at
ion
bits
and
f
r
oze
n
bits
by
their
Bhatt
acharyy
a
par
am
et
er
()
ZW
,
wh
ic
h
can
be
def
i
ned
as
the
upper
bound
of
the d
eci
si
on er
ror pr
obabili
ty
w
he
n
t
he
c
hannel is
us
ed
to
t
r
ansm
it
zero
or
on
e
as
fo
ll
ows
:
(
)
(
|
0
)
(
|
1
)
yY
Z
W
p
y
p
y
(2)
w
he
re
(
|
)
p
y
s
is
the
conditi
on
al
pro
ba
bili
ty
of
the
recei
ved
y
prov
i
ded
t
hat
0
,
1
s
is
transm
it
te
d.
As
the
bit
-
cha
nn
el
s
sta
rt
pola
rizi
ng,
they
a
ppr
oach
ei
the
r
no
ise
le
ss
good
bit
-
cha
nnel
or
a
pure
-
noise
ba
d
bit
-
channel.
The
Bhatt
acharyy
a
par
am
et
er
in
dicat
e
s
that
th
e
fr
act
io
n
of
bit
cha
nn
el
s
a
ppr
oach
es
the
m
utu
a
l
inf
or
m
at
ion
()
IW
as
n
.
Even
th
ou
gh
syst
em
atic
var
ia
nts
of
po
l
ar
enc
od
i
ng
do
exist,
we
c
onstr
uct
the
ori
gi
nal
pola
r
c
odes
whic
h
are
no
n
-
sy
stem
at
ic
,
and
bein
g
a
li
near
co
de,
t
he
e
nc
od
i
ng
sim
ply
nee
ds
a
m
at
rix
m
ult
ipli
cat
ion
.
O
nc
e
the
cod
e
s
iz
e
is
la
rg
er,
m
at
rix
m
ulti
pl
ic
at
ion
bec
ome
s
com
pu
ta
ti
on
al
ly
exp
e
ns
i
ve
as f
a
r
as
2
()
ON
. Th
us, in
our
w
ork
we u
se an
al
te
rn
at
iv
e i
m
ple
m
entati
on
base
d
on FF
T’s
butt
er
fly
ci
rcu
it
m
od
el
,
wh
ic
h
ex
hib
it
s
sign
ific
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ntly
red
uce
d
c
om
pu
ta
ti
on
al
com
pl
exity
of
(
l
o
g
)
.
O
N
N
In
ou
r
pola
r
cod
e
desig
n,
we
us
e
rec
ur
si
ve
est
im
at
ion
of
the
just
i
ntr
oduce
d
B
hatta
char
yy
a
par
am
et
ers
of
bit
-
c
ha
nn
el
s
,
wh
ic
h
is
goin
g t
o
be
d
et
ai
le
d i
n
the
n
e
xt secti
on.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Ele
c &
C
om
p
En
g,
V
ol.
10
, No
.
3
,
J
une
2020 :
32
00
-
3207
3202
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e
O
S
N
R
a
n
d
u
s
e
i
t
f
o
r
a
r
a
n
g
e
o
f
p
o
s
s
i
b
l
e
S
N
R
s
.
T
h
i
s
w
a
y
,
w
e
u
s
e
a
u
n
i
q
u
e
c
o
d
e
c
r
e
a
t
e
d
b
y
r
u
n
n
i
n
g
t
h
e
c
o
d
e
-
c
o
n
s
t
r
u
c
t
i
o
n
a
t
a
s
i
n
g
l
e
v
a
l
u
e
o
f
t
h
e
c
h
a
n
n
e
l
-
s
t
a
t
e
a
n
d
k
e
e
p
i
n
g
t
h
e
c
o
d
e
u
n
c
h
a
n
g
e
d
f
o
r
a
l
l
c
h
a
n
n
e
l
c
o
n
d
i
t
i
o
n
s
.
A
s
w
e
s
e
e
l
a
t
e
r
,
i
t
i
s
c
r
u
c
i
a
l
t
o
p
r
o
p
e
r
l
y
s
e
l
e
c
t
t
h
e
a
d
e
q
u
a
t
e
O
S
N
R
g
i
v
e
n
r
a
t
e
a
n
d
b
l
o
c
k
l
e
n
g
t
h
f
o
r
t
h
e
p
e
r
f
o
r
m
a
n
c
e
i
n
t
e
r
m
s
o
f
b
i
t
e
r
r
o
r
r
a
t
e
.
4.
THE
NATIV
E DEC
ODIN
G
It
is
pro
ven
in
[
26
]
that
f
or
any
(
,
)
NK
po
la
r
c
ode
on
a
ny
B
-
D
MC
,
there
exi
sts
an
e
nc
od
e
r
an
d
a
decoder
known
as
su
cce
ssive
cancel
la
ti
on
(S
C
)
dec
od
e
r,
eac
h
wi
th
the
sam
e
order
of
c
omplexit
y
(
l
o
g
)
.
O
N
N
W
e
ass
um
e
that
the
dec
od
e
r
consi
der
e
d
i
n
the
syst
em
is
a
SC
dec
od
e
r,
f
or
w
hich
po
la
r
codes
are
ta
il
or
e
d.
S
C
al
gor
it
hm
,
wh
ic
h
dec
od
e
s
e
ach
bit
in
a
s
uc
cessi
ve
m
ann
e
r,
is
usual
ly
em
plo
ye
d
and
pro
posed
as
sub
-
optim
a
l
appro
ac
h.
By
ta
kin
g
a
dvanta
ge
of
t
he
pola
rizat
ion
eff
ect
,
pola
r
co
des
ca
n
a
chieve
the
sy
m
m
et
ric
capaci
ty
of
bin
ary
m
e
m
or
yl
ess
channels
with
low
com
plexity
SC
deco
di
ng
strat
e
gy
[1]
.
Be
ing
f
undam
ental
for
al
l
th
e
la
te
r
adv
a
nc
ed
dec
oders
t
ha
t
exh
ibit
s
up
e
rior
pe
rfor
m
ance,
one
can
not
avo
i
d
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
Study
of the
op
eratio
na
l
SNR
whil
e co
ns
truct
ing
polar
code
s
(
Red
a
Be
nkhou
y
a
)
3203
hav
i
ng
an
SC
decode
r.
The
SC
al
gorithm
traverse
s
th
e
e
ntire
po
la
r
c
ode
tree
de
pth
first,
vis
it
ing
a
ll
le
af
nodes
[27]
.
F
r
om
deco
di
ng
view
po
i
nt,
c
onstructin
g
a
po
l
ar
co
de
of
di
m
ension
K
is
equ
i
valent
to
f
ind
in
g
the
K
best
bi
t
-
cha
nn
el
s
t
ha
t
m
od
el
the
channel
that
t
he
decoder
s
e
es
w
hen
it
re
cov
e
rs
one
by
on
e
the
inf
or
m
at
ion
bits
c
orrespondin
g
to
t
he
receive
d
co
de
wo
rd
by
the
SC
dec
od
e
r
[28]
.
Acc
ordi
ng
t
o
the
co
ns
tr
uctio
n
of
pola
r
c
od
es,
two
gro
ups
of
bits
are
es
ta
blished
from
the
m
any
ind
epende
nt
co
pies
of
channels.
The
first
gr
oup
is
t
he
in
form
at
ion
bits
:1
F
C
i
U
u
i
K
and
t
he
s
eco
nd
one
is
t
he
f
r
ozen
bits
:1
F
j
U
u
j
N
K
that
are
m
a
de
know
n
to
the
decoder.
The
log
-
li
ke
li
ho
od
rati
os
(LLR)
of
the ch
a
nnel
are
calc
ulate
d
as
(
|
0
)
(
)
l
n
(
|
1
)
ii
i
ii
p
y
x
L
L
R
y
p
y
x
(5)
The
SC
ap
plies
the
recursive
cal
culat
ion
s
on
the
recei
ved
LLRs
f
ro
m
(
5
)
an
d
the
decisi
on
f
unct
io
n
for
the
SC
dec
od
e
r
is
de
fine
d by
1
11
1
11
0
,
(
,
)
0
ˆ
1
,
(
,
)
0
Ni
i
Ni
L
L
R
y
U
U
L
L
R
y
U
(6)
wh
e
re
1
11
(
,
)
Ni
L
L
R
y
U
is
equ
ivale
nt
to
the
li
kelihoo
d
rati
o
of
i
U
giv
en
the
c
hannel
outp
ut
Y
and
1
1
i
U
wh
ic
h
are
f
ound
prev
iou
sly
by
the
de
cod
e
r.
It
shoul
d
be
m
entione
d
that,
f
or
the
f
irst
bit
1
ˆ
U
value,
the
dec
od
e
r
us
es
on
ly
y
fo
r
the
decisi
on
.
I
n
our
sim
ulati
on
we
us
e
an
im
plem
entat
ion
of
the
basic
suc
cessi
ve
cance
ll
at
ion
decode
r,
w
hich
w
e
belie
ve
t
o be the
sim
plest
i
m
ple
m
entat
ion
po
s
sible.
5.
NUMER
CI
A
L RES
ULTS
AND DIS
C
USS
ION
In
t
his
sect
io
n
we
re
port
t
he
r
esults
of
our
si
m
ula
ti
on
s.
We
co
ns
ide
r
c
ompari
ng
t
he
perf
or
m
ance
of
po
la
r
co
des
f
r
om
var
iou
s
pa
ram
et
ers.
Even
if
the
er
ror
perform
ance
of
pola
r
co
des
with
sho
rt
codewor
d
le
ng
th
is
al
rea
dy
descr
i
bed
by
[4
]
as
m
edi
ocr
e
un
de
r
SC
al
go
rithm
,
we
insist
on
co
nsi
der
in
g
bl
ock
l
eng
t
h
N
=256
i
n
a
dd
i
ti
on
t
o
tw
o
ne
w
blo
c
klen
gths,
nam
ely
N
=
10
24,
N=
4096.
Fo
r
eac
h
blo
c
klen
gth
we
co
ns
id
e
r
on
ly
high c
od
e
r
at
e
R
=
5/6
. T
he
cond
it
io
ns
of sim
ulat
ion
a
re
d
esc
ribe
d
in
T
able 1.
Table
1.
Sim
ul
at
ion
par
am
et
e
rs
Para
m
eter
na
m
e
Valu
e
Mini
m
u
m
blo
ck
sa
m
p
l
es
1000
Mini
m
u
m
bit
er
ror
s
100
Mod
u
latio
n
BPSK
Ch
an
n
el
AW
G
N
The
tra
ns
m
issio
n
is
sup
po
se
d
to
be
over
an
A
WGN
ch
ann
el
with
ze
r
o
m
ean.
W
it
hout
l
os
s
of
gen
e
rali
ty
,
we
norm
al
iz
e
the
no
ise
var
ia
nce
to
be
un
it
y
in
the
rem
ai
nd
er
of
our
sim
ulati
on
.
Bi
ts
in
co
de
word
are
m
od
ulate
d
us
in
g
bin
a
ry
phase
s
hift
keyi
ng
(BP
SK).
We
en
s
ure
a
pra
ct
ic
al
values
of
BER
(e.g.
ord
er
of
10
-
3
a
nd
le
ss
),
an
d
guara
ntee
a
m
ini
m
u
m
of
1000
bl
ock
sa
m
ples.
Fo
r
each
eval
uated
S
N
R,
we
achie
ve
at
le
ast
100
bit
error
s
.
In
orde
r
to
stud
y
the
im
pac
t
of
OSNR
on
BER
per
form
ance,
we
us
e
the
discrete
sea
rch
of
OSNR
over
a
finite
inter
val.
W
e
ca
rr
y
out
si
m
ulati
on
s
and
we
plo
t
t
he
res
ults
in
l
og
a
rithm
ic
do
m
ai
n.
The
disc
rete
search
c
on
sist
s
on
s
pa
nn
i
ng
t
he
w
ho
le
inter
val
sta
rting
f
r
om
the
OS
NR
-
5dB
as
init
ia
l
po
int
wh
e
n
necessar
y.
The
searc
h
i
s
purs
ued
f
urt
he
r
by
inc
rem
enting
O
SN
R
as
l
ong
as
the
BE
R
i
m
pr
ov
es
. W
e
sto
p
the
discrete
se
arch
once
the
BER
perform
a
nce
de
grades
f
or
at
le
ast
one
from
the
nex
t
OSNRs.
By
th
is
way,
we
retrie
ve
th
e
cand
i
date
O
SN
R
w
hose
B
ER
curve
is
t
he
fir
st
one,
wh
ic
h
cr
os
ses
the
unc
od
e
d
curve
.
We conf
i
rm
the BER
d
egr
a
da
ti
on
b
y usi
ng
s
om
e g
reater v
a
lue o
f OS
NR (e.g.
10dB). N
ot
e that i
n
each f
ig
ur
e,
the
i
m
po
rtant
portio
n
of
the
BER
cur
ves
is
m
agn
ifie
d,
wh
e
re
cu
rv
es
of
stu
died
c
odes
cro
ss
the
c
urve
of
the unc
od
e
d sy
stem
.
Figure
1
il
lust
rates
S
N
R
versus
BER
f
or
N
=256
at
R
=
5/
6.
It
ca
n
be
note
d
t
hat
al
m
os
t
al
l
OSNRs
offer
t
he
sam
e
perform
ance.
I
t
is
al
so
sh
ow
n
that
the
unco
de
d
case
off
ers
bette
r
pe
rfor
m
ance
in
te
rm
s
of
BER
than
t
he
co
de
d
one
si
nce
S
NR
is
le
ss
tha
n
3.7
7dB.
Acc
ordin
g
to
our
adopted
m
et
ho
d
ba
sed
on
discrete
search
,
the
ca
nd
i
date
OSNR
is
1d
B.
I
ncr
e
asi
ng
N
to
10
24
m
akes
the
per
f
orm
ance
weak
ly
sensiti
ve
to
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Ele
c &
C
om
p
En
g,
V
ol.
10
, No
.
3
,
J
une
2020 :
32
00
-
3207
3204
the
O
SN
R
,
as
dep
ic
te
d
in
Fi
gure
2.
It
is
s
how
n
once
a
gai
n
that
t
he
unc
od
e
d
ca
se
offe
rs
bette
r
perfor
m
ance
than
t
he
co
de
d on
e
since
SN
R
is less t
han 3.
65dB
for
R
=
5/6
. Fr
om
the zo
om
p
art, the ca
nd
i
date O
SN
R
is 3dB
for
R
=
5/6.
Figure
1
.
Im
pact o
f
O
SN
R
on
BER
p
e
rfor
m
ance
for
N
=
256
at
R
=5/6
Figure
2
.
BER
sensiti
vity
to
O
SN
R
for
N
=
1024 at
R
=
5/6
Figure
3
de
pic
t
s
the
per
f
or
m
ance
of
po
la
r
cod
e
s
pro
du
ce
d
for
N
=4
096
at
R
=5/6.
U
nlike
sm
a
ll
er
blo
c
klen
gth
,
it
is
sh
ow
n
that
f
or
N
=
4096
the
BER
bec
om
es
plainly
sensiti
ve
to
OSNR.
The
un
c
oded
s
yst
e
m
offer
s
b
et
te
r
p
e
rfor
m
ance tha
n t
he
c
od
e
d o
ne i
n
te
rm
s o
f
BE
R si
nce SNR i
s
less tha
n
3.468d
B
. I
t ca
n be
no
te
d
that
the
ca
nd
i
date
O
SN
R
is
5dB.
F
or
inst
ance,
t
he
BER
de
gr
a
datio
n
s
ta
rts
at
OSNR
>
5dB
a
nd
de
gr
a
des
dr
am
at
ic
ally
w
hen
OSNR
rea
ches
10
dB
.
A
s
recapitulat
io
n,
inc
reasin
g
bl
ock
le
ngth
m
akes
BER
perform
ance
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
Study
of the
op
eratio
na
l
SNR
whil
e co
ns
truct
ing
polar
code
s
(
Red
a
Be
nkhou
y
a
)
3205
sensiti
ve
to
OSNR.
It
is
i
nd
ee
d
crit
ic
al
to
co
ns
tr
uct
pola
r
c
od
e
with
a
good
BER
pe
rfo
r
m
ance.
This
ha
s
be
e
n
al
read
y
sta
te
d
in
[
6]
bu
t
only
f
or
bl
ock
le
ng
t
h
N
=
2048
a
nd
co
de
rate
R
=
1/
2
.
T
o
av
oid
c
onf
us
io
n
a
nd
s
tress
the
diff
e
re
nces
,
le
t
us
su
m
m
a
rize
the
resu
lt
s
in
Table
2.
T
he
cand
id
at
e
OSNR
corres
pond
s
to
a
sel
ect
ed
value
accor
ding
to
t
he
disc
rete
search
m
et
ho
d.
Figure
4
il
lust
rates
the
c
onst
ru
ct
io
n
c
har
t
f
or
c
od
e
rate
R
=5/6
.
Cl
early
fo
r
a
giv
e
n
c
od
e
ra
te
R
;
the
hi
gher
blo
c
kle
ng
t
h
is,
t
he
ea
rlie
r
the
c
oded
syst
e
m
ou
tpe
r
form
s
the unc
od
e
d o
ne
.
The
c
urves
dem
on
strat
e
th
e
BER
per
f
or
m
ance
ver
s
us
SN
R
f
or
t
he
cod
e
rate
R
=5/6.
Wh
il
e
const
ru
ct
in
g
pola
r
c
od
e
with
rate
R
=5/
6
,
in
creasin
g
bl
oc
kl
eng
th
from
N
=256
to
N
=
40
96
ac
hie
ves
th
e
SN
R
gain
of
Gain
=1.2d
B
at
the
BER
of
10
-
4
.
This
tra
de
-
off
so
rte
d
out
m
us
t
be
ta
ken
i
nto
consi
der
at
io
n
wh
il
e
const
ru
ct
in
g p
olar
c
odes
for hig
h
-
t
hroug
hput appli
cat
ion
.
Figur
e
3. Im
pact o
f
OSNR
on
BER
p
e
rfor
m
ance
for
N
=
4096 at
R
=
5/6
Figure
4.
Co
nst
ru
ct
io
n
c
har
t
f
or co
de rat
e
R
=5/6
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Ele
c &
C
om
p
En
g,
V
ol.
10
, No
.
3
,
J
une
2020 :
32
00
-
3207
3206
Ta
bl
e
2
.
Im
pact of OS
NR on
BE
R
sensiti
vi
t
y
for
code
r
ate
R
=5/
6
Co
d
e leng
th
Sen
sib
ility
Can
d
id
ate OSNR
256
Low
1
1024
Mediu
m
3
4096
Hig
h
5
6.
CONCL
US
I
O
N
W
e
rest
ud
ie
d
i
n
this
pap
e
r
th
e
non
-
unive
rsa
li
ty
of
po
la
r
c
od
e
s.
We
pe
rfor
m
ed
a
discre
te
search
t
o
fin
d
the
be
st
O
SN
R
f
or
c
ode
const
ru
ct
io
n.
We
the
n
com
par
ed
BER
perf
or
m
ances
f
or
t
hr
ee
c
odew
ord
le
ng
ths
and
ob
se
r
ved
that
fo
r
s
hort
one
the
ef
fect
of
OSNR
is
m
eaning
le
ss
e
ven
f
or
higher
cod
e
rate
.
It
is
al
so
ob
s
er
ved
that
f
or
lo
ng
bl
ock
l
eng
t
h,
OSNR
hav
e
hu
ge
im
pact
on
BER
pe
rfor
m
ance.
I
n
this
pa
per
,
t
he
BER
perform
ance
analy
sis
is
su
m
m
arized
to
cl
arify
disc
us
sio
n
on
c
on
st
r
uc
ti
on
pe
rs
pecti
ve.
We
ass
ume
that
the
pr
opos
e
d
char
t
c
ontrib
ut
es
to
pa
ve
the
path
to
wards
this
en
d.
Th
e
resu
lt
s
s
how
n
are
pr
el
im
inary
an
d
the
w
ork
nee
ds
to
be
exte
nded
f
urt
her
to
pro
ve
that
t
he
s
tud
y
is
in
dee
d
viable
f
or
Ra
yl
ei
gh
fa
ding
c
hannel
,
or
e
ven
Na
kaga
m
i
-
m
fad
ing
channel
.
We
inten
d
to
in
vest
igate
in
a
fu
t
ure
work
t
he
pe
r
form
ance
analy
sis
of
the
con
si
der
e
d
co
ns
tr
uction
under
ort
ho
gonal
f
reque
nc
y
-
div
isi
on
m
ulti
plexing
(
OFDM)
.
S
uc
h
syst
e
m
auth
or
iz
es
div
i
sion
of
the
ba
ndwidt
h
into
narrow
or
th
og
on
al
s
ub
c
ha
nnel
,
an
d
this
is
us
ef
ul
to
op
tim
iz
e
the
sp
ect
ru
m
use
.
H
oweve
r,
c
on
ce
r
ning
pola
r
co
des
,
the
de
cod
i
ng
pe
rform
ance
of
SC
al
gorithm
is
st
il
l
no
t
sat
isfyi
ng
.
We
m
a
y
ob
ta
in
be
tt
er
perf
or
m
a
nce
us
in
g
a
n
i
te
rati
ve
dec
od
er.
T
he
re
is
al
so
a
nee
d
to
stud
y
th
e ef
fect
of
i
niti
al
v
al
ue of
B
hatta
char
yy
a
pa
ram
et
er o
n
sy
stem
’s
perf
or
m
ance
in
a
fu
t
ure w
ork.
REFERE
NCE
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and
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a,
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64
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iscre
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A
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ara
t
ive
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Cons
truc
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AW
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[7]
G.
A.
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sain,
L.
Audah
,
“
BCH
code
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5G
wire
l
ess
communic
a
ti
on
s
y
s
tem
s
over
m
ult
ipath
fad
ing
ch
ann
el
,
”
Indone
sian J
our
nal
of
Elec
tric
al
Engi
ne
ering
and
Computer
Sc
ie
n
ce
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IJEECS)
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P.
Manha
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M.
K
Soni,
“
OF
D
M
Sy
st
em
Perform
anc
e
Ev
al
ua
ti
on
under
Diffe
ren
t
Fading
Cha
nnel
s
and
Ch
an
nel
Coding
using
Matlab
Sim
uli
nk,
”
Indone
sian
Jou
rnal
of
Elec
trical
Engi
n
ee
ring
and
Computer
Sci
en
ce
(
IJEECS)
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-
266,
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P.
S.
Sw
apna,
S.
Pill
a
i
Sakun
ta
l
a
,
“
Resourc
e
Allo
ca
t
ion
Algori
th
m
for
S
y
m
m
et
ri
ca
l
Services
in
OF
DMA
Sy
st
ems
,
”
Indone
sian J
our
nal
of
Elec
tric
al
Engi
ne
ering
and
Computer
Sc
ie
n
ce
(
IJEECS)
,
vol
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18
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no
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2
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8
67
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874,
2020
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[10]
J.
Shukla,
A.
Jos
hi,
and
R.
T
y
agi,
“
PA
PR
ana
l
y
sis
of
OF
DM
sy
st
em
using
AI
base
d
m
ult
ipl
e
signa
l
rep
rese
nt
at
ion
m
et
hods
,
”
TEL
KOMNIKA
(
Tele
communic
ati
on,
C
omputing,
Elec
tronic
s and
Control)
,
vol.
17,
no
.
2,
pp.
2983
-
2991
,
2020.
[11]
M.
K.
Hus
ei
n,
“
Minim
iz
e
M
IMO
O
FDM
i
nte
rfe
r
ence
and
noise
rat
io
u
sing
pol
y
nom
ial
-
ti
m
e
al
gorit
hm
,
”
Inte
rnational
Jo
urnal
of El
e
ct
ri
c
al
and
Comput
er
Engi
n
ee
ring
(
IJE
CE)
,
vol
.
10
,
n
o
.
1
,
pp
.
900
-
90
7,
2020
.
[12]
B.
Sabbar
,
M.
Khali
fa
,
“
Perfor
m
anc
e
Ev
al
u
at
i
on
of
High
Mo
bil
ity
OF
DM
C
hanne
l
Esti
m
ati
on
Techni
ques,
”
Inte
rnational
Jo
u
rnal
of El
e
ct
ri
c
al
and
Comput
er
Engi
n
ee
ring
(
IJE
CE)
,
vol
.
10
,
n
o.
3
,
pp
.
2562
-
2
568,
2020
.
[13]
S.
Raz
m
i,
N.
Pa
rhiz
gar
,
“
Adaptive
resourc
es
ass
ignment
in
OF
DM
-
base
d
cogni
t
i
ve
rad
io
s
y
s
te
m
s,
”
Inte
rnat
ional
Journal
of
Elec
t
rical
and
Computer
Eng
ine
ering
(
IJE
CE)
,
vol. 9,
no
.
3
,
pp
.
1935
-
1943,
2019
.
[14]
S.
Su
y
oto
,
I.
I
skanda
r,
and
S
.
Sugihart
ono,
Adit
Kurniawa
n
,
“
Im
prove
d
Tim
ing
Esti
m
at
io
n
Us
ing
Ite
rati
ve
Norm
al
iz
ation
Te
chn
ique
for
OF
DM
Sy
st
ems
,
”
Int
ernati
ona
l
Journal
of
El
e
ct
rical
and
Co
mputer
Engi
ne
e
ring
(
IJE
CE)
,
vol
.
7,
no
.
2
,
pp
.
905
-
9
11,
2017
.
[15]
H.
Ham
li
li,
S.
Kam
ec
he,
and
A.
Abdelmal
ek,
“
SαS
noise
suppress
ion
for
OF
DM
wire
le
ss
comm
unic
at
io
n
in
ra
y
l
ei
ght
ch
a
nnel
,
”
Int
ernational
Journal
o
f
El
e
ct
ri
cal
and
Computer
Enginee
ring
(
IJE
CE
)
,
vol.
10,
no
.
2,
pp.
2003
-
2010
,
2020.
[16]
B.
Archa
n
a
B
.
,
and
T
.
P.
Surek
ha
,
“
Int
egr
ated
appr
oac
h
for
eff
ic
i
ent
power
co
nsum
pti
on
and
r
es
ourc
e
al
lo
cati
on
in
MIM
O
-
OF
D
MA
,
”
Inte
rnat
io
nal
Journal
o
f
El
e
ct
rica
l
and
Computer
Enginee
ring
(
IJE
CE
)
,
vol.
10
,
no
.
2,
pp.
2069
-
2076
,
2020.
[17]
A.
H.
Ali,
and
A.
A.
Hussie
n
,
“
Com
pre
hensive
Inve
stiga
t
ion
of
Cohere
nt
Opti
ca
l
OF
DM
-
Ro
F
E
mpl
o
y
ing
16QA
M
Ext
ern
al
Modul
at
ion
for
Long
-
Haul
Optic
a
l
C
om
m
unic
at
ion
Sy
stem,
”
Inte
rnat
ional
Journal
o
f
El
e
ct
rica
l
and
Computer
Engi
n
ee
ring
(
IJE
C
E)
,
vol.
10
,
no
.
3
,
pp
.
2607
-
2616
,
20
20.
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
Study
of the
op
eratio
na
l
SNR
whil
e co
ns
truct
ing
polar
code
s
(
Red
a
Be
nkhou
y
a
)
3207
[18]
M.I.
Yous
sif,
A.
E.
Emam
,
M.
A.
El
Ghan
y
,
“
Im
age
m
ult
iplexing
u
sing
residue
nu
m
ber
s
y
stem
co
ding
over
MIM
O
-
OF
DM
co
m
m
un
ic
a
ti
on
s
y
s
te
m
,
”
Inte
rnationa
l
J
ournal
of
Elec
tr
ic
al
and
Compu
te
r
Engi
n
ee
ring
(
IJE
CE)
,
vol.
9
,
no
.
6
,
pp
.
4815
-
4825,
2019
.
[19]
M.
D.
Roz
ai
ni
,
A.
Idris,
D
.
M.
Ali,
E.
Abdul
la
h
,
“
Media
n
codew
ord
Shift
(MCS
)
te
chni
q
ue
for
PA
PR
red
uct
i
o
n
with
low
compl
exi
t
y
in
OF
DM
s
y
stem,
”
In
te
rna
ti
onal
Journal
o
f
Elec
tri
cal
and
Computer
Engi
n
ee
ring
(
IJE
CE)
,
vol.
9
,
no
.
6
,
pp
.
4882
-
4888,
201
9
[20]
M.
F.
Ghanim
,
“
Perform
anc
e
inve
stigation
o
f
W
OF
D
M
for
5G
wire
le
ss
ne
t
works
,
”
Inte
rna
ti
onal
Journal
of
El
e
ct
rica
l
and
C
omputer
Engi
n
e
ering
(
IJE
CE)
,
v
ol.
9
,
no
.
4
,
pp
.
3
153
-
3158,
2019
[21]
K.
J.
Tha
j
eel,
I
.
K.
Abboud,
L.
A.
Kunbar
,
“
Design
of
enc
r
y
pt
e
d
tra
nsce
ive
r
No
n
-
cohe
re
n
t
OF
DM
with
abi
lit
y
t
o
cor
rect
codi
ng
b
it
s
of
informati
on,
”
Inte
rnat
ional
Journal
of
El
ect
rical
and
Computer
Engi
ne
erin
g
(
IJE
CE)
,
vol.
9,
no.
4
,
pp
.
3212
-
3220,
2019
.
[22]
A.
H.
Ali,
H.
J.
Alhamdane
,
Be
gar
ed
Sali
h
Has
sen,
“
Design
ana
l
y
s
is
and
per
fo
rm
anc
e
evalua
t
i
on
of
the
W
D
M
int
egr
at
ion
wi
th
CO
-
OF
D
M
sy
st
em
for
rad
io
ov
e
r
fibe
r
S
y
s
te
m
,
”
Indone
sian
Jour
nal
of
E
lectric
a
l
Engi
ne
ering
an
d
Computer
Scien
ce
(
IJEECS)
,
vol
.
15
,
no
.
2
,
pp
.
8
70
-
878,
2019
.
[23]
S.
Atoui,
N.
D
oghm
ane
,
S.
Afifi,
“
Bli
nd
fr
e
quency
offset
e
stim
at
or
for
OF
DM
sy
stems
,
”
TEL
KOMNIKA
(
Tele
communic
ati
on,
Computing, E
l
ec
troni
cs
and
Control)
,
vol. 17
,
no
.
6
,
pp
.
2722
-
2728,
2019
.
[24]
Rawa
a
J.
Hasan,
and
Hikm
at
N.
Abdulla
h
,
“
Co
m
par
at
ive
study
of
select
ed
subca
rr
ie
r
inde
x
m
odula
ti
o
n
OF
DM
sche
m
es
,
”
TEL
KOMNIKA
(
Tele
communic
ati
on
,
Comput
ing,
E
le
c
tronic
s
and
Control
)
,
vol.
17,
no
.
1,
pp.
15
-
22
,
2019
.
[25]
Z.
M
Abid,
A.
A
Jaffa
ar,
S.
Q
Hadi,
“
PA
PR
re
duct
ion
in
OF
DM
sy
st
em
for
D
VB
-
S2,
”
Indone
sian
Journal
of
El
e
ct
rica
l
Eng
in
ee
ring a
nd
Computer
Sc
ie
nc
e
(
IJ
EE
CS)
,
vol
.
17
,
no
.
1
,
pp
.
317
-
3
23,
2020
.
[26]
A.
Hadi,
K.
M.
Rabi
e
and
E.
Al
sus
a,
“
Polar
cod
es
base
d
OF
D
M
-
PLC
sy
stems
in
the
pre
senc
e
of
m
iddl
et
on
cl
ass
-
A
noise,
”
20
16
10t
h
Inte
rnationa
l
Symposium
on
Comm
unic
ati
on
Syste
ms
,
Net
wor
ks
and
Digit
al
S
ignal
Proc
essing
(
CSNDSP
)
,
Prague
,
pp
.
1
-
6
,
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EE
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Circui
ts and
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te
ms
(
ISCAS)
,
Montreal, QC,
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ane
w
pol
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nformation
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pp
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234
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2016.
BIOGR
AP
H
I
ES
OF
A
UTH
ORS
Reda
Benk
houy
a
was
invi
t
ed
as
a
visi
ti
ng
sch
ola
r
at
Toul
ouse
insti
tu
te
of
co
m
pute
r
scie
n
ce
rese
arc
h
(IRIT
)
,
Franc
e,
in
2004
.
Since
2006
he
has
bee
n
wi
th
E
t
isal
at
where
he
i
s
cur
ren
t
l
y
an
IT
SM
.
He
is
now
pursuing
the
Ph.D.
degr
e
e
at
Ibn
Tofail
U
nive
rsit
y
.
His
r
ese
arc
h
int
er
est
inc
lud
es
cha
n
nel c
oding
,
cogni
t
iv
e
rad
io
,
ar
ti
fi
ci
a
l
intelligence, Io
T,
cl
oud
and
big dat
a
.
Id
ri
ss
Ch
ana
r
ec
e
ive
d
the
Ph.
D.
degr
ee
f
rom
Moham
ed
V
Univer
sit
y
,
Morocc
o
in
2013
.
He
is
cur
ren
tly
a
full
profe
ss
or
at
Moula
y
Ism
ai
l
Univer
sit
y
,
Mo
roc
co.
He
is
m
ember
of
IEE
E.
His
rese
arc
h
intere
sts
include
in
form
at
ion
and
c
om
m
unic
at
ion
t
ec
hnolog
ie
s.
A
l
arg
e
p
art
of
h
is
rese
arc
h
proj
ec
ts
are
re
la
t
ed
to
E
rror
cor
r
ec
t
ion
c
odes
and
Turbo
code
s.
Id
riss
Chana
pub
li
she
d
m
ore
tha
n
20
p
a
per
s in
m
a
jor
jou
rna
ls a
nd
conf
er
enc
es
in
Inform
a
ti
on
The
or
y
.
You
ss
ef
Hadi
r
ec
e
ive
d
his
Ph.
D.
degr
e
e
in
Co
m
pute
r
Scie
nc
es
and
Tele
communic
a
ti
ons
from
the
Facul
t
y
of
Scie
n
ce
s
of
the
Moham
m
ed
V
Uni
ver
sit
y
,
Rab
at
,
Morocc
o
in
2008.
From
2009
to
2015,
he
was
an
As
sistant
Profess
or
at
Ibn
Tofa
il
Univer
sit
y
,
Fa
cul
t
y
of
Scie
n
ces
with
LAR
IT
la
bora
tor
y
.
Curr
ent
l
y
h
e
is
an
As
socia
te
Profe
ss
or
at
the
sam
e
univers
ity
and
he
is
the
Vi
ce
Dire
ct
or
of
MIS
C
La
bora
tor
y
(
Modeli
ng
of
Inf
orm
at
ion
and
C
om
m
unic
at
ion
Sy
stems
).
Also
,
h
e
is
a
m
ember
of
IEE
E
and
he
is
Student
Bran
ch
Mem
ber
of
Ibn
Tofa
il
Univ
e
rsit
y
.
Yous
sef
Hadi
rese
arc
h
i
nte
rests
inc
lud
e
Software
Enginee
ring
,
Mode
l
Drive
n
Engi
n
ee
ring
,
Cloud
Com
puti
ng
and S
igna
l
Proc
essing.
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