JOURNAL OF RESEARCH IN NATIONAL DEVELOPMENT VOLUME 8 NO 2, DECEMBER, 2010
IMPROVING WCDMA NETWOTK CAPACITY USING ADAPTIVE SECTORISATION
J.N. Dike, S.I
Orakwue and Edward O. F
Department of
Electrical and Electronic Engineering, University
of Port Harcourt, Nigeria
Email:
edlarry4u@yahoo.com,
edyodesa@yahoo.com
Abstract
A major problem affecting the capacity of
Wideband Code Division Multiple Access (WCDMA) is
interference.
This
work focuses
on reducing cochannel interference problem by
the application
of adaptive sectorisation
in
nonuniform
traffic. It considers
an
isolated
areas
of
congested
traffic
called Hot
Spots (HS). It
is
envisaged
that
the
traffic
density inside a HS
is many more times that
outside the HS. A more
even
traffic
distribution among sectors
is attempted
by readjustment
of sector
boundaries
using
finite
antenna
beam
switching.
System
capacity
is
estimated
on
the basis
of
tolerable
interference
in a
sector
taking
into
account
intrasector
and
intersector
interference
in a multicell environment. Perfect
power control
in
the
uplink is assumed.
Path
losses and
shadowing
losses
is considered. It
is
shown
that a significant
improvement
in
system
capacity
could
be
obtained with
adaptive
sectorisation.
Keywords:
Interference, WCDMA, sectorisation, antenna beam
Introduction
WCDMA
is the radio interface
for
the present
day third
generation cellular
mobile
communication
systems.
The
capacity
of a WCDMA
cellular
system is
determined
by
the
amount
of
interference
it
can
tolerate
Giuliano, .
Mazzenga
and Vatalaro ( 2001). This
interference is in
two forms. The
interference arising
from
other
traffic in
the
same
cell
and
the
interference
arriving
from
traffic
in
nearby
cells. If
the
traffic
could
be
redistributed
among
cells
so
as
to
minimize
the
overall
interference in a
given
cell
more
traffic
can
be
accepted
in that
cell.
In a
sectorised cell,
the
redistribution
of
traffic
could
be
achieved
by
adaptive
sectorisation.
This
paper looks at the
capacity
of a WCDMA
system
where
the
user
distribution
consists
of
high
density
pockets
called
Hot
Spots
(HS). A
HS
is
formed
by
the
gathering
of many
users in a
small
area.
In
this
study,
the
user
densities
(within
and
outside
the
HS)
are
assumed
to
be
uniform
although
the
user
density
inside
the
HS
is
much
higher
than
the
user
density outside
the
HS.
The
user
density
ratio
in
these
two
regions
is
taken
as a
parameter that
reflects
the
traffic
environment.
Use
of
adaptive
sectorisation to
minimize
the
total
received
and
transmitted
power
by
all
users
has
been
studied
in
Saraydar and
Yener (1999).
Adaptive
sector
control
using
Butler
matrix
fed
circular
array
is
given
in
Mahmoudi,
et
al. (1999)
and
the
impact
of
sectorisation on WCDMA
network
is
discussed
in
Wacker,
et
al.(1999). These
works
have
assumed
ideal
antenna
characteristics
and
thus
the
noninterference between
sectors.
Giuliano
et
al.
(2001)
have
considered the
use
of
adaptive
sectorisation
in
WCDMA
systems
to
enhance
capacity
in a
HS
environment.
Their
study
is
based
on
the
rotation
of
sectors to
share the
hot
spots among
the
adjacent sectors.
The
approach
used in
this
investigation to
improve
cell
capacity
is to
employ
adaptive
sectorisation.
The
sector
coverage
in a
cell
can
be
controlled
by
the
use
of
antenna
structures
that
allow finite
beam switching.
Finite
width
beams
are
combined
to
cover
an
area
of a
cell
that
is
divided
into
three
sectors.
Sectors
could
be
adjusted
in such a
way
that a
given
sector
covers a
HS
either
fully
or
partially. The finite
antenna
beam
switching
provides a
simple
and
robust
technique
for
sector boundary
adjustment.
System model
For this paper,
the
system
model
considers
only
the first tier
of cochannel
interfering cells,
which
means
that
there
are
six cochannel
interfering
(adjacent)
cells.
Therefore,
the geometry
of
the
interference
model can
be
represented
as
shown
in
Figure
1.
The
interference
from
second
and
third
tiers
to
the
home
cell
is
extremely
small Chung and
Wen(1998),
and
thus
is
ignored.
In
Figure 1
home
cell A consists
of sector
A1 ,
A2
,
and
A3
of
which
A1
is
the
home
sector
where
the
HS
is located.
A2
and
A3
are
adjacent
sectors,
and
B1, B2
, B3
,
C1,
C2 ,
and
C3
are
nearby
sectors
from
which the home
sector may
receive
interference.
It
is
assumed
that
the
users
in
each
sector,
including
those in
home
sector,
are
uniformly distributed.
However,
the
traffic
density
in
the
HS
region
(Figure
1)
is
several
times
higher
than
that
outside
the
HS.
In
this
investigation the
mobility
characteristics
of
users
are
ignored.
Cells are
assumed
to
be
hexagonal
in
shape
and
identical in
size.
Propagation model
The
signal
propagation
in
the
mobile
channel
(when
fast
fading
is
ignored)
is
generally
modeled
as a
product
of
three
components,
one
inversely
proportional to a
power
of
the
distance
representing the
path
loss,
the
second a
random
variable
with
lognormal
distribution
representing the
shadowing
losses,
and the
third
representing
the
directional
antenna
gain
Viterbi et. al(1994)
and Gilhousen et al.(1991).
The
shadowing
represents slow
variations
in signal
strength
even
for
mobile
users.
On
the
other
hand,
fast
fading,
which
is
largely
due
to
multipath
propagation,
can
be
assumed
to
have no
effect
in
the
average
signal
power
level
Viterbi et. al(1994). Hence,
for a
user
at a
distance r
from a
Base
Station
(BS)
at an angle θ
as
in
Figure
1,
the
total propagation
path loss
is a
function
of
r,
ζ ,
and A(θ ),
given
by
PL(r,ζ
,θ
)
=
r
−n
·
10ζ/10
· A(θ
),
(1)
where A(θ )
is
the
antenna
gain in
the
direction
of
mobile
station
(MS),
and n
is
the
propagation path
loss
exponent
which
typically
has a
value
of
4. ζ
is a
random
variable
with
normal
distribution,
(10ζ/10
represents
the
lognormal
shadowing
process).
Due
to
shadowing
the
local
mean
of
signal
power fluctuates
around the
area
mean
with
lognormal
distribution,
and
the standard
deviation
σ
of this
distribution
generally
varies
between 6
dB
and
12
dB
and
has
Figure
1.
Geometry
of
the system model for
interference
evaluation.
A
typical
value
of 8
dB.
In
order
for a
BS
to
be
the
most
favorable
to a MS
the
PL(r,ζ
,θ )
with respect
to that
BS
must
be
smaller
than
the
PL(r,ζ
,θ )
with
respect to
all other BSs Chatovich and
Jabbari (1994).
Adaptive
antenna
array
factor
In
applications
such
as
cellular
mobile
systems,
where
adaptive
sectorisation
is
required,
there
is a
need
for
the
down
link
beam
to
scan
in
different
directions in
the
azimuth
and
two
of
the
most
common
scanning
techniques
used
are
the
mechanical
scanning
and
the
electronic
scanning.
In
case
of
mechanical
scanning,
the
array
can
be
rotated
mechanically
through
360◦
to
give
allround
coverage
and
can
be
adopted
when
the
rotating
structure
is
not
too
large.
In other
cases electronic
scanning
is preferred.
The
main beam
of an
antenna array
consisting of several
equally
spaced
elements
points
in a
direction θs
to
the
array
normal
when
the
phase
difference
between adjacent
elements
is
given
by Connor (1989).
β
= k
·
d
·
sin θs
,
(2)
where k
=
2π
/λ
(λ
is
the
free
space
wave
length)
and d
is
the
spacing
between
adjacent elements.
Thus,
by
varying
the
phase
difference β
the
beam
can
be
steered
through
various
directions. However,
it
is
to
be
noted
that
for
an
element
spacing
of
about
half
wavelength,beam
steering
is restricted
to
about ±60◦
to
avoid
grating lobes.
Since
the
Array
Factor
of a
linear
array
of N
elements
is
given
by
N
−1
AF(θ )
=
∑
exp
[j
·
n(k
·
d · sin θ
+
β)],
(3)
n=0
Figure
2.
(a) Antenna element radiation
pattern (RFS). (b) Array
factor (superimposed for θs
=
45◦
, 15◦,
–15◦
and (–45◦). (c) Resultant
pattern (superimposed for θs
= (45◦, 15◦,
–15◦
, and
–45◦
).
When
element
spacing is
λ/2,
substituting (2)
into
(3), we
have,
N
−1
AF(θ )
=
∑
exp
[j
·
n ·
π ·
(sin
θ +
sin
θs
)],
(4)
n=0
where
0◦
≤ θ
≤
360◦
and θs
=
[45◦
,
15◦
,
−15◦,
−45◦
].
If A(θ )
represents the
radiation
pattern
of a
single
element
of
the
array,
the
resultant
Antenna
Pattern
AP(θ )
is
found
by
pattern
multiplication
(i.e.,
as
the
product of
A(θ )
and
AF(θ
))
AP(θ
)
= A(θ )
·
AF(θ ) .
(5)
By
varying
the
element
spacing
d
and/or
the
phase
difference
β
between
element
excitations, the
array
factor
and
the
resultant array
pattern can
be
varied.
Figure
2(a)
shows
the
radiation
pattern
of a
single
element
of
the
antenna
array
.
Figure
2(b)
shows
the
antenna
array patterns
corresponding
to
main
beam
directions
45◦,
15◦ ,−15◦
and −45◦.
Figure
2(c)
gives
the
resultant
antenna
pattern
obtained
by
pattern
multiplication. Each
element
of
the
antenna array
is a
λ/2
dipole
and
the
array spacing and
the
phase of
feed
current
are
controlled to
obtain
the
desired
radiation
pattern.
It
can
be
seen
that
the
main beam
can
be
steered to
cover a
desired part of a sector.
Adaptive
sector
control
We
consider a
BS
antenna
structure
that
consists
of
twelve fixed
30◦
beams
per
cell.
The
narrow
beams
are
combined
to
obtain 3
composite
beams,
which
would
substitute
for
the
beams
provided
by
the
normal
120◦
directional antenna.
Next,
keeping
the
number
of
sectors fixed
at 3
per
cell,
we
may
adaptively
change
the sector
size
by
combining
an
appropriate
number
of
narrow
beams
(Figure
1).
Obviously,
each
sector
acts
like a
cell
with
it
is
own
pilot
signal
and
the
softer
handover
is
responsible
for
switching
the
users
from
one
sector
to another.
The
adaptive
sectorisation allows
sector
beamwidths
to
be
approximately
30,
60,
90,
120,
150, 180,
or
210
degrees.
Switched
beams
can
adjust
the
sector
size
to
include
either
fully
or
partially an
area
of
high
user
density,
that is,
Hot
Spot
(HS).
By
using
adaptive
beam
switching the traffic
can
be shifted
from heavily
loaded
HS
sectors to
sectors that
are
underutilized.
System
capacity evaluation
Sectorised
cell
capacity
In
this
analysis we
assume that
perfect
power control
is
in
place in
the uplink.
This mean
that
the
signal
strength S
received
by a
sector
BS
due
to
the
presence
of a MS
in
the
sector
is the
same
for
every MS
in
the
sector,
and
is
true
for
all
sectors.
Then
the
received
Signalto
Interference
Ratio (SIR)
at a
sector
BS
can
be
expressed
as,
S

S

η,
(6
where
Iintra
is
the
interference occurring
within
the
sector,
Iinter
is
the
interference arriving
from neighbouring
sectors,
and η
is
the
background thermal
noise.
If
Ni
is
the
number
of users
in
the sector,
Iintra=(Ni−1)S.
(7)
To
evaluate
Iinter
consider a MS situated
in
the
nearby sector B1
(Figure
1). The
intercell interference by mobile station (MS)
located outside the home cell is influence by the
position (distance and angular orientation) of the
MS. As shown above, in fig. 1 the distance r from
its respective controlling base station, BS, and r_{o}
from the home cell base station, BS_{o}
depicts the geometry of this situation. The
intercell interference on the reverse link (with
perfect power control) can be expressed as
=
(8)
Where n is propagation loss exponent, r is the
distance of the MS from its own base station, BS_{1},
r_{o} is the distance of the MS from the
home cell base station, BS to and
are
random variables representing the lognormal
shadowing process in neighbor cell and home cell
respectively.
The total interference power received at the home
cell base station, BS_{0} due to users in
the interfering cell can be found as
Iinter =2
(9)
The SIR of reverse link can be found by
substituting equation 7 and 9 into 6
(10)
Table 4.2
Simulation Parameter
Data
rate, Rb
9.6kbps
Chip rate, W
1.2288Mcps
Required Eb/No
7.4db
Standar deviation of shadow fadind, d
8dB
Cell radius, R
1km
Reverse link SIRth
13.6dB
Number
of sector N
3
System
access
When
an MS
chooses
to
access a
certain
sector’s
BS,
the
sector’s
BS
will
check
whether
the prevailing
SIR
is
greater
than
the
minimum
(threshold) value
required.
If the
SIR
is
less
than
the
threshold
the MS
is
blocked.
This
threshold
value,
SIRth,
is a
function
of
Eb
/N0
and
the
system
Processing
Gain
(PG)
and
is
given
by
SIRth[dB] =
Eb
/N0
[dB]−
PG
(dB).
The
Eb
/N0
required
in a WCDMA
system
is
about
7.4
dB
if
the
biterror
rate is
not
to
exceed
10− Chung
et al. 1998.
The
SIRth
based
algorithm
for call
admission
is a
distributed
mechanism Chung et
al. 1998.
It
can
be
used
by
each
sector’s
BS
to
determine
whether
or
not a
sector
admits a
call.
If
SIR >
SIRth
the
call
request
is
accepted.
Otherwise,
the
call
request
is
rejected.
Therefore,
the
call
blocking
probability
is
given
by,
Pb
=
Pr{SIR ≤
SIRth} .
(13)
System simulation
The
number
of
users
the
system
can
support
is
evaluated
using a
computer
simulation
according
to
(13).
The
simulation
is based
on
the
system parameters
shown
in
Table
1.
The
HS
is
in
the
home
sector
A1
(Figure
1)
(which
therefore
is also
called
the
Hot
Spot
Sector
(HSS))
and
the
HSS
can
vary
from
30◦
to
120◦
in
steps
of
30◦.
In
this
investigation
we
consider
a case where
Hot
Spot
Area
(HSA)
is
completely
inside
the
HSS .
In
both
cases
it
is
assumed
that
the
HSA
is
confined
to a
strip
of dimension L × W
where W
is
the
arc
width
of the
HS
and L
is
its
radial
length.
The
cell
radii
in
all
scenarios
are normalized
to
unity
and
the
conventional
hexagonal
cell pattern
is
assumed.
Perfect
power
control
is
also
assumed
so
that
the
received
power
at
the
sector’s
BS
from
all
mobiles
within
the
sector
is
the
same. A
uniformly
distributed
mobile
population is
generated
with
random
locations
within
the
home
and
the
six
nearby
sectors.
This
is
done
by
generating two
sets
of
random
numbers
that
assign
an
angular
position
and a radial
distance
to
each
mobile.
The
radial
position
is
the
distance
of
the MS
from
the
home
BS.
The individual
path
losses
(coupled
with
the
shadowing
effect)
are
calculated
for
each MS in
order
to
evaluate
the
SIR
at the
sector
BS.
The
system capacity
is
evaluated
in
terms
of possible
number
of
users in
each
sector
when at
most
1%
new
call
blocking
is
experienced
in
any
of
the
sectors.
The
cell
capacity
is the
sum
of
three sector
capacities.
The
simulation
starts with
empty
system
(no users
any
where)
and
proceeds
by
adding
users progressively,
one
user
at a
time,
positioning each
user
at a
randomly
selected
location
in
each
sector
and
in
HS
region.
Every
time a
user
is
added
(any
where
in
the
system)
the
SIR
at the
BSs
of
all
sectors are
evaluated
to
see
that
with
the
added
user the
system
blocking
probability
does
not
exceed
the
stipulated value. When
the
blocking
probability
exceeds
the
stipulated value
the
simulation
terminates
and
the
number
of
users
in
each
sector
and
the
sector
causing
the
simulation
termination
are
noted
Case of per fec t antenna
The
case
of a
perfect
antenna
serves
as a
reference
to examine
the
system
under
ideal
conditions
and
to
compare
it
with
the
practical
case.
The
sector
coverage
in
this
case
(with
perfect
antenna)
is
assumed
to
be
uniform
over
the
entire
sector and
there
is
no
spillover of
main
lobe
or
occurrence of
side lobes
in
the
radiation
pattern.
Where W
=
20
◦
Figure 3
shows
the
results
for
the
case
of
perfect
antenna
for a
blocking
probability
of
1%,
in
the
overall
system.
As
mentioned
earlier,
in
Figure
1,
A1
is
the
HSS,
A2
and
A3
are
the
adjacent sectors,
and B1 , B2 , B3,
C1,
C2,
C3
are
the
nearby
sectors.
In the
absence
of
HSs
there
is
uniform
traffic
in
every
cell
(HS
to
nonHS
user
density
ratio
is
1)
and
the
system
offers a
traffic
capacity
of 34
users/sector.
This
is
taken
as
the
reference.
The
results
(Figure
3) indicate
that when
all
sectors
are of
the
same
size
(i.e.,
A1
=
120◦
),
the
possible
number
of users
in hot
spot
sector
A1
increases
with
increasing
user
density
in
HS
while
the
possible
number
of
users
in
adjacent (A2
or
A3 )
and
nearby
(B1
,
C1,..
.)
sectors
decreases
with increasing
user
density
in HS.
Simulation
shows
that
in
this
situation
blocking always
occurs
first
in
A1 .
This
is
in
contrast
to
the
situation
when A1
is
60◦
or
30◦.
In
these
cases
blocking first
occurs
in
the
adjacent
sectors
(A2
or
A3 )
and
then
moves
to
A1
as
the
HS
to
nonHS
user density
ratio
reaches 5
and
10,
respectively.
The
system
capacity
(per
cell)
can
be
obtained
at a
give
HS
to
nonHS
user
density
ratio
by
summing
up
the
number
of
users
in
each
sector.
Figure 5
illustrates this
situation
and shows
the
cell
capacity
as a
function
of HS
to
nonHS
user
density
ratio.
It
can
be
seen
that
there
is
an
overall
capacity
improvement
which
starts
at a
user
density
ratio
of
about 5,
and
reaches a
maximum
value
of
about
37%
of
the
nominal
capacity
at a
user density ratio
of
about
15.
Figure
3.
Sector
capacity
versus
hotspot
to
nonhot
spot
user
density ratio (Case
1, W
=
20◦ ) (case
of
perfect antenna).
It shows
that
the
overall
capacity
improvement
in
this
case
starts
to
occur
at a
user
density
ratio
of
about 2
and
it
reaches
about
60%
of
the
nominal
capacity
at a
user
density
ratio of
about
12.
Conclusion
In
this investigation we reviewed the basic concepts
underlying cellular wireless communication systems
in order to bring the issue of capacity in WCDMA
cellular systems to the forefront. In particular,
we considered the case of capacity improvement in
cellular
WCDMA systems when nonuniform user
distributions (hot spots) are involved in the
coverage area.
The system capacity was estimated in terms of the
number of users the cell (or sector) could
accommodate while providing an acceptable quality
of service. The quality of service is measured in
terms of the system blocking probability which in
turn reflects the acceptable
signaltointerference ratio. In order to
calculate the interference arising in the system
we considered a sectorised multicell model, with
a hot spot located in the home sector, and the
rest of the mobile population evenly distributed
in the neighbor sectors. In calculating
interference at sector BSs, both intra and inter
sector interference were taken into account. The
random locations of the mobile users in home and
neighbor sectors and the normal radio signal
propagation environment, including pathloss and
slow fading (shadowing) were considered.
Studied was the possibility of using adaptive sectorisation as a means of reducing interference in sectors where it appears crucial in a bid to increase the overall capacity of the system. It was found achievable. It was also found that the adaptive sectorisation could be easily implemented using finite antenna beam switching, and for that purpose practical array antennas could be employed. The capacity improvement obtainable with adaptive sectorisation (in the presence of hot spots) is a function of user density in the