Wireless Sensor Network, 2010, 2, 599-605
doi:10.4236/wsn.2010.28071 Published Online August 2010 (http://www.SciRP.org/journal/wsn)
Joint Centralized Power Control and Cell Sectoring for
Interference Management in CDMA Cellular Systems
in a 2D Urban Environment
Mohamad Dosaranian Moghadam1, Hamidreza Bakhshi2, Gholamreza Dadashzadeh2
1Department of Electrical Engineering, Qazvin Islamic Azad University, Qazvin, Iran
2Department of Electrical Engineering, Shahed University, Tehran, Iran
Received May 15, 2010; revised May 26, 2010; accepted June 7, 2010
Abstract
The interference reduction capability of cell sectoring and power control algorithms have been considered
separately as means to decrease the interference in Code Division Multiple Access (CDMA) cellular systems.
In this paper, we present Switched-Beam (SB) and Rotatable Equal Sectoring (RES) techniques for CDMA
cellular systems in a 2D urban environment. In the SB technique by using a number of fixed, independent, or
directional antennas we increase the downlink capacity of the CDMA systems. Also in the RES method, the
equal sectors of the base stations are rotating together to decrease the inter-cell and intra-cell interferences.
Also in this paper we use centralized power control to overcome the near-far problem. Simulation results
indicate that the proposed techniques considerably increase the capacity of the CDMA cellular systems
compared to ordinary Equal Sectoring (ES) method.
Keywords: CDMA, Centralized Power Control, Equal Sectoring, Forward Link, Rotatable Equal Sectoring,
Switched-Beam
1. Introduction
Code-division multiple access (CDMA) for cellular
communication networks requires the implementation of
some forms of adaptive power control. In uplink of
CDMA systems, the maximum number of supportable
users per cell is limited by multipath fading, shadowing,
and near-far effects that cause fluctuations of the re-
ceived power at the base station (BS). Depending on the
location where the decision on how to adjust the trans-
mitted powers is made, the power control algorithms can
be divided into two groups: centralized and distributed
techniques [1-6]. In centralized power control, a network
center can simultaneously compute the optimal power
levels for all users. However, it requires measurement of
all the link gains and the communication overhead be-
tween a network center and base stations [7]. Distributed
power control, on the other hand, uses only local infor-
mation to determine transmitter power levels. It is much
more scalable than centralized power control. However,
transmitter power levels may not be optimal, resulting in
performance degradation [8]. In this paper a centralized
power control algorithm is used to compensate for
near-far effects.
Diversity and power control are two effective tech-
niques for enhancing the signal to interference plus noise
ratio (SINR) for wireless networks. Diversity exploits the
random nature of radio propagation by finding inde-
pendent (or, at least, highly uncorrelated) signal paths for
communication. If one radio path undergoes a deep fade,
another independent path may have a strong signal. By
having more than one path to select from, the SINR at
the receiver can be improved. The diversity scheme can
be divided into three methods: 1) the space diversity; 2)
the time diversity; 3) the frequency diversity [1]. In these
schemes, the same information is first received (or
transmitted) at different locations (or time slots/ fre-
quency bands). After that, these signals are combined to
increase the received SINR. The antenna array is an ex-
ample of the space diversity, which uses a beamformer to
increase the SINR for a particular direction [9,10]. In this
paper we present switched-beam (SB) technique with
antenna arrays in CDMA cellular systems. Also, we
propose a method called rotatable equal sectoring (RES)
This work was funded by the Islamic Azad University of Qazvin, Iran.

M. D. MOGHADAM ET AL. 600
that is as simple as the equal sectoring (ES) method, but
it is able to rotate the sectors based on slow variation of
users’ distribution within a day.
The organization of the remainder of this paper is as
follows. In Section 2, propagation model in a 2D urban
environment and also functional state of urban signal
propagation simulator (USPS) are described. In Section 3,
the system model and formulation are introduced. In
Section 4, we present the RES method. Section 5 de-
scribes the SB technique. Finally, simulation results and
conclusions are given in Sections 6 and 7, respectively.
2. Propagation Model
Because of using 2D urban structure in this paper, for
computing yield for path between base station and a user,
propagation model in urban environments are dramatized.
In a propagation model of urban environments and in
forward link (downlink), base station antenna is radiating
beams which are diffusing in all directions and parts of
beams reach to base station.
In urban environment, delivered beam from base sta-
tion by the time of collision to an obstacle like a wall
surface or a building, reflects to a new angle and contin-
ues its path, this is called reflection phenomena. In con-
dition that radiated beam is conflicted to an obstacle edge,
then diffraction phenomena is happened and diffracting
point is diffusing new beams to all directions like a
transmitter. All reflected beams, will stay in the envi-
ronment till the time their power are not reduced to a
threshold limit. Figure 1 shows both phenomena in for-
ward link and for line of sight (LoS) and non-LoS paths.
In this paper, the software USPS is used to implement
a 2D urban environment [9,11]. We list the propagation
parameters for this simulator in Table 1.
3. System Model and Formulation
3.1. System Model
In this paper, we mainly focus on sectoring in a multi-cell
CDMA system and only the downlink of cellular system
is considered. In multi-cell CDMA systems, a mobile set
in a given sector may be exposed by both interferences its
own base station and surrounding sectors and base sta-
tions.
Our objective here is to find the best sectoring of the
cells at any time, to maximize system capacity and
minimize the total transmitted power for the whole sys-
tem, while at the same time ensuring SINR requirements
for each user. Figure 2 shows an urban area used in our
simulations that is part of Canadian Toronto city. The
area contains five base stations that are used for studying
downlink capacity of the CDMA systems. For simplicity,
Figure 1. Diffraction phenomena and reflection phenomena
(LoS and Non-LoS paths) for a 2D urban environment in
forward link.
Table 1. Propagation parameters in USPS.
Parameter Amount
Resolution 1
Path Loss 0.1 dB/m
Minimum received power in USPS –100 dBm
Figure 2. Part of 2D plane of Canadian Toronto city and
placing five base stations.
we list the notations for this paper in Table 2.
3.2. System Capacity
Consider a CDMA cellular system (see Figure 2) where
each of M base stations use N directional antennas for
signal transmission. The received SINR for the user i in
the sector n from the base station j can be represented by
the signal to interference plus noise ratio ()
,,
SINRijn

M. D. MOGHADAM ET AL.601
Table 2. List of notations.
Symbol Quantity
M
Total number of base stations/cells
N Total number of sectors in ES method
2
n

Noise power

Angle for rotating sectors in RES method
,,ijn

Voice activity of the user (connected to the sector
of the base station
in
j
)
i
G Processing gain of the user . i
, where W is
the total bandwidth and
i
i
/
i
GWR
R
is the bit rate of the user i
,jn
K
Number of users in the cell (base station)
j
and the
sector n
,,ijn
P Transmitted power by the sector of the base station n
j
to the user i

,,ijn
hi Channel gain between the sector of the base station n
j
and the useri
,,ijn

The SINR target of the user (connected to the sector
of the base station
i n
j
)
which is given by [12]
,
,, ,,
,,
2
,, ,,,,,,
1,
()
SINR
()
jn
iijn ijn
ijn K
kjn ijnkjnijnn
kki
Ghi P
hkP I






(1)
where ,,ijn
I
is out-sector and out-cell interference
power for the user i that is in the sector n of the base sta-
tion/cell j and can be shown to be

,
,,,, ,,,,
11 1
,,
()
mn
K
MN
ijnkmn imnkmn
mn k
mn jn
Ih 



 

 kP

(2)
where is the channel gain between the sector
n' of the base station m (connected to the user k) and the
user i (see Figure 3). Let bit rate Ri = R for all users, thus
processing gain for all users is Gi = G (see Table 2).
,, () imn
hk

3.3. Centralized Power Control Algorithm
A major limiting factor for the satisfactory performance
of CDMA systems is the near-far effect. Power control is
an intelligent way of adjusting the transmitted powers in
cellular systems so that the total transmitted power is
minimized, but at the same time, the user SINRs satisfies
the system quality of service (QoS) requirements [13-
15].
The goal of power control in this paper is to find all
with centralized power control technique, such as
the total transmitted power of each base station is mini-
,,ijn
P
Figure 3. Channel gain between base stations and users in
forward link [12].
mized while a certain required QoS is guaranteed for all
users in all cells. This algorithm defines as follows [16].
,
,,
11
;1,...,
jn
K
N
jkjn
nk
PPj


 M (3)
The QoS for the user i in the sector n of the base sta-
tion j can be defined by means of its received SINR as
,
,, ,,
,,
2
,, ,,,,,,
1,
()
()
jn
ijn ijn
ijn
K
kjn ijnkjnijnn
kki
Ghi P
hkP I






(4)
where min, ,maxijn
 

, max

and min

are maximum
and minimum received SINR for each user, respectively.
Without loss of generality, we assume:

,
,,, ,, ,
11 1
,
,,
1()
mn
K
MN
ijnkmn imn
mn k
mn
mn jn
P
I
hk
NK




 







 
where P is maximum transmitted power for each base
station.
Then (4) can be rewritten as
,
,, ,,
,, ,,,,,,
1,
,,
() ()
jn
K
ijn ijn
kjni jnkjni jn
kki
ijn
Ghi PhkP





where ,,ijn

is defined as
2
,, ,,ijn ijnn
I

  (7)
In matrix form, (6) can be expressed as
,,, ,
j
njnjn jn
H(h ,
g
)pn (8)
where
,
,
,1,, ,,
,1,, ,,
[,..., ]
[,..., ]
jn
jn
T
jnjnK jn
T
jnjnK jn
PP



p
n (9)

M. D. MOGHADAM ET AL. 602
are the vectors of the transmitted powers and
out-sector and out-cell interference plus noise power,
respectively. Also in (8),
,1 jn
K
,
j
n
h
()l
is the vector containing
all channel gains for
,,ijn
h, ,1,...,
j
n
il k,,jn

g
, and
,, ,
., ]
jn
T
K jn

1, ,
[ ,..
jn
,,
,,
,,,
,, ,,
() for
[]
() for
ijn
ijn
jnjn il
ljn ijn
Gh iil
hl il







H(h ,g)

,

Using (8), the optimal transmitted powers can be
computed as [16]
1
,,,
[]
j
njnjn

pH(h, jn
g
)n (11)
4. Rotatable Equal Sectoring Method
A way of reducing the interference between users is to
sectoring the cells using directional antennas. While this
approach still utilizes the spatial domain to introduce or-
thogonalization to the system, it is fundamentally differ-
ent than beamforming. Beamforming method combines
the received signals from multiple antennas in a unique
way for each user to suppress the interference that the
user sees. Sectoring merely employs directional antennas
and each users signal is received at only one of these an-
tennas. Since only a subset of the users is received at each
antenna, the interference that each user sees is less com-
pared to a single antenna system. No spatial combiner is
used. While this is a more rigid scheme than beamform-
ing, the simplicity of the resulting receivers is appealing
and sectoring can be quite beneficial especially for static
systems, if the users do not have to handoff from sector to
sector very frequently [14,15].
It has been shown that sectoring increases the number
of users admissible in a system. However under highly
non-uniform traffic loads, conventional sectoring, i.e., ES
method, which divides the cell into equal width sectors
might fail to bring much capacity improvement.
To increase the capacity of CDMA cellular systems, in
this paper, the RES is proposed to reduce rejecting of call
requests in situations like as traffic jams and crowded
hours in entertainment places.
This method is capable of rotating the pattern β de-
grees in each direction, discretely. Hence, there are
360/(βN) possible different states, where N is the number
of sectors for each base station. In the RES method, an-
gle rotation of each base station is chosen such that the
SINR of each user remains between γmin and γmax under
minimizing the transmitted power of each base station.
5. Switched-Beam Technique
One simple alternative to the fully adaptive antenna is
the switched-beam architecture in which the best beam is
chosen from a number of fixed steered beams. Switched-
beam systems are technologically the simplest and can
be implemented by using antenna arrays and or a number
of fixed, independent, or directional antennas [17]. We
list the SB technique conditions for this paper as follows.
1) According to Figure 4, beams coverage angle is 30˚
and overlap between consecutive beams is 20˚. Thus
each base station has 36 beams.
2) Each user can use nmax beams for its each path to
communicate with a base station at any time. In the SB
technique, number of beams is chosen such that SINR of
each user remains between γmin and γmax under minimiz-
ing the transmitted power of each base station. In Figure
5, we show select of beams for three users with the SB
technique for nmax = 2. It should be mentioned that using
nmax = 2 means maximum two beams are paying service
to users in form of unit beam.
6. Simulation Results
In this section we present the simulation results to com-
pare the performance of the RES, SB, and ES methods.
The simulated ES method uses the distribution of users
which can be seen in Figure 6 for pattern configuration
of M = 5 base stations (see Figure 2). Since the ES
method does not change this configuration according to
the changes of the distribution, in some conditions this
method is not able to handle many of call requests. But
in case of using the RES method, we can improve the
performance, as this method rotates the patterns of base
stations according to the distribution of the users at each
moment.
In our simulation, we use the following parameter set-
ting: Total number of base stations M = 5; total number
of sectors in the ES method N = 3 (sector angle is 120˚);
processing gain G = 512; voice activity for all users
1


; noise power 22
n


; angles for rotating sectors
in the RES method β = 10˚ and β = 30˚; maximum
transmitted power for each base station P = 120W; γmax =
9 dB and γmin = 7 dB.
In Figure 7, the number of active users in different
hours of day and night in a day off for the RES, SB, and
ES methods is compared. In such a day, we assume users
are spending their spare time in places such as park,
cinema and sport clubs and are gathered in two different
places and around different hours (around 17 and 22
hours). As you can see especially around mentioned time
in region we face crises, increasing capacity for the RES
method is very considerable in comparison with the ES
method. This increasing capacity for the RES method
and for β = 10˚ is higher than β = 30˚, because the system
has more degrees of freedom. In addition, we see that the
number of active users in mentioned time with the SB

M. D. MOGHADAM ET AL.603
Figure 4. 36 beams in each base station with switched-beam
technique.
Figure 5. Select of beam for three users with switched-beam
technique.
Figure 6. Distribution of users in the ES method.
technique is higher than the RES and ES methods, be-
cause in the SB technique the interference is lower than
the RES and ES methods. It should be mentioned that
increasing the number of active users in the SB technique,
will lead more complexity in receiver in comparison with
the RES and ES methods. Also it can be seen that the
number of active users with the SB technique for nmax =
3 is higher than the other cases (nmax = 1, nmax = 2).
Figure 8 shows the comparison of the number of ac-
tive users in different hours of a day and night in a
working day for the RES, SB, and ES methods. This
study is assumed where highest user demands for con-
centration on conversation are happened around 7.30,
12.30 and 16.30 (starting and finishing times for educa-
tional centres, offices, and …). Similar to Figure 7, we
observe that the number of active users in the RES
method is much higher than the ES method and also is
lower than the SB technique. Also it can be seen that the
number of users in the RES method and for β = 10˚ is
higher than β = 30˚.
Figure 7. Number of active users (Normalized) for the RES,
SB, and ES methods in a day off.
Figure 8. Number of active users (Normalized) for the RES,
SB, and ES methods on a working day.
Figure 9. The average of active users (Normalized) for the
RES, SB, and ES methods in a day off.

M. D. MOGHADAM ET AL. 604
Figure 10. Percentage of improvement in the system capac-
ity in the SB technique versus the RES and ES methods in a
day off.
Figure 9 shows the average of active users in different
hours of a day and night in a day off for the RES, SB,
and ES methods (see Figure 7). Accordingly, we ob-
serve that the number of users in mentioned hours is paid
services by the RES method which is much higher than
the ES method. It is noticed that with β = 10˚, the RES
method has better performance than β = 30˚. Also ob-
serve that the average of the number of active users in
the SB technique is higher than the RES and ES methods.
Also it can be seen that the number of users in the SB
technique for nmax = 3 is higher than the other cases.
Figure 10 shows the percentage of improvement in the
system capacity for the SB technique versus the RES and
ES methods in a day off (see Figure 7). For example, in
around 22 hour, the number of users allowed in the sys-
tem for the SB technique and for nmax = 3 increases by
approximately 41.5% in comparison with the ES method,
while versus the RES method and for β = 30˚ and β = 10˚
can provide a capacity increment 25% and 21.5%, re-
spectively.
7. Conclusions
In this paper we propose the switched-beam and ro-
tatable equal sectoring techniques that are suitable to
increase the capacity of a multi-cell CDMA system. In
the SB technique, each user can use nmax beams for its
each path to communicate with a base station at any time.
Also the RES method is discretely capable of rotating the
pattern β degrees in each direction. In both techniques,
number of beams and angle rotation of each base station
are chosen such that SINR of each user remains between
γmin and γmax under minimizing the transmitted power of
each base station. Simulation results indicated that be-
sides the RES method has the simplicity of the ES
method, it increases the capacity of the CDMA cellular
systems compared to the ES method. It has also observed
that using the SB technique will increase the number of
active users and complexity of receiver compared to the
RES and ES methods.
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