Coverage and Capacity Performance Degradation on a Co-Located Network Involving CDMA2000 and WCDMA @1.9GH

Abstract—Coverage and capacity performance in a cellular
network determines the system potentials. If the coverage radius is
limited, end users suffer poor service quality, if the system capacity
reduces, fewer subscribers will be accommodated. This paper
investigated the performance effects of the noise rise caused by the
spurious emission from a co-located jammer involving downlink
frequency of CDMA2000 and uplink frequency of WCDMA
operating at 1.9GHz. Measurements were carried out to evaluate the
impact on the coverage radius and the system capacity.
Keywords—Capacity, Co-location, Coverage, Noise rise.
I. INTRODUCTION
OMMUNICATION technologies are confronted with
various interference challenges which the network
operators must adopt strategies to minimize. The rapid
increase in the number of mobile subscribers due to the
affordable nature of mobile phones necessitated the need for
more base stations to enhance better coverage and improved
quality service delivery. The desire by the network operators
to establish more base stations was further driven by the need
to provide coverage to a geographic region where the service
provider has not previously served; to allow for the reuse of
channels or spectrum bandwidth to support a larger number of
customers and to meet the higher speed requirements of
emerging technologies [1]. The drive to meet these
requirements led to proliferation of new cell towers which are
characterized by its expensive nature; pose environmental
health hazards and distorts the beauty of the environment.
A co-location strategy was introduced by the Nigerian
National Telecommunication Regulatory Body; The National
Communication Commission (NCC) to achieve the outlined
objectives: [2], [3].
• Optimize savings and efficient utilization of capital and
operational expenditure for site infrastructure
development and to achieve improved network coverage
and capacity.
• Ensure that incessant duplication of infrastructure is
minimized to facilitate sharing thereby maximizing the
use of network facilities.
O. C. Nosiri is with the Federal University of Technology, Owerri, Nigeria
(phone: +2348033761852; e-mail: buchinosiri@ gmail.com).
V. E. Idigo, C.O. Ohaneme, and K.A. Akpado are with Nnamdi Azikiwe
University, Awka, Nigeria (e-mail: vicugoo@yahoo.com,
co.ohaneme@unizik.edu.ng, kenakpado@yahoo.com).
This work was supported by research grant from TETFUND
• Promote fair competition through equal access granted to
the installations and facilities of operators on mutually
agreed terms.
• Ensure that new projects and developments should be
catered for the unserved and the underserved areas in line
with the national communication commission’s policy.
Sequel to these needs and developments, new operators
seeking to expand their services in the city by building new
cell sites are besieged and managed by the licensed service
vendors for rent of cell sites and the infrastructure sharing in
the country [4], [5]. The drive in this co-location reform
though has lots of future benefits to the industry; pose quality
service challenges to the network operators. This occurs when
a very strong off channel transmitter noise signal appears at
the input of a receiver in a co-located setting; it reduces the
sensitivity of the receiver with a rise in the total noise floor
depending on the degree of the transmitter noise. This also
could reduce the utilization capacity and the coverage radius,
disfranchising the end users from enjoying their hard paid
services. This paper primarily focused on the effects of noise
rise caused by spurious emission on network coverage and
system capacity.
II. METHODOLOGY
An essential consideration when studying a co-located
network primarily requires frequency band analysis between
the networks of interest. This is to evaluate whether the
frequencies of the networks are adjacent or overlaps. Figs. 1
and 2 show the intended frequency bands of downlink
CDMA2000 and uplink WCDMA networks and the likelihood
of interference occurrence.
Fig. 1 Intended frequency band
O. C. Nosiri, V. E. Idigo, C. O. Ohaneme, K. A. Akpado
Coverage and Capacity Performance Degradation
on a Co-Located Network Involving CDMA2000
and WCDMA @1.9GH
C
World Academy of Science, Engineering and Technology
International Journal of Computer, Information Science and Engineering Vol:8 No:3, 2014
3853
InternationalScienceIndexVol:8,No:3,2014waset.org/publications/9997836

Fig. 2 Interference overview
Fig. 3 shows the spectrum allocation by the International
Telecommunication Union (ITU) [6]. The frequency band
allocation for CDMA 2000 downlink is between 1930-
1990MHz and that of WCDMA uplink is between 1920-1980.
The figure shows that CDMA downlink frequency overlaps
with the WCDMA uplink frequency by 50MHz, therefore, the
CDMA 2000 Tx will interfere UMTS Bs Rx. Considering the
great impact of the interference between the two networks if
co-located, the regulatory body (NCC), rebanded the
frequency between these two networks as shown in Fig. 4.
Therefore, CDMA 2000 downlink new frequency band is
between 1960-1990. From the figure, the PCS Tx band
overlaps 20MHz on WCDMA Rx band. There is no
interference between UMTS Bs Tx and CDMA 2000 Bs Rx
because of wide frequency isolation band. Refer to Table I.
Fig. 3 Spectrum allocation by ITU
Fig. 4 Spectrum Allocation by NCC (After Rebanding)
TABLE I
FREQUENCY SPECTRUM ALLOCATION
Wireless
access
technology
Mobile station
transmitter (Uplink)
(MHz)
Base station
Transmitter
(downlink) (MH)
Duplex
separation
(MHz)
CDMA 2000 1850-1910 1930-1990 80
WCDMA 1920-1980 2110-2170 190
It becomes necessary to establish the significant impacts of
noise rise on the system coverage radius. To obtain this, a link
budget of WCDMA system was conducted on the user
equipment. The analysis was carried out so as to determine the
connectivity of user equipment (UE). A drive test was
conducted using the following instruments: Laptop, UE (Sony
Ericsson Z750i), GPS (Globalsat GPS BU-353).
A NetTek analyzer and YBT250 equipment were also
utilized in the measurement. The analyzer was connected to
the WCDMA sectors under test to measure the received total
wideband power (RTWP) at different transmitting intervals of
the interfering CDMA system. Table II shows the site
parameters and Fig. 5 shows the map of the site measured.
TABLE II
SITE PARAMETERS
Site Name Cell ID PSC Antenna Height Azimuth
UORL001 UORL001_SI 0 22 100
UORL001 UORL001_S2 8 22 220
UORL001 UORL001_S3 16 22 340
UORL002 UORL002_SI 24 24 90
UORL002 UORL002_S2 32 24 220
UORL002 UORL002_SI 40 24 330
Fig. 5 Map showing the measured site
To analyze the measured received data, certain parameters
of importance were calculated by using (1) and (2). These
include; the Noise rise (NR) and load factor )( ULη . Noise rise
is the ratio of the real value of the received total wideband
power (RTWP) to the real value of reference noise power
expressed in dB, while load factor predicts the rise in
background noise due to interference in a radio system.
)(log10)( 10
fv
rv
P
P
dBNR = (1)
3854

where rvP and fvP are real values of RTWP and reference
noise power respectively. The expression between the load
factor )( ULη and Noise rise(NR) is shown in (2).
UL
NR
η−
=
1
1 (2)
A. Analysis of Spurious Impact on Coverage
WCDMA system is interference limited; therefore, system
parameter like coverage is greatly impacted by spurious
emission. Cell coverage of a system reduces when there is
higher load factor of utilization. The uplink capacity is
seriously affected due to noise rise caused by loading from
spurious. A link budget analysis on the WCDMA system was
conducted to determine the connectivity of user equipment.
The system loading ought to be managed such that noise rise,
including all fluctuations due to offered traffic density
variation is kept within the original designed bound. Equation
(3) was used to evaluate the uplink path loss on the WCDMA
system.
jfantmmsenUEpath LGBLPCLNFNRRPL +−−−−−−−= argarg (3)
Lpath is the uplink path loss: PUE is the UE output power: Rsen
is the receiver sensitivity: NR is the noise rise: LNFMarg is the
log-normal fading margin: PCmarg is the power control margin:
BL is the body loss: Gant is the sum of the receiver antenna
gain and UE antenna gain: Lf+j is the loss in feeder and
jumpers (neglected). The Wolfish-Ikegami model in equation
4 was considered which gave better approximate cell coverage
radius from the typical urban area.
))(17log(18log383.155 dBHRL bpath −−+=
(4)
where the coverage radius α
10=R ,
Hence,
38/)]17log(183.155[ −+−= bpath HLα
(5)
The ,pathL α and coverage radius(R) at different levels of
the noise rise were obtained.
B. Analysis of Spurious Impact on Capacity
Providing capacity to keep pace with the explosive growth
in wireless data services is a highly complex task due to
varying terrain and nature of offered traffic. This poses one of
the significant issues of concern during cell planning. If not
checked and properly mitigated, severely compromises
capacity, consuming the design margin intended to
accommodate variations in traffic due to user equipment (UE)
loading.
The capacity of a WCDMA was calculated using load
equation refer to (6), the uplink load factor is due to the
number of subscribers using the system.
W
RiNV
N
Eb
UL
)1(
0
+
=η (6)
The number of users that correspond to specific loading
factor was computed by using (7).
1
])1([ −
+=
o
bUL
N
E
iV
R
W
N
η (7)
ULη is the loading factor due to noise rise: N is the number of
users: V is the activity factor of user at the physical layer: W is
the chip rate of WCDMA: R is the bit rate of the user. It is
obvious that the number of users decreases proportionately
with loading. However, as the system is oblivious of spurious
emission level from an interfering network, the system’s
capacity intended for legitimate users will be suppressed.
III. RESULT AND DISCUSSION
Table III shows the summary of the performance results
obtained from the analysis. Corresponding graphical
representations on the impact of noise rise on the system
capacity and coverage were clearly shown in Figs. 6 to 8. If
the noise rise level increases to 2dB due to spurious, it
signifies 15 subscribers have been cut off with about 33%
capacity reduction. But this increase does not signify user
loading rather it is due to spurious. This change shows the
level of capacity degradation which would have been utilized
by subscribers. The linear degradation of coverage at early
stage of Fig. 7 suggests degradation basically due to user
equipment loading of the system. This corresponds to 75%
loading at 6dB noise rise shown in Fig. 6.
TABLE III
OBTAINED COVERAGE AND CAPACITY DEGRADATION DUE TO NOISE RISE
Noise
Rise
(dB)
LPath
(dB)
%
Load
Factor
Coverage
Radius
(km)
%
Coverage
Degradati
on
Reductio
n in No.
of users
%
Capacity
Reduction
1 151.6 20 2.70 5.9 9 20
2 150.6 37 2.54 11.5 15 33
3 149.6 50 2.39 16.7 21 46
4 148.6 60 2.25 21.4 27 60
6 147.6 75 2.12 30.4 33 73
12 145.6 94 1.88 51.5 42 93
18 139.6 98 1.31 66.5 44 97
22 133.6 99.3 0.91 70.4 45 100
26 131.6 99.5 0.80 79.3 45 100
32 125.6 99.9 0.56 85.6 45 100
The presence of the interfering power from the co-located
jammer significantly reduces the receiver sensitivity with
increase in noise floor other than the original thermal noise
level. This impact give negative effect on the system
performance. It is therefore important to study the system
loading to ensure that all distortions are controlled within the
3855

original design bounds if the site coverage area and capacity
must be maintained.
0 5 10 15 20 25 30 35
20
30
40
50
60
70
80
90
100
Noise Rise (dB)
LoadFactor(%)
Fig. 6 Noise rise and the uplink load factor due to spurious
0 5 10 15 20 25 30 35
20
30
40
50
60
70
80
90
100
Noise Rise (dB)
CapacityReduction(%)
Fig. 7 Effect of Noise rise on the coverage performance
0 5 10 15 20 25 30 35
0
10
20
30
40
50
60
70
80
90
Noise Rise (dB)
CoverageDegradation(%)
Fig. 8 Capacity degradation performance due to spurious emission
IV. CONCLUSION
Detailed performance effects of the spurious emission on
the noise rise, network coverage radius and channel capacity
were clearly evaluated. The results obtained showed that as
the spurious from the interfering system increases, the noise
level increases thereby causing the degradation to be random.
This implies that as noise level rises, the cell radius decreases
causing users who are within the degraded radius area to be
out of service. This interference challenge can be mitigated by
the combination of antenna isolation technique and application
of filters or the use of adaptive noise cancellation technique
depending on the characteristics of the signal.
REFERENCES
[1] O. M. SadiqA.O. Oyelade and C.A. Ukachukwu, “Ten years of
telecommunication infrastructure development in Nigeria”, international
conference on innovation in engineering and technology, August 8-10,
2011.
[2] A. C. Louay, E. Bahjat, H. Ghassan, and M. Mohamad, “Telecom
Infrastructure Sharing: Regulatory Enablers and Economic Benefits,”
Booz Allen Hamilton, 2007.
[3] S. Opara, I. Ituen, “An option for Telecom operators during recession”.
A journal paper, pp 1-2, 2009.
[4] Nigerian Communication Week, the Treat of Multiple Regulations in
Telecommunication. Page 1, Mon, 08, 2012.
[5] NCC ”Guidelines on Collocation and Infrastructure Sharing’ Nigerian
Communications Commission, pp.1-13, 2002.
[6] C. Xinting, “Analysis on co-site interference between different Mobile
Communication system, wireless technical support department, Huawei
Technologies Co. Ltd, p 9, 2008.
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Coverage and Capacity Performance Degradation on a Co-Located Network Involving CDMA2000 and WCDMA @1.9GH

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