Performance Evaluation and Optimization of CDMA 2000 1X ...

International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 4, April 2014)

328

Performance Evaluation and Optimization of CDMA 2000 1X

Mobile Cellular Radio Network Idigo V.E.

1, Ohaneme C.O.

2, Oguejiofor O.S.

3, Ezeagwu C.O.

4

1,2,3,4 Department of Electronic and Computer Engineering, Nnamdi Azikiwe University Awka, Nigeria

Abstract-- Evaluation and optimization exercise after

service rollout is to correct the expected errors in network

planning and to achieve benefits such as improved network

capacity, enhanced coverage and quality of service. The key

performance indicators viz; call drop ratio, call setup success

ratio, call failure rate, call connection rate that have direct

impact on the subscribers on the network were collated and

analyzed using the industrial best practice values as

benchmark for the exercise. Visafone, an independent mobile

network operator with CDMA access technology at

Maiduguri, North-East Nigeria is used as case study. To

eliminate any existing faults in transmission and installation,

drive tests were carried out and analysis of the traffic

statistics made. Network optimization is then implemented.

The results show that after optimization process, the key

performance indicators were greatly improved.

Keywords-- Call drop, Evaluation, Optimization, Success

ratio, Network coverage.

I. INTRODUCTION

Cellular network operators must periodically evaluate

and optimize their networks to accommodate traffic

growth and performance degradation. Network

performance evaluation and optimization action after

service rollout is to correct the expected errors in

network planning and the benefits like improved

network capacity, enhanced coverage and quality of

service.[1]

Wireless network optimization is the major challenge to

every wireless communication system. The classical

cellular architecture provides only rough guidelines,

propagation modeling and statistics, and network

simulations fall short of representing and optimizing the

actual network performance[2]. Cost effective wireless

network optimization governs the radio coverage at the

base stations and additional RF access points as

required by the environmental and traffic demands.

Optimal performance is achieved by combining

prediction models with dynamic measurements and

applying coverage and diversity means accordingly.

Some research efforts in the past had tried to show

that the optimization of the antennae parameters would

be able to yield some capacity improvements,

however poor handling of this operation or insufficient

tilt will result in high level of inter-cell interference

thereby reducing the capacity of the network, and

ultimately the network operators could end up paying

for unnecessary network infrastructure[3].

Some previous works are reported on the combined

effects of radio interface parameter and network

performance indicator at real data [1, 7]. Some work

investigates individual as well as combined effects of

antenna height, high gain antennas and antenna down

tilting for microcellular applications [1]. Using simulations,

the authors show in [2] that the smaller the cell sizes the

larger the antenna down tilt should be, and the higher the

traffic load the higher the antenna down-tilt should be to

improve performance. While the inter-cell interference is

indeed reduced through such down tilt, the sectorization

efficiency may also be reduced with increased down tilt

[3]. Another study finds that optimization of pilot powers

in a CDMA-1X system does not increase the performance

of the system significantly and substantial reduction in

capacity can be associated with pilot power optimization.

However the optimization of the antenna parameters is able

to yield substantial capacity improvements [4]. Recently,

[5] discussed antenna down tilt concepts and performance

in an actual operating cellular system, relationship between

antenna height, down tilt angle, and coverage radius. In

modern urban propagation environments, the cell coverage

area is less than 2 km, it concluded.

The tradeoff between the coverage and number of users

with fixed transmit power is as presented in [6].

More recent work, has examined the impact of

interference, such as, the problem of where to locate base

stations so as to maximize user capacity in a cellular

CDMA network is studied in [7,8].

The impact of intra-cell and average inter-cell

interference using power-control constraints is captured.



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All these efforts had not actually resulted into the

desired capacity and coverage enhancements due to these

obvious limitations.

RF coverage on the forward link is much larger than

that in the reverse link because excessive BTS power

is allocated to the remote user.

Excessive soft handoff area caused by improper cell

site layout and misuse of base station antennas.

Improper RF parameter settings, as this needs to be

fine tuned according to the traffic loading distribution.

However this research effort attempts to bridge these

limitations through the following contributions.

Link imbalance can be identified by drive testing into

problematic areas or analyzing the network

performance data for problematic clusters/sectors.

Unnecessary soft handoff could be reduced.

Maiduguri network of Visafone communications

limited, a privately owned and nationally licensed

telecommunications operator that started commercial

operations in Nigeria in February 2008 using the

CDMA technology platform is the network under

study. Maiduguri, which is the capital city of Borno

state, situated in the North East geopolitical zone of

the country, with a beautiful flat terrain, is one of the

latest cities Visafone has rolled out services with

sixteen Base station transceiver station (BTS) sites. The

BTS sites are connected to the Kano Base station

controller (BSC) via 16E1 leased fibre link. The scope

of this research work includes checking, uploading and

analysis of transmission alarms, Received Signal

Strength Indicator (RSSI), Frame Error Rate (FER), and

other traffic statistics data from the M2000 and the

LMT from all the operational BTS in Maiduguri. For

acquisition of initial knowledge of network quality,

and to eliminate any existing faults in transmission

and installation. Drive tests were carried out and

analysis of the traffic statistics made, and the network

optimization was then implemented at a higher level

using the various techniques.

II. EVALUATION AND OPTIMIZATION APPROACHES

Optimization process begins with monitoring, collection

of data, and the performance of maintenance functions on

the BTS at the far-end, using the Local Maintenance

Terminal (LMT) which is connected to the BSC BAM,

known as a client and Back LMT Administrator Module

(BAM) known as a server.

The BTS Audit is also required to see the real condition

and quality of the whole of the device - the device BTS by

reference the actual parameter values, because sometimes

the values obtained from monitoring (far-end) is far

different from the direct measurements performed on the

field. The drive test data collection requires post-

processing of data analysis, and finally the tuning of the

network is needed to solve problems of RF coverage. Drive

test is performed again to validate the earlier actions taken.

A. Drive Test Exercise

During the drive test, the following tools were used;

Agilent E6474A, drive test equipment such as a laptop unit

that has installed software for the Agilent CDMA, GPS,

two fruit headset (for the long call and short call), power

supply, Agilent hardware devices, and street map site.

Drive test procedure itself was divided into three levels

namely:

Single-cell function tests: Done to test individual base

stations.

Cluster Optimization: Done for testing multiple base

stations in a single cluster and the performance of good

relationship between the BTS.

System Optimization: Done to test a wider network

performance, e.g. in some clusters.

Drive Test are done on several conditions [9]:

Initial test drives conducted when an installed base

station have been completed to determine the initial

data of a BTS and also to demonstrate the feasibility

of a network level.

Maintenance drive test conducted in order to monitor

the performance of the BTS in accordance with the

schedule.

Executed for these necessary reasons, i.e. if there

were complaints from customers or impairment of

performance of base stations as can be seen from the

daily reports.

In some places drive test data uses Actix analyzer

software. Actix analyzer software is useful for processing

drive test data, visualize data, analyze the data and can

identify network problems for subsequent resolution.



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III. RESEARCH METHODOLOGY

A. Research Concept

This research work is categorized as a network

planning, optimization and evaluation effort whose

focus is to evaluate the performance of a mobile

cellular radio network in terms of coverage, capacity

and quality, before and after the optimization exercise.

This would have been preceded by the network

planning stage where the various models are analyzed.

The key radio parameters that determine network

performance, namely Tx level (transmit power), Rx level

(receive power), Ec/Io of the primary pilot, FFER

values, and RSSI values are collated and evaluated

The Ec/Io of the primary pilot and the Rx level are

used to define the forward coverage range of the

system. The transmit power of the MS is used to

measure the reverse coverage range. The mean FFER

of the forward link is used to determine the quality of

the traffic channel. The key performance indicators

namely, call drop ratio, call setup success ratio, call

failure rate, call connection rate, that have direct

impact on the subscribers on the network were

collated and evaluated using the industrial best practice

values as benchmark for the exercise [8].

B. Experimental Test Bed

Following the need for the coverage of Maiduguri city in

Nigeria, 16 BTS sites were built by Visafone, with the

intention of creating a good CDMA Tx network in the city.

The BTS configurations are S1/1/1; with frequency point of

419 in the 800MHz band. The 16BTS sites are connected to

the Kano BSC, which is one of the nine BSC locations of

Visafone, via a 16E1 capacity fibre link. The list of the on-

air sites, their co-ordinates and configurations are listed in

Table 1.

Table 1

List of On-Air Sites

Source: Visafone Nigeria

Table 2:

Antenna Adjustment Proposal



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C. Sampling Technique

Recently, new sites were installed in Maiduguri. After

installation, it was decided that Drive Test (DT) should be

carried out to determine the performance of the sites and to

proffer solution should any coverage problem be

discovered in the network.

The Drive Test was carried out as decided, but certain

areas of the network proved to have poor network

coverage. Hence, optimization was suggested to improve

the network, with antenna adjustment plan as shown in the

Table 2

Note: Black stands for values BEFORE OPTIMIZATION

Red stands for values AFTER OPTIMIZATION.

D. Research Method and Test Route

Install a set of drive test equipment with GPS and

Qualcomm 1X test mobile station into the test car. Besides,

a compatible computer installed with collection software

(Pilot Panorama). Set the two Mobile stations to the status

of Markov long call and short call respectively at full rate.

MS is used to test Transmit Level (Tx Level), Receive level

(Rx Level) and Down link Pilot (Ec/Io) of the primary

pilot. The Ec/Io of the primary pilot and Rx level are used

to define the forward coverage range of the system.

The transmit power of the MS is used to measure the

reverse coverage range.

The mean FFER of forward link which is used to

determine the quality of the traffic channel was determined.

IV. RESULTS AND DATA ANALYSIS

The data were collated through the drive test, before and

after the network optimization exercise .These were

processed with the drive test tool, Dingli Panorama and the

output was produced in the form of distribution charts and

maps and subsequently analyzed to lay credence to the set

objectives of the study. This result was compared with the

simulation output produced by the simulation software,

Tems cell Planner. These outputs of the examined network

optimization metrics include, Ec/Io, Rx level, Tx level,

FFER, Call drop, PN Plot, Short call statistics.

A. Ec/Io Coverage

Areas around MAD016 and MAD 002 had poor

coverage due to GPS antenna tracking problem of

MAD0016 and MAD002 coupled with some sites with

RSSI problems. However, after optimization, all these

snags were cleared and the city has excellent Ec/Io

coverage. As shown by statistics in Figure 1, Total Ec/Io

greater than -9dB was 91.51%, before optimization.

However, after optimization, as shown in Figure 2, the

value came to 95.08%, which is a remarkable improvement

over the previous value for the network.

Figure 1: Maiduguri Visafone Network Distribution map



332

Figure 2: Ec/Io distribution chart before optimization

Figure 3: Ec/Io distribution chart after optimization

B. Rx Level Coverage

Areas around MAD 016, MAD 002 and MAD011 had

poor coverage. But after optimization, Rx Level has

improved in the affected areas.

Figure 4 shows that Rx level above -90dBm was

14.47%, before optimization. However, after optimization

Rx level above -90dBm came to 19.55%, which is an

improvement over the previous values as shown in figure 5



333

Figure 4: Rx Level distribution chart before optimization

Figure 5: Rx Level distribution chart after optimization

C. Tx Level Coverage

The Tx distribution in most areas is good except for the

area around MAD 016, which is at the edge of the

coverage. However, after optimization, the Tx improved

significantly in this area.

Figure 6 shows that Tx level below 0 was 3.63% before

optimization. However, as shown in figure 7, after

optimization Tx level below 0 came to 5.87%, which is a

good improvement over the previous value.



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Figure 6: Tx level distribution before optimization

Figure 7: Tx level distribution after optimization

D. FFER Coverage

The quality of the network measured by FFER was poor

in areas around MAD 016 and MAD 002. Figure 8 and

Figure 9 reveal that the value of FFER value lower than

2% was 9.81%.

But after optimization, the value came to 10.14%, which

is a good improvement over the initial value.



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Figure 8: FFER distribution histogram after optimization

Figure 9: FFER distribution histogram before optimization

E. Call Drop Analysis Long Call

Before optimization, call drops featured at the center of

the city, as well as at areas toward the edges of the network

due to GPS tracking problem on some sites.

However, no call drops featured in these areas and the

rest of the network after optimization.



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Short Call Statistics

In Table 3 and Table 4 there is an improvement after the

optimization in the Call Setup success ratio and call drops.

Table 3:

Short call statistics before optimization

Table 4:

Short Call Statistics after optimization

V. ANALYSIS OF SIMULATION RESULT

A. Downlink Received Power

Figure 10 shows the total mean received RF power over

a carrier’s bandwidth, found by adding the received pilot

powers, common channel powers, traffic channel powers

and background noise at any pixel. The value at each pixel

is obtained by averaging the total received powers of the

terminals attempted at a pixel. In the plot, different colours

are applied to identify the different strength level of the

Mean Received Power. For example, the Green represents

the Received Power level between -80dBm and -70dBm.In

CDMA system, downlink coverage effect lies on both DL

Received Power and Pilot Ec/Io. For example, with the

increase of user, the strength of Received Power will be

stronger, while the strength of Pilot Ec/Io will decrease.

Only if both of them satisfy the coverage threshold, the

downlink coverage effect could be ensured well. The

outdoor coverage threshold of Received Power is -

105dBm; meanwhile in this simulation, there is 5dB-fading

margin to obligate for 75% edge coverage probability,

which means in the area where the Received Power is

greater than -100dBm the outdoor edge coverage of

downlink can be satisfied with a probability of 75%.

Moreover, here we set the penetration loss of buildings as

20dB, so the indoor coverage threshold of Received power

is -80dBm. As shown in the plot, the Received Power in the

areas except orange, yellow is greater than -80dBm, so the

downlink indoor coverage in these areas can be satisfied.

[10]

B. The Uplink (UL) Required MS Transmit Power

Figure 11 shows the mean uplink required Tx Power at

each pixel for the selected service. In the plot, different

colours are applied to identify the different strength level of

UL Mobile Transmit Power. For example, the green

represents the UL Transmit Power level between -22dBm

and -12dBm. The outdoor coverage threshold of the UL

Mobile Transmit Power is 23dBm; meanwhile in this

simulation there is 5dB-fading margin to obligate for 75%

edge coverage probability that means in the area where the

UL Mobile Transmit Power is less than 18dBm the uplink

outdoor edge coverage can be satisfied with a probability of

75%. Moreover, here we set the penetration loss of

buildings as 20dB, so the indoor coverage threshold of UL

Transmit Power is -2dBm. As shown in the plot, the UL

Transmit Power in the red, orange, yellow, green, blue area

is less than -2dBm, so the uplink indoor coverage in these

areas can be satisfied.

C. The Downlink (DL) Pilot Ec/Io

The Pilot Ec/Io figure 12 displays the achieved pilot

Ec/Io for each pixel and is in effect, the same as Ec/Io for

the first best server. In the plot, different colours are

applied to identify the different level of DL Pilot Ec/Io. For

example, the Green represents the Pilot Ec/Io level between

-9dB and -7dB.

In CDMA system, the T drop threshold is –13dB, which

is to say that when the Pilot Ec/Io level is below this

threshold, the DL coverage can’t be satisfied; and when the

DL Pilot Ec/Io level is below –11dB, the DL coverage

effect may be not good. As shown in the plot, the Pilot

Ec/Io in the pink, blue, green, yellow, orange area is greater

than –13dB, so the downlink outdoor coverage in these

areas can be satisfied; and the pilot coverage effect in the

pink, blue, green area, yellow is good.



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Figure 10: Downlink simulation

Fig 11: Uplink simulation



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Fig 12: DL Pilot E0/I0 Simulation

VI. CONCLUSION

The optimization process is a long term process that

requires the study of the network situation and the

provision of solutions to weak features sorted out first,

without a hasty implementation, for a successful outcome.

The antenna hardware changes (tilt and azimuth) are

important issue in the network optimization, as it is

observed that most times the advised changes are not

correct. The load on the system increases with time and

thus affecting the network performance, hence the need to

periodically monitor the carrier loads, and expand the

network if necessary. Interference affects network capacity

and the overall performance and quality of end user

experience (call setup, call drop rate, etc) and these are

considered key issues that need to be resolved. Network

planning must be based on standard value to predict the

demand services area and QoS. It is important to know the

network layout and QoS before implementing optimization

procedure. There are radio elements to use as check to

adjust the parameters to enhance the QoS. The threshold

values of the parameters must be used as performance

indicators to effect radio interface optimization. Knowing

the radio interface protocols of cdma2000 1x is essential

for radio interface optimization. The function of channels

in setup call and the messaging can provide one with the

reasons behind higher call setup failure and also high call

drop rate.

REFERENCES

[1] Edward B., and Abu S., 2004, “Effects of Antenna Height, Antenna Gain and Pattern Down tilting for Cellular Mobile Radio”,

Proceedings of IEEE Infocom.

[2] George C., and Matt D., 2006, “Antenna tilt control in CDMA Networks”, Motorola Inc.

[3] 3GPP2 C.S0010-B, 2002, “Recommended Minimum Performance Standards for CDMA 2000 Spread Spectrum Base Stations”, Vol.

4.0.

[4] 3GPP2 C.S0011-B, 2002, “Recommended Minimum Performance Standards for CDMA 2000 Spread Spectrum Mobile Stations”,

Vol.4.0.

[5] <www.tektronix.com/signaling_test, June 2003. “CDMA Network

Technologies: A Decade of Advances and Challenges”.

[6] Esmael D., and Aleksey K., January 2006. “The Impacts of Antenna Azimuth and Tilt Installation Accuracy on UMTS Network

Performance”, Bechtel Corporation.

[7] Myron D. Fanton, April 2006. “Antenna Pattern and Coverage

Optimization”, PE ERI Technical Series, Vol. 6

[8] Joseph Shapira, Nov. 2004. “Enhancement and Optimal Utilization of CDMA 2000 Networks”. CEWIT CDMA Workshop.

[9] Dingli Communications Inc, August 2004. “Pilot Panorama User Guide”.

[10] Robert AKL, 2006, “Subscriber Maximization in CDMA Cellular Networks”, Department of Computer Science and Engineering,

University of North Texas, CCCT04



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Authors’ Profile

Idigo Victor Eze is an Associate Professor and lecturer with the

Department of Electronic and Computer Engineering, Nnamdi

Azikiwe University Awka Nigeria. He holds Ph.D. in

Communication Engineering from Nnamdi Azikiwe University,

Awka, Nigeria. He has published many papers in both local and

international journal. He has also presented papers in both local

and international conferences. Idigo is currently the head of the

department of Electronic and Computer Engineering of the

institution, and a member in many professional bodies including

IEEE and COREN as in Nigeria. His research interest is on

Wireless and Mobile Communication Systems.

Ohaneme Cletus Ogbonna holds B.Eng. and M.Eng. in

Electrical/Electronic Engineering Communication Engineering

option, and PhD in Communication Engineering, all from Enugu

State University of Science and Technology (ESUT) Enugu,

Nigeria. He is currently a lecturer with the Department of

Electronic and Computer Engineering, Nnamdi Azikiwe

University, Awka Nigeria. Also, he is a member of several

professional bodies, some of which include: Nigeria Society of

Engineers (NSE), Nigeria Institution of Electrical Electronic

Engineers (NIEEE), International Association of Engineers

(IAENG) and a registered engineer with Council for the

Regulation of Engineers in Nigeria (COREN). His research

interest is on Wireless Communication and Spectrum

Management.

Oguejiofor Obinna Samuel is currently a lecturer with the

Department of Electronic and Computer Engineering, Nnamdi

Azikiwe University Awka Nigeria. He holds B.Eng. and M.Eng.

in Electronic and Computer Engineering (Communication

Engineering Option) from Nnamdi Azikiwe University Awka,

Nigeria and presently pursuing his Ph.D. Degree in

Communication Engineering from the same department and

institution. His research interest is on Wireless Communication

and Wireless Sensor Network.

Christopher Ogwugwuam Ezeagwu was born in Ezi, Aniocha

Local Government Area of Delta State Nigeria. He holds B.Eng.

in Electrical/Electronic Engineering and M.Eng. in Electronic and

Communication Engineering both from Enugu State University of

Science and Technology (ESUT) Enugu, Nigeria in 1986, and

2008 respectively. Currently, he is a PhD student in the

department of Electrical/Electronic Engineering, Enugu State

University of Science and Technology (ESUT) Enugu, Nigeria.

Christopher is presently a lecturer in the Department of Electronic

and Computer Engineering Nnamdi Azikiwe University, Awka

Nigeria. Besides, he is a member of several professional bodies

including, Nigeria Society of Engineers (NSE) , Member

Institution of Electrical and Electronic Engineers (IEEE), Fellow

Institute of Chartered Administration (ICA) of Nigeria and

Council for the Regulation of Engineering in Nigeria (COREN).

E-mail: [email protected]

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