SlideShare a Scribd company logo
1 of 8
Download to read offline
29
Factors Affecting QoS in Tanzania Cellular
Networks
Adam B. Mtaho and Fredrick R. Ishengoma
School of Informatics and Virtual Education, The University of Dodoma, Tanzania
Abhassigiye@yahoo.co.uk, fishengoma@udom.ac.tz
Abstract
Quality of service (QoS) in cellular communication system is a topic that recently has raised much interest
for many researchers. This paper presents the findings obtained from the study on factors affecting QoS in
Tanzania cellular networks. The study was carried out in Dodoma Municipal, Tanzania. The study
employed cross-sectional research design. Information was gathered from structured questionnaire of 240
subscribers during the study of quality of service for the four leading cellular networks in Tanzania
(Vodacom, Airtel, Tigo and Zantel). Both qualitative and quantitative data from field survey were collected
and analyzed using Statistical Package for Social Sciences (SPSS-version 11) and Excel software. The
study findings show that the major factors that degrade QoS in Tanzania cellular networks are inadequate
network infrastructure, lack of fairness from service providers and little efforts taken by the government in
enforcing the national agreed standards. Other factors are lack of reliable end-to-end systems, geographical
terrain, low quality handsets, poor government monitoring on standards and lack of subscriber’s skills and
training.
Keywords: Cellular networks, Network coverage, Network capacity, Quality of Service
I. Introduction
The cellular communication services in Tanzania were introduced after the liberalization of the
communication sector in 1993. Since then, a number of subscribers and vendors have been
increasing. Tanzania Communication Regulatory Authority (TCRA) statistics as of September
2013, indicates that the mobile telephone market is the fastest growing sector, with more than 26
million subscribers in a population of about 43 million, of which Vodacom is leading with, about
10 million subscribers, followed by Airtel 8.7 million, Tigo 6.2 million, and Zantel 1.7 million
(TCRA, 2013).
Quality of Service (QoS) refers to the effect of service performance that defines the level of a
user’s satisfaction with the service. The Tanzania Communications QoS Regulations clearly
recommends measuring the QoS provided in cellular networks from time to time and comparing
them with the norms so as to assess the level of performance. Several factors affect the quality
of services in cellular networks. However, so far, very little is known about the QoS in cellular
networks in the country. This paper therefore examines factors that affect QoS in Tanzania
cellular networks.
30
The rest of the paper is organized as follows: We start by providing an overview of cellular
networks in section 2. Section 3explains the study methodology used. Section 4 presents data
collection and data analysis. Study findings are presented in Section 5. We conclude in Section 6
along with recommendation for future practice.
II. Overview of Cellular Networks
Cellular communications worldwide has experienced a rapid growth in the past two decades.
Cellular phones allow a person to make and receive a call from almost everyplace through a
given network. Also, cellular networks enable a person in motion to continue with phone
conversation. Cellular communication is supported by an infrastructure called a cellular
network, which integrates cellular phones into the Public Switched Telephone Network (PSTN)
(Zhang and Stojmenovic, 2005). Apart from voice service, cellular telephony provides a number
of services to the users. Such services include Short Message Services (SMS), Instant Messaging
(IM), and Multimedia Messaging (MMS). SMS allows a subscriber to send and receive text
message using the mobile terminal. IM is a short message exchanged between mobile users in
real time while MMS allows users to send pictures, video or voice to other mobile terminals or
an electronic mail account. Other services include e-mail services, wireless Internet, emergence
calls, video services and mobile TV (Pashtan, 2006). A cellular network provides cell phones or
mobile stations (MSs), with wireless access to PSTN (Zhang and Stojmenovic, 2005)
A. Essential Elements of a Cellular Networks
Mobile Stations(MS) essentially enables a user uses to make communication. The MS is made
up of two parts, the handset and Subscriber Identity Module (SIM), whose major function is to
store data for both the operator and subscriber (Mishra, 2004). The service coverage area of a
cellular network is divided into several smaller areas, referred to as cells, each of which is served
by a base station (BS or BTS). The BS is fixed, and it is connected to the Mobile Telephone
Switching Office (MTSO), also known as the Mobile Switching Center (MSC). An MTSO is in
charge of a cluster of BSs and it is, in turn, connected to the PSTN (Zhang and Stojmenovic,
2005). For GSM network, BTS is then connected to MSC via the Base Station Controller (BSC).
The BSC main function is usually to handle radio resource management and handovers of the
calls from one BTS (or cell/sector) to another BTS equipped in it (Mishra, 2004). With the
wireless link between the BTS and MS, MSs are able to communicate with wire line phones in
the PSTN. Both BSs and MSs are equipped with a transceiver. Figure 1 illustrates a typical
cellular network, in which a cell is represented by a hexagon and a BS is represented by triangle.
31
Figure. 1. Typical cellular network (Source: Zhang, J. and Stojmenovic, I., 2005)
A cellular network is a network that divides a geographic area into cells such that the same radio
frequency (RF) can be reused in two cells that are a certain distance apart (Zhang and
Stojmenovic, 2005). The cellular network operates based on the frequency reuse concept, which
offers very high capacity in a limited spectrum allocation. Each BTS is allocated a segment of
the total number of channels available to the entire system, and nearby BTS are assigned non-
overlapping channel sets. All available channels are later assigned to a relatively small number
of neighboring BTSs. The BTS is then used within a small geographic area called a cell. In this
way these few available channels are distributed throughout the geographic region and may be
reused as many times as necessary, hence providing effective utilization of frequency while
providing adequate network coverage within the area (Rappaport, 2002).
When the demand for service increases due to increase of subscribers, the number of BTSs may
be increased, so as to increase the corresponding number of channels. This provides additional
radio. Some of the features that determine cellular network performance are network coverage
and capacity. Both capacity and coverage have direct impact on QoS. Network coverage refers to
the maximum allowed distance from which the MS can be reliably connected to the nearby BTS
(Mishra, 2004). Network capacity on other hand refers to the maximum number of subscribers a
given BTS can cater at a given time. The higher the capacity, the more the number of subscribers
who can be allowed to access cellular service at a given time (Mishra, 2004).
III. Study Methodology
A. Study Location and Justification for Its Selection
The study was conducted in Dodoma Municipal, Tanzania. Dodoma Municipal was selected
because it is a rapidly growing town that needs reliable cellular communication services for its
sustainable growth. Moreover in this municipality all four leading cellular networks in Tanzania
(Airtel, Tigo, Vodacom and Zantel) are present. The study employed the cross-sectional research
32
design, whereby data was collected among six institutions in Dodoma Municipal. Information
from structured questionnaire of 240 students’ subscribers, six key informants and observation
was collected to assess the quality of network performance and online customer service.
B. Sampling Procedures
a. Population
The population from which the sample was drawn for this study involved subscribers who are
getting cellular communication services from the four cellular networks present in Dodoma
(Tigo, Vodacom, Zantel and Airtel). The sampling frame was a students’ subscriber from six
higher learning institutions namely: College of Business Education (CBE), Institute of Rural
Development Planning (IRDP), The University of Dodoma – College of Informatics and Virtual
Education (CIVE), The University of Dodoma – College of Health and Social Science (CHSS),
The University of Dodoma – College of Education (CoED) and St.John’s University of Tanzania
(SJUT) in Dodoma Municipal.
b. Sample Size and Sampling Technique
According to the Department of Research and Consultancy of the Dodoma Municipal, Dodoma
Municipal has the total population of 507,141 people. In order to get the sample size the
researcher adopted the formula that has been developed by Yamena (1967).
=
(1 + ( )2)
Where − Sample Size, − Total Population, − Detection error expressed into percentage
(5% − 10%), and thus from = 507,141, = 6.74%,
=
507,141
(1 + 507,141
.
2)
= 220 Respondents
That means, according to Yamena (1967) the respondents were not required to be less than 220.
In order to make the research manageable, the sample size of 240 subscribers from six higher
learning institutions was involved in this study. The 240 respondents were selected by employing
purposive sampling technique. The specific criterion for selecting respondents was; being student
subscriber who lives and study at the given institution.
Later, 40 respondents were randomly selected from each educational institution using simple
random sampling procedure to make a total of 240 respondents. Furthermore, six key informants
(two site engineers, one frequency engineer and three cellular network engineers) were
interviewed using a checklist. Selection of the key informants was based on the experience in
working in cellular networks industry. It was logically assumed that the sample represented the
whole population of mobile subscribers in Tanzania.
33
IV. Data Collection and Data Analysis
In this study, for primary data, structured questionnaires, in-depth interview, and observation
were used as primary data collection instruments while documentary review were used for the
collection of the secondary data. Both qualitative and quantitative data from field survey were
collected and analyzed using Statistical Package for Social Sciences (SPSS-version 11) and
Excel software program. Data were first coded in the form suitable for addressing research
questions and the method of analysis to be employed. The analysis of the recorded and
summarized data from key informants used ethnographic approach; that is relying on the direct
information given by respondents according to the check list used during the discussion.
V. Study Findings
A. Factors that Affects the QoS in Tanzania Cellular Networks
Several factors that affect QoS in Tanzania cellular networks were identified during the study.
Among the factors pointed out to affect QoS by customers include limited coverage and
capacity, poor government monitoring on standards and lack of skills and training on the use of
mobile phones. Other factors include lack of fairness from service providers, low quality
handsets and delay in allocation of adequate network infrastructure. Further, geographical terrain
and lack of reliable end-to-end systems were pointed by telecommunication engineering
professionals to affect QoS in cellular networks.Figure 2 below presents the size and percentage
response of customers on the factors that affect QoS in Tanzania cellular networks.
Figure. 2.Response of customers on the factors affecting QoS in Tanzania cellular networks.
Figure 2 shows a number of factors that degrade the QoS in Tanzania cellular networks. These
factors are discussed as follows:
a. Limited Network Coverage and Capacity
Lack of adequate network coverage and capacity are the leading causes that affect QoS in
Tanzania cellular networks as it was evidenced by 45% of the total responses. The study found
that network infrastructure is available mainly in urban areas and limited in rural areas.
According to Tanzania’s Infrastructure report (2010), only 65 percent of the Tanzania population
8%
5%
18%
45%
17%
7%
Factors Affec ng QoS in Tanzania Cellular Networks
Low quality handset
Delay in alloca on of adequate
network infrastructure
Lack of fairness from service providers
Limited coverage and capacity
Poor government monitoring on
standards
Lack of skills and training on the use
of mobile phones
34
lives within the range of a GSM signal, compared with over 90 percent in neighboring Kenya
and Uganda. This indicates that network coverage in Tanzania is still inadequate.
The study found that despite having moderate network coverage in urban areas, the network
capacity is still limited. For example, despite having more than 23, 000 subscribers at UDOM
area has only three BTS. This makes an average of about 7500 subscribers per single BTS. This
number is too large for one BTS. It does nor matter which capacity improvement techniques is
used. The study found that network related problems (such as network outage and call dropout)
are among the reasons why subscribers own more than one SIM cards. According to the
findings, 44.6% of subscriber complained about network related problems to be the main causes
for subscribers owning more than one SIM card from different operators. Since QoS in cellular
networks depends mainly on network coverage and capacity (Mishra, 2004), inadequate network
coverage and low network capacity contributes to degradation of QoS in Tanzania cellular
networks.
b. Lack of Skills and Training
Lack of skills and training on using mobile phones is another cause that affects QoS as it was
evidenced by 7% of the total responses. Using mobile phone requires knowledge and ability to
properly follow the procedures. For example, the study found that some of subscribers do not
charge the phones to their full capacity. Improper charging of the battery limits its life span. Lack
of such knowledge can compromise the quality of the handset. The handset can be easily
susceptible to call drop out and network outage problems if its battery strength is weak. The
study found that some of the subscribers do not know how to effectively use mobile phones.
Most of the mobile handsets are configured to operate in English or other foreign languages,
while majority of Tanzanians understand Kiswahili. Respondents pointed out this problem as the
source of difficulty in using mobile phone. Improper knowledge of how to buy good quality
phones was also reported to be the major bottleneck towards aching effective QoS. This is
because poor quality handsets suffer from voice quality degradation (Mishra, 2007)
c. Poor Government Monitoring on Standards
Poor government monitoring on standards is another cause that affects QoS as it was evidenced
by 17% of the total responses. The study found that despite there being national standards,
operators are following their own standards. For instance, a caller in Airtel network may get
informed about the time and amount of money spent instantly after finishing the call. Vodacom
and Tigo networks do not give such information. This implies that Airtel subscribers can easily
verify the bills of their calls. The study found that operators use the same standards for few
services such as using the same dialing code to request online customer care (code 100 is used),
air balance inquiry and air time recharging.
d. Lack of Fairness from Service Providers
Lack of fairness from service providers is reported to be another barrier towards achieving
effective QoS in cellular networks. 18% of the total responses pointed out that providers were
sometimes unfair to the customers. For example, the study found that if a call drops out due to
network problems, the service provider does not pay the user for the loss incurred.
35
The International Telecommunication Union (ITU) recommends that to ensure service level
quality, service level agreement (SLA) must be included in contractual agreements between
customers and service providers. This includes tariffs and billing, network performance, and
compensation for unachieved level of service quality. The study found that SLA is not practiced
in Tanzania. For example, registration in cellular networks service does not include SLA
between mobile subscriber and service providers. In other words, the customer is neither
guaranteed by the provider to get high quality service nor assured to be compensated if the
normal service quality level is not achieved. Lack of SLA between the operator and subscriber
therefore affects QoS.
Lack of clear information about the service provided by network operators is another example
that shows how operators are unfair to their customers. For example the study found that
subscribers are always told to subscribe to the caller tune service. However, subscribers are not
informed how to unsubscribe from this service. As reported by Materu and Dyamett (2010),
subscribers are instructed to subscribe i.e. to join with new services, but they are not informed or
taught how to unsubscribe. According to Tanzania Communications (QoS) Regulations, 2005,
service providers must ensure that customers are provided with information about the services
that they provide, so as to enable them to make decision. However, the study found that such rule
is not effectively followed by operators.
e. LowQuality Handsets
In response to the factors affecting the QoS in cellular networks, the lack of handsets with good
quality was one of the complaints. This contributed 8% of the total responses. Low quality
handsets affect the QoS. Usually handsets that receive low network signal uses more power to
remain connected, than the handset near the BTS (Mishra, 2004). According to Ditech Networks
(2011), in CDMA networks, the use of inexpensive low quality handsets allows hybrid and
acoustic echoes; resulting degraded service quality. It is therefore recommended to have mobile
phone with good quality.
f. Delay in Allocation of Adequate Network Infrastructure
Delay in allocation of BTSs is another problem. It contributes 5% of the total responses. The
respondents pointed out that operators have been delaying to introduce new BTSs despite the
rapid increase of customers in the area. It was pointed out by the respondents that the increase of
subscribers does not match with the increase of BTSs. For example, the study found that there
are only three BTSs serving the population of about of 23000 subscribers at UDOM. This makes
an average of 7500 subscribers per BTS. This number is too large to be accommodated by a
single BTS. The study found that operators delay to increase number of BTS regardless of the
rising demand due to high investment and running cost of the equipment.
g. Geographical Terrain
Geographical terrain was pointed by cellular network engineers to be one of the variables that
affect the QoS. It was stated that around Dodoma Municipal there are hills and mountains. Radio
waves require direct line of sight from BTS to BTS. Presence of hills and mountains create
obstacles and prevents signal of one BTS from reaching another BTS or BSC. This problem
degrades QoS and affects both network coverage, and capacity. Presence of hills and mountains
in Dodoma municipals were pointed out by cellular network engineers to bring difficulties
36
during network planning. For example, the study found the Vodacom BTS at UDOM, which is
positioned about 9 kilometers from the BSC is linked with the BSC via another BTS at Kisasa
(about 12 Km from UDOM). Redirection of UDOM BTS was done to avoid unfavorable signal
propagation caused by obstacles due to the hilly terrain along the UDOM area.
h. Lack of Reliable End to End Systems
Relaying on radio link as the major connection between BSC and MSC was pointed out by site
and frequency engineers to be another factor that affects QoS in cellular networks. Despite the
introduction of fiber optic cable by SEACOM in July 2009, cellular networks in Tanzania still
use radio link as the primary media for signal transmission from BSC to MSC. Radio link suffers
from limited throughput and electromagnetic interferences from other sources. Interference cause
noise, call drop and call set up failure. However, the study found that Vodacom is cellular
network operator in Tanzania who currently uses fiber optic to link BSC and MSC as an alternate
to radio link.
VI. Conclusions
In this paper, we presented the factors that affect the Quality of Service in Tanzania cellular
networks. Some factors that were identified to be the contributors of poor QoS in Tanzania
cellular networks includes; limited network coverage and capacity, inadequate network
infrastructure, lack of fairness from service providers and little efforts taken by the government
in enforcing the national agreed standards. The study recommends TCRA to ensure that the
established standards are met and followed by operators. Further, telecomm operators in the
country are advised to improve network coverage and provide reliable and fair services to
customers.
References
i. Africa Infrastructures, Country Diagnostic (2010), Tanzania’s Infrastructure, Country Report, The World
Bank, 1818H Street, NW, Washington DC, 20433, USA.
ii. Ditech Networks (2011), Wireless/Mobile Voice Quality,
[http://www.ditechnetworks.com/solutions/wirelessSol.html], site visited on January 2014
iii. Materu B.M et al. (2010), Tanzania ICT Sector Performance Review 2009/2010, Towards Evidence-based
ICT Policy and Regulation, Vol. 2, No. 11.
iv. Mishra, A.R., (2004), Fundamentals of Cellular Network planning & Optimization, John Willey & Sons
Ltd, the Atrium, Southern Gate, Chichester,West Sussex Po19 8sq, England.
v. Mishra, A.R., (2007), Advanced Cellular Network Planning and Optimization, 2G/2.5G/3G, Evolution to
4G, John Wiley & Sons Ltd, the Atrium, Southern Gate, Chichester,West Sussex Po19 8sq, England.
vi. Mtaho A.B.et al. (2011). Analysis Of Quality Of Service in Tanzania Cellular Networks, A Case Of
Dodoma Municipal, Journal of Informatics and Virtual Education (JIVE), Vol.1 No.1.
vii. Pashtan, A. (2006), Wireless Terrestrial Communications, Cellular Telephony, Aware Networks, Inc.,
Buffalo grove, Illinois, USA, Eolss Publishers.
viii. Rappaport, T.S.(2002), Wireless Communications: Principles and Practice, 2nd
Edition, New Jersey,
Prentice Hall.
ix. Tanzania Communication Regulatory Authority (TCRA), (2013), 2013 Quarterly Statistics Reports.
x. Yamena, T., (1967),Statistics, an Introductory Analysis, 2nd
Edition, Harper and Ran, New York.
xi. Zhang, J et al. (2005), Cellular Networks, Handbook on Information Security (H. Bidgoli, ed.), Wiley, Vol.
I, Part 2, 654-663.

More Related Content

What's hot

Using SMS to Transfer Small Data Packets During (SBRC), 2015
Using SMS to Transfer Small Data Packets During (SBRC), 2015Using SMS to Transfer Small Data Packets During (SBRC), 2015
Using SMS to Transfer Small Data Packets During (SBRC), 2015
Carlos Malab
 
Iaetsd evaluation ofdma & sc-ofdma performance on
Iaetsd evaluation ofdma & sc-ofdma performance onIaetsd evaluation ofdma & sc-ofdma performance on
Iaetsd evaluation ofdma & sc-ofdma performance on
Iaetsd Iaetsd
 
120428665 (Complete Project-Final)
120428665 (Complete Project-Final)120428665 (Complete Project-Final)
120428665 (Complete Project-Final)
OSMAN SHEIKH
 
A Master of ScienceProject Report Optical cmms-oaa516
A Master of ScienceProject Report Optical cmms-oaa516A Master of ScienceProject Report Optical cmms-oaa516
A Master of ScienceProject Report Optical cmms-oaa516
Olufisayo Adekile
 
GSM report summer training
GSM report summer trainingGSM report summer training
GSM report summer training
Atul Sharma
 

What's hot (17)

Ieee paper mobile boadband
Ieee paper mobile boadbandIeee paper mobile boadband
Ieee paper mobile boadband
 
Site specific assessment of node b using key service quality indicators over ...
Site specific assessment of node b using key service quality indicators over ...Site specific assessment of node b using key service quality indicators over ...
Site specific assessment of node b using key service quality indicators over ...
 
Using SMS to Transfer Small Data Packets During (SBRC), 2015
Using SMS to Transfer Small Data Packets During (SBRC), 2015Using SMS to Transfer Small Data Packets During (SBRC), 2015
Using SMS to Transfer Small Data Packets During (SBRC), 2015
 
Mobile data offloading
Mobile data offloadingMobile data offloading
Mobile data offloading
 
Cc
CcCc
Cc
 
A WIRELESS NETWORK INFRASTRUCTURE ARCHITECTURE FOR RURAL COMMUNITIES
A WIRELESS NETWORK INFRASTRUCTURE ARCHITECTURE FOR RURAL COMMUNITIESA WIRELESS NETWORK INFRASTRUCTURE ARCHITECTURE FOR RURAL COMMUNITIES
A WIRELESS NETWORK INFRASTRUCTURE ARCHITECTURE FOR RURAL COMMUNITIES
 
Significance of public priorities from telecommunication to cellular communic...
Significance of public priorities from telecommunication to cellular communic...Significance of public priorities from telecommunication to cellular communic...
Significance of public priorities from telecommunication to cellular communic...
 
Internet Access Using Ethernet over PDH Technology for Remote Area
Internet Access Using Ethernet over PDH Technology for Remote AreaInternet Access Using Ethernet over PDH Technology for Remote Area
Internet Access Using Ethernet over PDH Technology for Remote Area
 
Interference Aware & SINR Estimation in Femtocell Networks
Interference Aware & SINR Estimation in Femtocell NetworksInterference Aware & SINR Estimation in Femtocell Networks
Interference Aware & SINR Estimation in Femtocell Networks
 
Optimization Technologies for Low-Bandwidth Networks
Optimization Technologies for Low-Bandwidth NetworksOptimization Technologies for Low-Bandwidth Networks
Optimization Technologies for Low-Bandwidth Networks
 
Sms based event notification system
  Sms based event notification system  Sms based event notification system
Sms based event notification system
 
Iaetsd evaluation ofdma & sc-ofdma performance on
Iaetsd evaluation ofdma & sc-ofdma performance onIaetsd evaluation ofdma & sc-ofdma performance on
Iaetsd evaluation ofdma & sc-ofdma performance on
 
IRJET- Research on Dynamic Spectrum Allocation
IRJET- Research on Dynamic Spectrum AllocationIRJET- Research on Dynamic Spectrum Allocation
IRJET- Research on Dynamic Spectrum Allocation
 
120428665 (Complete Project-Final)
120428665 (Complete Project-Final)120428665 (Complete Project-Final)
120428665 (Complete Project-Final)
 
A Master of ScienceProject Report Optical cmms-oaa516
A Master of ScienceProject Report Optical cmms-oaa516A Master of ScienceProject Report Optical cmms-oaa516
A Master of ScienceProject Report Optical cmms-oaa516
 
National Optical Fibre Network - A Review of the Pilot Blocks
National Optical Fibre Network - A Review of the Pilot BlocksNational Optical Fibre Network - A Review of the Pilot Blocks
National Optical Fibre Network - A Review of the Pilot Blocks
 
GSM report summer training
GSM report summer trainingGSM report summer training
GSM report summer training
 

Viewers also liked

Chapter 6
Chapter 6Chapter 6
Chapter 6
detjen
 
Dakotas Parent Meeting Presentation
Dakotas Parent Meeting PresentationDakotas Parent Meeting Presentation
Dakotas Parent Meeting Presentation
Paul OBriant
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
detjen
 
Arte a medio dibujar
Arte a medio dibujarArte a medio dibujar
Arte a medio dibujar
maugepe
 
Chapter 13
Chapter 13Chapter 13
Chapter 13
detjen
 
Drucker chapter 3
Drucker chapter 3Drucker chapter 3
Drucker chapter 3
detjen
 
Deploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalitiesDeploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalities
Fredrick Ishengoma
 
Collaborative archietyped for ipv4
Collaborative archietyped for ipv4Collaborative archietyped for ipv4
Collaborative archietyped for ipv4
Fredrick Ishengoma
 
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File SystemFredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma
 

Viewers also liked (19)

Chapter 6
Chapter 6Chapter 6
Chapter 6
 
Plenary Session - Technology and the Church
Plenary Session - Technology and the ChurchPlenary Session - Technology and the Church
Plenary Session - Technology and the Church
 
Dakotas Parent Meeting Presentation
Dakotas Parent Meeting PresentationDakotas Parent Meeting Presentation
Dakotas Parent Meeting Presentation
 
Luxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - BertoloLuxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - Bertolo
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
 
Arte a medio dibujar
Arte a medio dibujarArte a medio dibujar
Arte a medio dibujar
 
Online resources
Online resourcesOnline resources
Online resources
 
Online landscape
Online landscapeOnline landscape
Online landscape
 
Chapter 13
Chapter 13Chapter 13
Chapter 13
 
Cyber safety, technology and the church
Cyber safety, technology and the churchCyber safety, technology and the church
Cyber safety, technology and the church
 
Drucker chapter 3
Drucker chapter 3Drucker chapter 3
Drucker chapter 3
 
Deploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalitiesDeploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalities
 
Collaborative archietyped for ipv4
Collaborative archietyped for ipv4Collaborative archietyped for ipv4
Collaborative archietyped for ipv4
 
Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing C...
Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing C...Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing C...
Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing C...
 
Online safety
Online safetyOnline safety
Online safety
 
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
 
Using tech safely
Using tech safelyUsing tech safely
Using tech safely
 
Staying safe online
Staying safe onlineStaying safe online
Staying safe online
 
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File SystemFredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
 

Similar to Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular Networks

Comparative Study on Mobile Switching Center of Mobile Generations
Comparative Study on Mobile Switching Center of Mobile GenerationsComparative Study on Mobile Switching Center of Mobile Generations
Comparative Study on Mobile Switching Center of Mobile Generations
ijtsrd
 
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
pijans
 
Performance analysis of massive multiple input multiple output for high speed...
Performance analysis of massive multiple input multiple output for high speed...Performance analysis of massive multiple input multiple output for high speed...
Performance analysis of massive multiple input multiple output for high speed...
IJECEIAES
 
Path-loss prediction of GSM signals in warri
Path-loss prediction of GSM signals in warriPath-loss prediction of GSM signals in warri
Path-loss prediction of GSM signals in warri
onome okuma
 
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
iosrjce
 
G8gKADWDcjv934mbFProject_Compilation_20150415.doc
G8gKADWDcjv934mbFProject_Compilation_20150415.docG8gKADWDcjv934mbFProject_Compilation_20150415.doc
G8gKADWDcjv934mbFProject_Compilation_20150415.doc
Olukayode Aluko
 

Similar to Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular Networks (20)

A Review on Cooperative Communication Protocols in Wireless World
A Review on Cooperative Communication  Protocols in Wireless World A Review on Cooperative Communication  Protocols in Wireless World
A Review on Cooperative Communication Protocols in Wireless World
 
Wap based seamless roaming in urban environment with wise handoff technique
Wap based seamless roaming in urban environment with wise handoff techniqueWap based seamless roaming in urban environment with wise handoff technique
Wap based seamless roaming in urban environment with wise handoff technique
 
Broadband adoption in Thailand : A Quantitative Study in Mea Fah Luang Unive...
Broadband adoption in Thailand : A Quantitative Study in Mea  Fah Luang Unive...Broadband adoption in Thailand : A Quantitative Study in Mea  Fah Luang Unive...
Broadband adoption in Thailand : A Quantitative Study in Mea Fah Luang Unive...
 
Comparative Study on Mobile Switching Center of Mobile Generations
Comparative Study on Mobile Switching Center of Mobile GenerationsComparative Study on Mobile Switching Center of Mobile Generations
Comparative Study on Mobile Switching Center of Mobile Generations
 
Reduce the probability of blocking for handoff and calls in cellular systems ...
Reduce the probability of blocking for handoff and calls in cellular systems ...Reduce the probability of blocking for handoff and calls in cellular systems ...
Reduce the probability of blocking for handoff and calls in cellular systems ...
 
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
An Efficient Call Admission Control Scheme for Handling Handoffs in Wireless ...
 
Mobile data offloading
Mobile data offloadingMobile data offloading
Mobile data offloading
 
Mobile data offloading
Mobile data offloadingMobile data offloading
Mobile data offloading
 
Performance analysis of massive multiple input multiple output for high speed...
Performance analysis of massive multiple input multiple output for high speed...Performance analysis of massive multiple input multiple output for high speed...
Performance analysis of massive multiple input multiple output for high speed...
 
Path-loss prediction of GSM signals in warri
Path-loss prediction of GSM signals in warriPath-loss prediction of GSM signals in warri
Path-loss prediction of GSM signals in warri
 
a data mining approach for location production in mobile environments
a data mining approach for location production in mobile environments a data mining approach for location production in mobile environments
a data mining approach for location production in mobile environments
 
A COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOE
A COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOEA COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOE
A COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOE
 
G010613135
G010613135G010613135
G010613135
 
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network
 
Teletraffic Analysis of Overflowed Traffic with Voice only in Multilayer 3G W...
Teletraffic Analysis of Overflowed Traffic with Voice only in Multilayer 3G W...Teletraffic Analysis of Overflowed Traffic with Voice only in Multilayer 3G W...
Teletraffic Analysis of Overflowed Traffic with Voice only in Multilayer 3G W...
 
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5GNEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
 
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5GNEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5G
 
Comparative Study of Optic Fibre and Wireless Technologies in Internet Connec...
Comparative Study of Optic Fibre and Wireless Technologies in Internet Connec...Comparative Study of Optic Fibre and Wireless Technologies in Internet Connec...
Comparative Study of Optic Fibre and Wireless Technologies in Internet Connec...
 
G8gKADWDcjv934mbFProject_Compilation_20150415.doc
G8gKADWDcjv934mbFProject_Compilation_20150415.docG8gKADWDcjv934mbFProject_Compilation_20150415.doc
G8gKADWDcjv934mbFProject_Compilation_20150415.doc
 
T0 numtq0n tg=
T0 numtq0n tg=T0 numtq0n tg=
T0 numtq0n tg=
 

Recently uploaded

Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 

Recently uploaded (20)

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 

Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular Networks

  • 1. 29 Factors Affecting QoS in Tanzania Cellular Networks Adam B. Mtaho and Fredrick R. Ishengoma School of Informatics and Virtual Education, The University of Dodoma, Tanzania Abhassigiye@yahoo.co.uk, fishengoma@udom.ac.tz Abstract Quality of service (QoS) in cellular communication system is a topic that recently has raised much interest for many researchers. This paper presents the findings obtained from the study on factors affecting QoS in Tanzania cellular networks. The study was carried out in Dodoma Municipal, Tanzania. The study employed cross-sectional research design. Information was gathered from structured questionnaire of 240 subscribers during the study of quality of service for the four leading cellular networks in Tanzania (Vodacom, Airtel, Tigo and Zantel). Both qualitative and quantitative data from field survey were collected and analyzed using Statistical Package for Social Sciences (SPSS-version 11) and Excel software. The study findings show that the major factors that degrade QoS in Tanzania cellular networks are inadequate network infrastructure, lack of fairness from service providers and little efforts taken by the government in enforcing the national agreed standards. Other factors are lack of reliable end-to-end systems, geographical terrain, low quality handsets, poor government monitoring on standards and lack of subscriber’s skills and training. Keywords: Cellular networks, Network coverage, Network capacity, Quality of Service I. Introduction The cellular communication services in Tanzania were introduced after the liberalization of the communication sector in 1993. Since then, a number of subscribers and vendors have been increasing. Tanzania Communication Regulatory Authority (TCRA) statistics as of September 2013, indicates that the mobile telephone market is the fastest growing sector, with more than 26 million subscribers in a population of about 43 million, of which Vodacom is leading with, about 10 million subscribers, followed by Airtel 8.7 million, Tigo 6.2 million, and Zantel 1.7 million (TCRA, 2013). Quality of Service (QoS) refers to the effect of service performance that defines the level of a user’s satisfaction with the service. The Tanzania Communications QoS Regulations clearly recommends measuring the QoS provided in cellular networks from time to time and comparing them with the norms so as to assess the level of performance. Several factors affect the quality of services in cellular networks. However, so far, very little is known about the QoS in cellular networks in the country. This paper therefore examines factors that affect QoS in Tanzania cellular networks.
  • 2. 30 The rest of the paper is organized as follows: We start by providing an overview of cellular networks in section 2. Section 3explains the study methodology used. Section 4 presents data collection and data analysis. Study findings are presented in Section 5. We conclude in Section 6 along with recommendation for future practice. II. Overview of Cellular Networks Cellular communications worldwide has experienced a rapid growth in the past two decades. Cellular phones allow a person to make and receive a call from almost everyplace through a given network. Also, cellular networks enable a person in motion to continue with phone conversation. Cellular communication is supported by an infrastructure called a cellular network, which integrates cellular phones into the Public Switched Telephone Network (PSTN) (Zhang and Stojmenovic, 2005). Apart from voice service, cellular telephony provides a number of services to the users. Such services include Short Message Services (SMS), Instant Messaging (IM), and Multimedia Messaging (MMS). SMS allows a subscriber to send and receive text message using the mobile terminal. IM is a short message exchanged between mobile users in real time while MMS allows users to send pictures, video or voice to other mobile terminals or an electronic mail account. Other services include e-mail services, wireless Internet, emergence calls, video services and mobile TV (Pashtan, 2006). A cellular network provides cell phones or mobile stations (MSs), with wireless access to PSTN (Zhang and Stojmenovic, 2005) A. Essential Elements of a Cellular Networks Mobile Stations(MS) essentially enables a user uses to make communication. The MS is made up of two parts, the handset and Subscriber Identity Module (SIM), whose major function is to store data for both the operator and subscriber (Mishra, 2004). The service coverage area of a cellular network is divided into several smaller areas, referred to as cells, each of which is served by a base station (BS or BTS). The BS is fixed, and it is connected to the Mobile Telephone Switching Office (MTSO), also known as the Mobile Switching Center (MSC). An MTSO is in charge of a cluster of BSs and it is, in turn, connected to the PSTN (Zhang and Stojmenovic, 2005). For GSM network, BTS is then connected to MSC via the Base Station Controller (BSC). The BSC main function is usually to handle radio resource management and handovers of the calls from one BTS (or cell/sector) to another BTS equipped in it (Mishra, 2004). With the wireless link between the BTS and MS, MSs are able to communicate with wire line phones in the PSTN. Both BSs and MSs are equipped with a transceiver. Figure 1 illustrates a typical cellular network, in which a cell is represented by a hexagon and a BS is represented by triangle.
  • 3. 31 Figure. 1. Typical cellular network (Source: Zhang, J. and Stojmenovic, I., 2005) A cellular network is a network that divides a geographic area into cells such that the same radio frequency (RF) can be reused in two cells that are a certain distance apart (Zhang and Stojmenovic, 2005). The cellular network operates based on the frequency reuse concept, which offers very high capacity in a limited spectrum allocation. Each BTS is allocated a segment of the total number of channels available to the entire system, and nearby BTS are assigned non- overlapping channel sets. All available channels are later assigned to a relatively small number of neighboring BTSs. The BTS is then used within a small geographic area called a cell. In this way these few available channels are distributed throughout the geographic region and may be reused as many times as necessary, hence providing effective utilization of frequency while providing adequate network coverage within the area (Rappaport, 2002). When the demand for service increases due to increase of subscribers, the number of BTSs may be increased, so as to increase the corresponding number of channels. This provides additional radio. Some of the features that determine cellular network performance are network coverage and capacity. Both capacity and coverage have direct impact on QoS. Network coverage refers to the maximum allowed distance from which the MS can be reliably connected to the nearby BTS (Mishra, 2004). Network capacity on other hand refers to the maximum number of subscribers a given BTS can cater at a given time. The higher the capacity, the more the number of subscribers who can be allowed to access cellular service at a given time (Mishra, 2004). III. Study Methodology A. Study Location and Justification for Its Selection The study was conducted in Dodoma Municipal, Tanzania. Dodoma Municipal was selected because it is a rapidly growing town that needs reliable cellular communication services for its sustainable growth. Moreover in this municipality all four leading cellular networks in Tanzania (Airtel, Tigo, Vodacom and Zantel) are present. The study employed the cross-sectional research
  • 4. 32 design, whereby data was collected among six institutions in Dodoma Municipal. Information from structured questionnaire of 240 students’ subscribers, six key informants and observation was collected to assess the quality of network performance and online customer service. B. Sampling Procedures a. Population The population from which the sample was drawn for this study involved subscribers who are getting cellular communication services from the four cellular networks present in Dodoma (Tigo, Vodacom, Zantel and Airtel). The sampling frame was a students’ subscriber from six higher learning institutions namely: College of Business Education (CBE), Institute of Rural Development Planning (IRDP), The University of Dodoma – College of Informatics and Virtual Education (CIVE), The University of Dodoma – College of Health and Social Science (CHSS), The University of Dodoma – College of Education (CoED) and St.John’s University of Tanzania (SJUT) in Dodoma Municipal. b. Sample Size and Sampling Technique According to the Department of Research and Consultancy of the Dodoma Municipal, Dodoma Municipal has the total population of 507,141 people. In order to get the sample size the researcher adopted the formula that has been developed by Yamena (1967). = (1 + ( )2) Where − Sample Size, − Total Population, − Detection error expressed into percentage (5% − 10%), and thus from = 507,141, = 6.74%, = 507,141 (1 + 507,141 . 2) = 220 Respondents That means, according to Yamena (1967) the respondents were not required to be less than 220. In order to make the research manageable, the sample size of 240 subscribers from six higher learning institutions was involved in this study. The 240 respondents were selected by employing purposive sampling technique. The specific criterion for selecting respondents was; being student subscriber who lives and study at the given institution. Later, 40 respondents were randomly selected from each educational institution using simple random sampling procedure to make a total of 240 respondents. Furthermore, six key informants (two site engineers, one frequency engineer and three cellular network engineers) were interviewed using a checklist. Selection of the key informants was based on the experience in working in cellular networks industry. It was logically assumed that the sample represented the whole population of mobile subscribers in Tanzania.
  • 5. 33 IV. Data Collection and Data Analysis In this study, for primary data, structured questionnaires, in-depth interview, and observation were used as primary data collection instruments while documentary review were used for the collection of the secondary data. Both qualitative and quantitative data from field survey were collected and analyzed using Statistical Package for Social Sciences (SPSS-version 11) and Excel software program. Data were first coded in the form suitable for addressing research questions and the method of analysis to be employed. The analysis of the recorded and summarized data from key informants used ethnographic approach; that is relying on the direct information given by respondents according to the check list used during the discussion. V. Study Findings A. Factors that Affects the QoS in Tanzania Cellular Networks Several factors that affect QoS in Tanzania cellular networks were identified during the study. Among the factors pointed out to affect QoS by customers include limited coverage and capacity, poor government monitoring on standards and lack of skills and training on the use of mobile phones. Other factors include lack of fairness from service providers, low quality handsets and delay in allocation of adequate network infrastructure. Further, geographical terrain and lack of reliable end-to-end systems were pointed by telecommunication engineering professionals to affect QoS in cellular networks.Figure 2 below presents the size and percentage response of customers on the factors that affect QoS in Tanzania cellular networks. Figure. 2.Response of customers on the factors affecting QoS in Tanzania cellular networks. Figure 2 shows a number of factors that degrade the QoS in Tanzania cellular networks. These factors are discussed as follows: a. Limited Network Coverage and Capacity Lack of adequate network coverage and capacity are the leading causes that affect QoS in Tanzania cellular networks as it was evidenced by 45% of the total responses. The study found that network infrastructure is available mainly in urban areas and limited in rural areas. According to Tanzania’s Infrastructure report (2010), only 65 percent of the Tanzania population 8% 5% 18% 45% 17% 7% Factors Affec ng QoS in Tanzania Cellular Networks Low quality handset Delay in alloca on of adequate network infrastructure Lack of fairness from service providers Limited coverage and capacity Poor government monitoring on standards Lack of skills and training on the use of mobile phones
  • 6. 34 lives within the range of a GSM signal, compared with over 90 percent in neighboring Kenya and Uganda. This indicates that network coverage in Tanzania is still inadequate. The study found that despite having moderate network coverage in urban areas, the network capacity is still limited. For example, despite having more than 23, 000 subscribers at UDOM area has only three BTS. This makes an average of about 7500 subscribers per single BTS. This number is too large for one BTS. It does nor matter which capacity improvement techniques is used. The study found that network related problems (such as network outage and call dropout) are among the reasons why subscribers own more than one SIM cards. According to the findings, 44.6% of subscriber complained about network related problems to be the main causes for subscribers owning more than one SIM card from different operators. Since QoS in cellular networks depends mainly on network coverage and capacity (Mishra, 2004), inadequate network coverage and low network capacity contributes to degradation of QoS in Tanzania cellular networks. b. Lack of Skills and Training Lack of skills and training on using mobile phones is another cause that affects QoS as it was evidenced by 7% of the total responses. Using mobile phone requires knowledge and ability to properly follow the procedures. For example, the study found that some of subscribers do not charge the phones to their full capacity. Improper charging of the battery limits its life span. Lack of such knowledge can compromise the quality of the handset. The handset can be easily susceptible to call drop out and network outage problems if its battery strength is weak. The study found that some of the subscribers do not know how to effectively use mobile phones. Most of the mobile handsets are configured to operate in English or other foreign languages, while majority of Tanzanians understand Kiswahili. Respondents pointed out this problem as the source of difficulty in using mobile phone. Improper knowledge of how to buy good quality phones was also reported to be the major bottleneck towards aching effective QoS. This is because poor quality handsets suffer from voice quality degradation (Mishra, 2007) c. Poor Government Monitoring on Standards Poor government monitoring on standards is another cause that affects QoS as it was evidenced by 17% of the total responses. The study found that despite there being national standards, operators are following their own standards. For instance, a caller in Airtel network may get informed about the time and amount of money spent instantly after finishing the call. Vodacom and Tigo networks do not give such information. This implies that Airtel subscribers can easily verify the bills of their calls. The study found that operators use the same standards for few services such as using the same dialing code to request online customer care (code 100 is used), air balance inquiry and air time recharging. d. Lack of Fairness from Service Providers Lack of fairness from service providers is reported to be another barrier towards achieving effective QoS in cellular networks. 18% of the total responses pointed out that providers were sometimes unfair to the customers. For example, the study found that if a call drops out due to network problems, the service provider does not pay the user for the loss incurred.
  • 7. 35 The International Telecommunication Union (ITU) recommends that to ensure service level quality, service level agreement (SLA) must be included in contractual agreements between customers and service providers. This includes tariffs and billing, network performance, and compensation for unachieved level of service quality. The study found that SLA is not practiced in Tanzania. For example, registration in cellular networks service does not include SLA between mobile subscriber and service providers. In other words, the customer is neither guaranteed by the provider to get high quality service nor assured to be compensated if the normal service quality level is not achieved. Lack of SLA between the operator and subscriber therefore affects QoS. Lack of clear information about the service provided by network operators is another example that shows how operators are unfair to their customers. For example the study found that subscribers are always told to subscribe to the caller tune service. However, subscribers are not informed how to unsubscribe from this service. As reported by Materu and Dyamett (2010), subscribers are instructed to subscribe i.e. to join with new services, but they are not informed or taught how to unsubscribe. According to Tanzania Communications (QoS) Regulations, 2005, service providers must ensure that customers are provided with information about the services that they provide, so as to enable them to make decision. However, the study found that such rule is not effectively followed by operators. e. LowQuality Handsets In response to the factors affecting the QoS in cellular networks, the lack of handsets with good quality was one of the complaints. This contributed 8% of the total responses. Low quality handsets affect the QoS. Usually handsets that receive low network signal uses more power to remain connected, than the handset near the BTS (Mishra, 2004). According to Ditech Networks (2011), in CDMA networks, the use of inexpensive low quality handsets allows hybrid and acoustic echoes; resulting degraded service quality. It is therefore recommended to have mobile phone with good quality. f. Delay in Allocation of Adequate Network Infrastructure Delay in allocation of BTSs is another problem. It contributes 5% of the total responses. The respondents pointed out that operators have been delaying to introduce new BTSs despite the rapid increase of customers in the area. It was pointed out by the respondents that the increase of subscribers does not match with the increase of BTSs. For example, the study found that there are only three BTSs serving the population of about of 23000 subscribers at UDOM. This makes an average of 7500 subscribers per BTS. This number is too large to be accommodated by a single BTS. The study found that operators delay to increase number of BTS regardless of the rising demand due to high investment and running cost of the equipment. g. Geographical Terrain Geographical terrain was pointed by cellular network engineers to be one of the variables that affect the QoS. It was stated that around Dodoma Municipal there are hills and mountains. Radio waves require direct line of sight from BTS to BTS. Presence of hills and mountains create obstacles and prevents signal of one BTS from reaching another BTS or BSC. This problem degrades QoS and affects both network coverage, and capacity. Presence of hills and mountains in Dodoma municipals were pointed out by cellular network engineers to bring difficulties
  • 8. 36 during network planning. For example, the study found the Vodacom BTS at UDOM, which is positioned about 9 kilometers from the BSC is linked with the BSC via another BTS at Kisasa (about 12 Km from UDOM). Redirection of UDOM BTS was done to avoid unfavorable signal propagation caused by obstacles due to the hilly terrain along the UDOM area. h. Lack of Reliable End to End Systems Relaying on radio link as the major connection between BSC and MSC was pointed out by site and frequency engineers to be another factor that affects QoS in cellular networks. Despite the introduction of fiber optic cable by SEACOM in July 2009, cellular networks in Tanzania still use radio link as the primary media for signal transmission from BSC to MSC. Radio link suffers from limited throughput and electromagnetic interferences from other sources. Interference cause noise, call drop and call set up failure. However, the study found that Vodacom is cellular network operator in Tanzania who currently uses fiber optic to link BSC and MSC as an alternate to radio link. VI. Conclusions In this paper, we presented the factors that affect the Quality of Service in Tanzania cellular networks. Some factors that were identified to be the contributors of poor QoS in Tanzania cellular networks includes; limited network coverage and capacity, inadequate network infrastructure, lack of fairness from service providers and little efforts taken by the government in enforcing the national agreed standards. The study recommends TCRA to ensure that the established standards are met and followed by operators. Further, telecomm operators in the country are advised to improve network coverage and provide reliable and fair services to customers. References i. Africa Infrastructures, Country Diagnostic (2010), Tanzania’s Infrastructure, Country Report, The World Bank, 1818H Street, NW, Washington DC, 20433, USA. ii. Ditech Networks (2011), Wireless/Mobile Voice Quality, [http://www.ditechnetworks.com/solutions/wirelessSol.html], site visited on January 2014 iii. Materu B.M et al. (2010), Tanzania ICT Sector Performance Review 2009/2010, Towards Evidence-based ICT Policy and Regulation, Vol. 2, No. 11. iv. Mishra, A.R., (2004), Fundamentals of Cellular Network planning & Optimization, John Willey & Sons Ltd, the Atrium, Southern Gate, Chichester,West Sussex Po19 8sq, England. v. Mishra, A.R., (2007), Advanced Cellular Network Planning and Optimization, 2G/2.5G/3G, Evolution to 4G, John Wiley & Sons Ltd, the Atrium, Southern Gate, Chichester,West Sussex Po19 8sq, England. vi. Mtaho A.B.et al. (2011). Analysis Of Quality Of Service in Tanzania Cellular Networks, A Case Of Dodoma Municipal, Journal of Informatics and Virtual Education (JIVE), Vol.1 No.1. vii. Pashtan, A. (2006), Wireless Terrestrial Communications, Cellular Telephony, Aware Networks, Inc., Buffalo grove, Illinois, USA, Eolss Publishers. viii. Rappaport, T.S.(2002), Wireless Communications: Principles and Practice, 2nd Edition, New Jersey, Prentice Hall. ix. Tanzania Communication Regulatory Authority (TCRA), (2013), 2013 Quarterly Statistics Reports. x. Yamena, T., (1967),Statistics, an Introductory Analysis, 2nd Edition, Harper and Ran, New York. xi. Zhang, J et al. (2005), Cellular Networks, Handbook on Information Security (H. Bidgoli, ed.), Wiley, Vol. I, Part 2, 654-663.