International Journal of Advancements in Research & Technology, Volume 4, Issue 10, October -2015
ISSN 2278-7763
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Comparative Analysis of the Performances of a
Combined and Non Combined Models Designs For
Congestion Controls in Global System For Mobile
Communication (GSM) Network
1
MBACHU, C. B., 2USIADE, R E.
1
Department of Electrical/Electronic Engineering, Anambra State University Uli, Nigeria
2
Department of Computer Engineering, Delta State Polytechnic Otefe-Oghara, Nigeria
Email: 2 rexiadeu@gmail.com, 1dambac614@gmail.com
ABSTRACT
In this resear ch work, a Co mbined Model fo r managing congestion in G SM network based on Call
Priority, Handoff Call Buffer and Frequently Recent Call concept s is de veloped. Based on thi s
Combined model, the perfor mance of the GSM networ k is extensively e valuated using the key
performance indicators which include; Call Set-up Success Rate (CSSR), Call Drop Rate (C DR), Call
Completion Success Rate (CC SR) and Traffic Channel Congestion Rate (TCHCR).
After the
evaluation, the various values of these para meter indicators na mely CSSR, CDR, CCSR, T CHCR are
approximately 98%, 2%, 97% and 2% respectively which satisfies the Ni geria Communication
Commission (NCC) acceptable bench mark for mobile operators. This paper also discusses different
developed schemes which include Dynamic Channel Allocation (DCA), Automatic Call Gappin g
(ACG), Adaptive Call Admission (ACA) and Call A dmission Control (CAC) for c ontrolling
congestion and pro viding good Quality of Service (QoS) in G SM networks. A comparison of the
performance of this Co mbined Model with the existing system based on mobile cellular network Key
Parameter Indicators as mentioned above reveals that this model has an improved performance (Quality
of Service) over the existing system. Finally, the contribution of this re search work is to make this
designed (Combined) model a more reliable al ternative to existing models for managing congestion in
GSM network.
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KEYWORDS: Global System for Mobile Communication GSM; Mobile Network Evaluation; Drive
Test; Key Performance Indicators KPIs; Quality of Service QoS. Call Prioritization, Handoff Call.
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1. Introduction
In recent time, especially the 21st century, information and communication technology has formed the
bedrock of technological and ec onomical growth in the world. The reason is not far-fetche d. People
need to comm unicate, that is, they desire to reach out to others and
share information, ideas and
resources. This desire has been a dri ving force, motivating man to continuously seek for a new and
more effective means of disse minating information to one another on real tim e basis irre spective of
distance [1].
The analogue system of teleco mmunication was associated with l ots of setback or li mitations which
made it impossible for subscribers to get the desired satisfaction for its available services. The two
major inherent limitations of the analogue cellular systems are severe confined spectrum allocation and
incompatibility among the various analogue services available [2]. This consequently l ed to the
convergence of the Europeans on a uniform standard for second generation digital system called global
system for mobile teleco mmunication (GSM). The GS M network is a mobile telecommunication
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technology system that uses the Time Division Multiple Access (TD MA) to di vide the channel into
time slots. It offers hi gh quality voice communication and low bandwidth (9. 6kb/sec) data connection
for fax, short message service (SMS) and full dial-up conn ection to the internet for e-mail and web
browsing, usually requirin g a mobile computer or intellig ent handset. Increase in de mand for GSM
services may lead to congestion if there is no commensurate increase in congestion control measures.
In digital communication congestion occurs when the nu mber of subscrib ers attempting to
simultaneously access the networ k is more than the capacity the
network can handle or sustain.
According to [3], it is the unav ailability of network to the subscriber at the ti
me of making a call.
Congestion can also be defined as a sit uation when a subscriber cannot obtain a con nection to the
wanted subscriber i mmediately [4]. In another related publication, [5] describ ed congestion as a
situation that arises when the num ber of calls emanating or terminating from a particular n etwork is
more than the capacity the network is able to cater for at a time.
A lot of research works and publications have been carried out and written respectively in different
congestion control measures. Some of these include [6] dynamic channel allocation (DCA) where there
is no fixed channel. A ll channels are kept in a central pool and are assi gned dynamically to radio cells
as new calls arrive in the system. After a call is terminated, the channel is returned to the common pool.
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Since generally more than one channel m ay be available in the central pool to b e assigned to a caller
that requires a channel, the system fails to develop strategy that must be applied to select th e assigned
channel. The authors in [ 7] did an a ppraisal of the performance of GSM operators in a c ountry known
as Nigeria in African Continen t. Having evaluated the parameters that attrib uted to poor quality of
service by o perators, they ca me up with methods that are su
ggested towards improving network
performance. A hybrid model was developed in [8] for congestion management which was a
combination of other models. However, they failed to make provision for managing handoff calls when
network channels are unavailable. This leads to high blocking probability for handoff/handover calls.
A work in [9] proposes the concept of prioriti zation of handoff calls ov er new calls by usin g buffering
technique since it is desirable to handle an ongoing call an d to ac cept new ones when the bandwidth
has reached its full capacity utilization. Similarly, another research by [10] proposed a threshold-based
guard channel policy. The polic y allocates some channels to handoff calls when the number of busy
channels exceeds the given threshold thereby blockin g new calls. In a related sche me which was
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proffered by [11] it m akes use of bufferin g calls that can tolerate delay if no channels are
free. The
major setback associated with the last thr ee works, which are guard channel schemes, is their inability
to establish a recor d of frequently recent rejected/blocked calls in order to determine the order of their
access to network facilities when the channel is free. In addition, these schem es perform better in light
traffic only.
A scheme where calls are queued and no ne w calls are granted access before the pre vious calls in the
queue is presented in [12]. It is a s tricter scheme than the previously discussed guard channel ones.
This scheme is not effecti ve because the rate of call rejection/blo ck is very hi gh. Another scheme
performed a co mbination of queuin g of new calls and guard channels. The results s howed that the
blocking of handoff calls decreases much faster as the queuing probability of new call s increases. A
scheme that combined ad mission control and bandwidth adaptation to enhance the Quality of Service
(QoS) provision was developed in [13]. Another proposed tech nique for con gestion control was
developed to adopt the principle of Automatic Call Gapping (ACG) which helps to reduce call attempts
by allowing only one call attempt per specific gap interval [14]. This scheme was not found to be very
effective because it per mitted a lot of idle t ime. A congestion control scheme for wireless mobile
network, which had a combination of call admission control with buffer management, was pr esented in
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[15]. The authors in [16] and [17] sugg ested upgrading of existing facilities, installation of additional
base stations and switchin g centres, and where applicable impro ving power supply to control
congestion in GSM networ k. A combined scheme which incorporat ed the Adaptive Call Admission
(ACA) scheme and load balancin g strategy was developed in [18] and the sche
me is c apable of
minimising the New Call Bloc king Probability (NCBP) and the Handoff Call Droppin g Probability
(HCDP). In [5] and [4], the researchers attributed the causes of congestion in GSM network in some
countries like Nigeria to factors s uch as exce eding the carryin g capacity of netw ork facilities, use of
mobile phones for data transfer and multi media activities, vandalisation of networ k equipment and
unfavourable weather conditions.
In this pap er, the proposed research de velops a new sche me that can control con gestion in GSM
network. The network performance evaluation is based on four m ajor key parameter indicators (KPIs)
which include call setup success rate, call drop rate, han dover success rate and traffic channel
congestion rate. Every KPI is explored and improvement methodologies are suggested. These include a
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combination assignment of priorit y levels to network subscribers, buffer of handoff
calls when
channels are not a vailable and allocation o f network facilities to b uffer new calls ba sed on the
frequency of channel demand. Finally, the performance of the new model is compared with that of the
non-combined (existing) model.
2. Analysis of Existing GSM Network Model
In a typical G SM network, the major determinant of system performance is always tied to traffic flow.
In this analysis, one of the basic assu
mptions is that it is im practicable for all subscri bers to be
connected at the same time due to the resources shared among the subscribers. The under-lining issue is
the probability that a system will be congested (busy) and will be unable to serv e a potential subscriber
[19]. Fig. 1 shows the g
eneral architecture of GS M network while fig. 2 depicts schematic
representation of a GSM service centre.
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Fig 1 General Architecture of GSM Network
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Fig 2 Schematic Representation of a GSM Network Service Centre
It is believed that a GSM network system has a pool of limited resources (servers). A subscriber arrives
with intention of using one of the ser vers for a period of tim e (service time). If any of the servers is
available, it is ‘hel d /occupied’ by th e arriving subscriber. If none is a vailable, the arri ving call is
‘blocked’. Hence, the entire (offe red) traffic load of the syste m is then split into; served load and
blocked load. The qu estion remains, ‘how much of the offered load is served and how much is
blocked’? (Congestion concept)
Offered load ‘A’ =
Where
1
= Average call arrival rate,
= service time, 1/ = Average holding time
3. The Combined Model
In this Co mbined Model, which is the proposed new model, Call A
dmission Control ( CAC) and
Network Resource Allocation are the key issues. CAC deter mines the condition for ac cepting or
rejecting a new call based on the a vailability of sufficient networ k resources to guarante e the QoS
parameters without affectin g the existing calls. The major call-level qualities of service param
eters
based on cellular telephone concept are: ne w call block ing and handoff call block ing probabilities.
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However, for this new model design, instead of blocking such call, a buffer is introduced w hich stores
the call until a channel is available to trans mit the call. This recommended model has a pri oritization
scheduled to maintain un-interrupted communication during emergency. It also pro vides a location for
temporary memory to cater for handoff and incessant frequent callers within a specified period. It gives
them a higher priority over a new entrant call. This is a unique innov ation for this research. This model
should be implemented at every base station. The advantages of this operation are:
It gives a priori ty to hi ghly essential duties calls that need i mmediate attention; this w ill thereby
forestall any casualties that may occur if such attention is not given.
It gives priority to the most denied calls to grab the channel when they appear within a specified
time.
It does not allow any call to occupy the channel more than necessary when there are calls waiting to
grab the channel.
It does n ot pre-empt the subs criber if there i s no call waitin g and allows d ynamic allocation of
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channel when there is equal priority calls.
3.1 The Combined Model Algorithm
Start()
Initiate_call()
Add_call_to_Queue()
Add caller ID
if((counter <= n)&&(callerPriority == higher)){
Assign_Channel()
}else{
if (Call == Handoff){
// hand off start
if (Channel == Free){
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Assign_Channel
}else{
if(Buffer == Full){
End_Call
}else{
Buffer_Call_to_M1()
}
}
}else{
// hand off end
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if (Call == Waiting){
Get_Caller_With_Highest_Waiting_Time()
}else{
if (Channel == Free){
Assign_Channel()
}else{
Buffer_Call()
}
}
}
}
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3.2 Characterization of Combined Model
A cautious observation of this model reveals that this Combined Model has some distinct features when
compared with existing model.
There are three basic features found in this Com bined Model that accounts for its distinc tion. These
features include
Call prioritization technique.
Call buffer technique for handoff call.
Call waiting / frequently recent call allocation technique.
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3.3 System (Combined Model) Testing
The three basic methods for testing and evaluation of GSM network performance include
Drive Test
Customer Complaint / Subscribers Feedback
Traffic Observation Report/Networ k Statistics from Network Operation and Maintenance Centre
(OMC) Report.
The method adopted for data collection in th is research is driv e test usin g the well k nown software
called the TEMS (Ericsson Test Mobile System), and fig. 4 is the setup for the drive test.
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Fig 4 Block diagram of Drive Test Componenets Interconnectivity
The drive test is used because firstly it is a
powerful tool for the radio frequenc y (RF) a nalysis and
problem solving, secondly, the scanner to ol used in drive test is a
very good tool for detectin g
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interfering signals, and finally, the dri ve test gives the exact geo graphical location for each sample
through the connected GPS receiver.
4. Result
The post processing was done via the assistance of a major GSM network service provider for both the
combined (C-M) and existing or non-combined model (E-M), considering the parameters such as Call
Set-Up Success Rate (CSSR), Call Drop Rate (CDR), Call Completion Success Rate (CCSR) and
Traffic Channel Cong estion Rate (TCHCR), from January to April, 2014 and the g
raphical forms of
these results are represented as figures 5, 6, 7 and 8.
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Fig 5 Call Set-Up Success Rate for Combined and Existing Models
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Fig 6
Call Drop Rate for Combined and Existing Models
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Fig 7 Call Completion Success Rate for Combined and Existing Models
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Fig 8 Traffic Channel Congestion Rate Combined and Existing Models
NOTE: C-M represents Combined Model
5.
E-M represents Existing Model
Discussion of Results
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Figure 5 shows the Call Set-Up Success Rate (CSSR) of both the combined and the existin g systems
during the test period. It can be seen that the parameter is higher in the co mbined model than in the
existing model and this implies that combined model is better with respect to CSSR. Figure 6 depicts
the Call Drop Rate (CDR) of the two syste ms during the test period. Since the parameter is less in the
combined model than the exi sting model the implication is that the co mbined model is b etter with
respect to CDR.
Figure 7 defines the Call Co mpletion Success Rate (CCSR) of both the co mbined and th e existing
systems during the test period. As the parameter is hi gher in the com bined model than that of the
existing model it means that the combined model is b etter than the existing model with respect to
CCSR. Figure 8 represents the Traffic Channel Congestion Rate (TCHCR) of the two systems during
the test period. The fact that the para meter is less in the combined model than in the exist ing model
shows that the combined model is better with respect to TCHCR. Since the co mbined model has better
values than the exiting model in all the four k
ey performance indicators used in this performance
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assessment, it is therefore clear that the combined model offers a better quality of service (QoS) than
the existing model.
6. Conclusion
It has be en analytically pr oven that we can
improve (optimize) an ex isting GSM network using
different methodologies to offer re markable Quality of S ervice to the end users. Moreo ver, the issues
discussed here are quite helpful for the an
networks. The priority calls function
alysis and perform ance evaluation of differ ent mobile
of the proposed model can be particularly useful in security,
health and other related emergency matters.
Introduction of buffers in this design plays a vital role in ensuring that the handoff and waiting calls are
not deteriorated and the quality of ser
vice is generally improved. It has been established that the
proposed model offers a very hi gh quality o f service and therefore recommended for use in global
systems for mobile networks and can also be adapted to other networks.
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