ABSTRACT
The great challenge of the remarkably growing demand for personal communication mobile service has actively motivated different Telephone Telecommunication Company to adopt various techniques in order to substantially improve its network capacity. An efficient allocation strategy of communication channels that could ensure good performance of the cellular network is critically needed, given the limited spectrum currently available that uses the Fixed Channel Allocation (FCA) strategy. Therefore, the aim of this research work is congestion control in cellular network using Distributed Dynamic Channel Allocation technique for improved performance. In this study, experimental investigations were conducted to improve a particular site in the choice of environment (9Mobile) by proposing the evaluation of the adoption of the Channel Allocator Distributed Dynamic Channel Allocation (CA – DDCA) technique. The main reasons for proposing the adoption of the CA – DDCA technique are; to minimize the call blocking probability, to minimize call dropping probability, enhancing the network performance and increasing the number of network subscribers. This work has been done by applying actual data from an existing cellular network of 9Mobile network Company formally known as Etisalat in to the experimental simulation program known as model using MATLAB R2007b. The results demonstrated clearly that the more number of Channel Allocator used in a particular network the higher congestion control that occurs in that network. The results got from the developed SIMULINK model shows clearly that when 1 CA is used the maximum or peak value of congestion is 0.5, when 2 CAs are used the congestion peak reduced to 0.25 which also reduced further to 0.17 when 3 CAs are used. This shows very clearly that the congestion in the developed model was reduced by more than 50%, of which the impact of the reduced traffic in the network will increase the quality of service of that network.
TABLE OF CONTENTS
Title page i
Declaration ii
Certification iii
Dedication iv
Acknowledgements v
Table of Contents vi
List of Tables viii
List of Figures ix
Abstract x
CHAPTER 1: INTRODUCTION
1.1 Background of Study 1
1.2 Problem Statement 3
1.3 Aim and Objectives of the Study 3
1.4 Significance of the Study 4
1.5 Scope of the Study 5
1.6 Organization of the Study 5
CHAPTER 2: LITERATURE REVIEW
2.1 Global System for Mobile Communication 6
2.2 Congestion in Cellular Networks 9
2.2.1 Causes of congestion in GSM network in nigeria 11
2.2.2 Some existing congestion control methods 12
2.2.3 Distributed dynamic channel allocation 13
2.4 Network channel 14
2.5 Traffic models 15
2.6 Key Performance Indicators (KPI) 16
2.7 Summary Review of Related Literature 18
CHAPTER 3: MATERIALS AND METHOD
3.1 Materials 26
3.2 Method 28
3.2.1 Procedure for data collection 28
3.2.2 Choice of environment 30
3.3 Monthly Determination of the Network Understudy 32
3.3.1 Determination of an ideal bit error rate for the network choice of environment 33
3.4 Simulation Model 34
CHAPTER 4: RESULTS AND DISCUSSION
4.1 Representation of Results in a Tabular Form 36
4.1.1 Graphical Representation of Results Obtained 44
4.2 Discussion 50
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS
5.1 Conclusion 51
5.2 Recommendations 52
References 53
Appendices 58
LIST OF TABLES
4.1: Values of packet loss, calculated congestion, calculated bit error rate and dates of data collection for month of March 36
4.2: Values of packet loss, calculated congestion, calculated bit error rate and dates of data collection for month of April 37
4.3: Values of packet loss, calculated congestion and the dates of data collection for month of May 38
4.4: Values of packet loss, calculated congestion, calculated bit error rate and dates of data collection for month of June 39
4.5: Values of packet loss, calculated congestion and the dates of data collection for month of July 40
4.6: Values of packet loss, calculated congestion and the dates of data collection for month of August 41
4.7: Values displayed by the model when using 1 – CA 42
4.8: Values displayed by the model when using 2 – CA 42
4.9: Values displayed by the model when using 3 – CA 43
LIST OF FIGURES
2.1: General architecture of a GSM 7
2.2: Typical time slot composition 15
3.1: Site manager 27
3.2: Picture of the researcher launching site manager software for data collection 28
3.3: Data collected on call drop due to Congestion in a table form 29
3.4: Data collected in a chart form 29
3.5: Block diagram of Thesis process 31
3.6: Developed SIMULINK model 34
3.7: Flow chart for cellular network congestion control using dynamic channel allocation technique 35
4.1: Congestion graph for the six months when the CA is 1 44
4.2: Congestion graph for the six months when using 2 CA 46
4.3 Congestion graph for the six month using 3 – CA 48
4.4: Congestion graph using CA 1, 2 and 3 for the six months 50
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND OF STUDY
As the technology advances mobile computing has gained lot of importance in recent years. Mobile Computing uses cellular/wireless communication network (Rappaport, 2003). In cellular communication system, a geographical area is divided into regions called cells. Each cell has a cell site or base station referred to as a Mobile Service Station (MSS) and numbers of Mobile Hosts (MH) are presents in the cell. Mobile service stations are connected to each other via fixed wire network and communication between MSS and MH is through wireless network. The bandwidth is the limited resource in cellular mobile system. The proper utilization of limited bandwidth is key factor to improve the performance of cellular system. The total bandwidth is divided into a set of carriers and is further divided into a number of channels for communication. In cellular communication mainly two types of channels are available between MH and MSS: communication channel and control channel. Establishing a communication session between MSS and MS in a cell, communication channel is used while control channel is the set-up channel used to send messages that are generated by the channel allocation algorithm.
In cellular/ wireless system two cells can use the same channel if the distance between these cells has the minimum reuse distance (Jiang, 2002), otherwise cannot use the same channel due to interference. Such interference is known as co-channel interference. A cell C is said to be an interference neighbours of another cell, if geographical distance between them is less than minimum reuse distance. Many channel allocation schemes are proposed in the literature. The purpose of these schemes is to assign channels so that channel utilization is maximized at the same time maintaining the voice quality.
The performances of the hybrid channel allocation schemes are intermediate between fixed and dynamic channel allocation schemes. (Katzela and Naghshineh, 1996)
The dynamic channel allocation schemes are divided into two types centralized and distributed.
In Centralized dynamic channel allocation (CDCA) schemes (Katzela and Naghshineh, 1996), a channel is selected for a new call from a central pool of free channels, and a specific characterizing function is used to select one among available free channels. The simplest scheme is to select the first available free channel that can satisfy the reuse distance. Also that free channel can be picked which can minimize the further blocking probability in the neighbourhood of the cell that needs an additional channel (Yang, 2007). Centralized schemes can theoretically provide near optimal performance, but the amount of computation and communication among the BSs (Base Stations) lead to excessive system latencies and make them impractical. Therefore, Distributed Dynamic Channel Allocation (DDCA) schemes (Katzela and Naghshineh, 1996) have been proposed, that involve scattering of channels across a network. A channel is selected for a new call from its cell or interfering neighbouring cells.
A channel allocation algorithm consists of two phases: a channel acquisition phase and channel selection phase (Gupta and Sachan, 2007). The task of channel acquisition phase is to collect the information of free available channels from the interference cells and insure that two cells within the minimum reuse distance do not share the same channel. The channel selection phase is concern for choosing a channel from the number of available free channels in order to get better channel utilization in terms of channel reuse.
In general, the acquisition phase of the distributed dynamic channel algorithm consist of two approaches namely search and update. In search approach (Guhong, 2000) when a cell requires a channel, it searches in its all interference neighbours to find the currently free available channel set and this set is used to select one channel-by-channel selection schemes. In the update approach, a cell maintains information about free available channels. When a cell requires a channel, the channel selection scheme is used to pickup one available channel and confirms with its all interference neighbouring cells whether it can use the selected channel or not. After that, when a cell acquires or releases a channel at any time, inform its interference neighbours so that, every cell in the system model always knows the available channels of its interference neighbouring cells. (Guhong, 2000)
1.2 PROBLEM STATEMENT
The development of cellular network has caused rise in the number of network users and applications. But the increased numbers of users share the available limited bandwidth resources and as a result of this, network congestion always occurs. Network congestion also occur in cellular networks due to inadequate base stations, lack of adequate channels, faulty equipments, marketing strategies and pricing schemes. (Jardosh et al, 2005)
Therefore, this work focuses on network congestion control using Dynamic Channel Allocation Scheme technique. Congestion is controlled in a designed model using CA – DDCA approach. The CA – DDCA increases as congestion increases thereby reducing call block and call drop.
1.3 AIM AND OBJECTIVES OF THE STUDY
The aim of this study is congestion control in cellular network using dynamic distributed channel allocation technique.
The specific objectives of this study are:
1. To review various related work in order to ascertain the current state of art in the field of study.
2. To choose a particular network environment where congestion occurs.
3. To determine the congestion in the network under study
4. To determine the bit error rate in the network under study
5. To design a model that minimizes congestion using dynamic distributed channel allocation technique for improved performance.
6. To validate the proposed work by comparing the result with other existing standard work
1.4 SIGNIFICANCE OF THE STUDY
This study is directed towards controlling congestion in a cellular network using dynamic distributed channel allocations which will result in the reduction of call blocking and call dropping probability. This offers the subscribers the opportunity to effectively make calls without interruptions because this method of using Channel Allocator Dynamic Distributed Channel Allocation (CA – DDCA) will increase the quality of service of the network in making the intra or inter handover over different radio base stations to be very fast and effective, thereby allowing call dropping and call blocking probability to reduce dramatically. The service providers can give subscribers the maximum satisfaction they needed since quality of service is massively improved on thereby increasing subscriber’s patronage. This method of using CA – DDCA (Channel Allocator Dynamic Distributed Channel Allocation) also reduce costs to the service providers, since the radio terminals can make use of channels interchangeably in order to avoid too many equipment leading to unnecessary interference and outrageous cost, which will lead the service providers to tax the subscribers high as their cost of equipment set up increases.
1.5 SCOPE OF THE STUDY
Congestion in cellular network can occur at different terminal of the GSM system but the scope of this work is to control congestion at the radio terminals in a cellular network using dynamic distributed channel allocation technique for improved performance of the system. Therefore, distributed dynamic channel allocation allows for the efficient use of the channel since in this work, the radio terminal will make use of any available channel to transmit to the radio terminals especially the free neighbour channel. The congestion control is focused only on the terminal of the GSM network.
1.6 ORGANISATION OF THE STUDY
The work is organized in chapters. Chapter one contains the background of the study, problem statement, aims and objectives, significance of the study, scope of the study and organizational report. Chapter two contains the literature review of the work and summary of related literature. Chapter three contains the step by step approach in achieving the result. Chapter four contains the results both in table and in graph. Chapter five is the summary of the work.
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