DEVELOPMENT OF AN IMPROVED SCHEDULING ALGORITHM FOR MULTICAST SERVICES OVER WiMAX NETWORKS USING PARTICLE SWARM OPTIMIZATION TECHNIQUES


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TABLE OF CONTENTS

ABSTRACT

CHAPTERONE: INTRODUCTION
1.1       Background
1.2       Statement of problem
1.3       Aim and Objectives
1.4       Methodology
1.5       Significant Contribution
1.6       Scope of the Dissertation
1.7       Dissertation
Organization

CHAPTER TWO: LITERATURE REVIEW        
2.1       Introduction
2.2       Review of Fundamental Concepts
2.2.1    Multicast
2.2.2 IP Multicast
2.2.3 WiMAX Internet Protocol Television
2.2.4 Types of IPTV
2.1.5 WiMAX IPTV principle of operation
2.2.5 WiMAX Networks
2.2.6 Subgroup- based Resource Distribution in WiMAX Networks
2.2.6.1 Channel Monitoring
2.2.6.2 Subgroup Creation
2.2.6.3 Radio Identification Resource Distribution
2.2.6.4 Radio-Detection Subgrouping Techniques
2.2.6.5 Maximum Throughput
2.2.6.6 Proportional Fairness
2.2.6.7 Conventional Multicast Scheme (CMS)
2.2.7 Channel Modeling
2.2.7.1 COST-231 Hata Model
2.2.8 Radio Channel Characteristics
2.2.9 Radio Channel Diversity
2.2.10 Time-Varying Channel
2.2.11 Multiuser Diversity
2.2.12 Adaptive Modulation and Dynamic Resource Allocation
2.2.13 Review of Scheduling Algorithms
2.2.14 Review of Optimization Techniques
2.2.14.1 Genetic Algorithm (GA)
2.2.14.2 Ant Colony Optimization (ACO)
2.2.14.3 Tabu Search (TS)
2.2.14.4 Particle Swarm Optimization (PSO)
2.3 Review of Similar Works

CHAPTER THREE: MATERIALS AND METHODS    
3.1       Introduction
3.2.   Proposed WiMAX Network Environment
3.2.1 Layer Data Rate
3.2.2 WiMAX Subscriber Substations
3.2.2.1 User Distribution Parameters
3.2.3 PSO base Objective Function
3.2.3.1 Throughput (Fobj)
3.2.4 Proposed PSO Algorithm for Throughput Maximization
3.2.5 Development of Improved PSO

CHAPTER FOUR: RESULTS AND DISCUSSIONS     
4.1       Introduction
4.2       Aggregate Data Rate
4.3       Summary of Results Obtained from Improved PSO Algorithm
4.4       Performance Evaluation of Improved Algorithm and Maximum Throughput Algorithm
4.5       Summary of Results Obtained based on the Parameters Published in Work of Araniti et al., (2012) using the Improved Algorithm
4.6       Comparison of Results
4.7       Validation

CHAPTER FIVE: CONCLUSION AND RECOMMENDATION         
5.1       Introduction
5.2       Summary of Findings
5.3       Conclusion
5.4       Limitations
5.5       Recommendations for Further Work
REFERENCES



ABSTRACT

The challenge of optimal resource allocation to subscribers ofmobile Worldwide Interoperability for Microwave Access (WiMAX) has not been fully overcome by researchers. This research work developed an optimal scheduling algorithm for WiMAX resource allocation based on an improved Particle Swarm Optimization (PSO) technique. In this work, an improved PSO based technique for allocating subcarriers and Orthogonal Frequency Division Multiplexing (OFDM) symbols to mobileWiMAX subscriberswasdeveloped using sub-group formation. The entire WiMAX network environment was sub-divided into 7 layers.Seven distinct modulation and coding schemes were used in transmitting packets to the subscribers located within the respective layers. The objective function was determined based on PSO for throughput maximization and channel data rate. An enhanced model for throughput maximization and channel data ratewas developed by implementing an improved PSO based WiMAX resource allocation algorithm. Simulation of different scenarios of WiMAX multicast service to mobile subscribers for the evaluation of Aggregate Data Rate (ADR) and Channel Data Rate (CDR) for each scenario were carried out.The results obtained for the various layers and uniform distribution of users over the entire layers based on the performance evaluation of the improved algorithm for ADR were 350Mbps, 525Mbps, 700Mbps, 1050Mbps, 1050Mbps, 1400Mbps, 1575Mbps and 1398Mbps. Similarly, for CDR the results obtained were 6.98Mbps, 10.48Mbps, 13.97Mbps, 20.95Mbps, 20.95Mbps, 27.94Mbps, 31.5Mbps and 28Mbps. Validation was done by comparing the results obtained using the improved algorithmwith those of Maximum Throughput Algorithm (MTA). The values of ADR obtained based on the published work of Araniti et al., (2012) using the developed algorithm when users were randomly distributed and restricted to exist within each of the layers 1, 4 and 7 were 694Mbps, 175Mbps, 525Mbps and 788Mbps. Similarly, the results obtained for the CDRwere 13.9Mbps, 3.5Mbps, 10.5Mbps and 15.8Mbps. The corresponding values for the MTA were 400Mbps, 100Mbps, 400Mbps, 500Mbps and 12.5Mbps, 2.5Mbps, 12.5Mbps, 12.5Mbps, respectively. ADR of 694Mbps was achieved, which represented 88.88% of the maximum achievable ADR of the system as compared to 400Mbps, which represented 80% of the maximum achievable ADR obtained using MTA. This showed that the developed algorithm performed better than the MTA by 8.88%.




CHAPTER ONE

INTRODUCTION

1.1              Background

Rising demand for high speed multimedia services like Internet Protocol Television(IPTV) and mobile television has led to the introduction of broadband wireless access (Giacomini & Agarwal, 2013).One of such broadband wireless access is the Worldwide Interoperability for Microwave Access(WiMAX), which is also known as IEEE 802.16. The standard enables high-speed access to data, video and voice services (Chaariet al, 2012). Internet Protocol Television (IPTV) is expected to bring aboutgreat market value to the service providers in 4 generation (4G) wireless network (Houet al.,

2009). It also serves as another possibility to cabled access networks, such as fiber optics, coaxial systems using cable modems and Digital Subscriber Lines (DSL) (Adebari& Bello, 2013). WiMAX has a wide coverage range per BS which can covers up to 30 miles in radius (Shu‘aibu et al., 2011). WiMAX requires changing and diverse Quality of Service (QoS) guarantee such as optimal system throughput, maximum latencyguarantees and minimal delay jitter (Genc et al., 2008). Some of the QoS that need to be defined for the purpose of this research work are:

1.      Throughput: This is the measure of numbers of packets sent successfully in a network and it is measured in terms of packets per second (Chauchan et al.,

2013).

2.      ChannelData Rate: Accounts for the total number of user data transmitted by the

BS (BS) over the air interface (Araniti et al., 2012).

WiMAX is heterogeneous with unsystematic mix of real and non-real time traffic. The IEEE 802.16 standard provides two modes for sharing the wireless medium (Prasad & Kumar, 2013)......


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