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Table of contents
1 Introduction
1.1 Introduction
1.2 Background
1.2.1 The Global Growth of the Mobile Cellular Market
1.2.2 Drivers for Mobile Subscriber Growth
1.2.3 Traditional Radio Network Planning
1.2.4 Subscriber Segmentation and Time Series Data in Mobile Networks
1.3 Problem Statement
1.3.1 Sub-Problems
1.3.1.1 Sub-Problem 1
1.3.1.2 Sub-Problem 2
1.4 Benets of Study
1.5 Delimitations
1.6 Condentiality
1.7 Research Methodology
1.8 Contributions and Outputs of Study
1.9 Outline of Thesis
2 Literature Review
2.1 Introduction
2.2 Impact of Growth on Mobile Networks
2.3 Information Retrieval in Telecommunication Databases
2.3.1 Impact of Subscriber Classes in Mobile Networks
2.3.2 Customer Segmentation in the Telecommunication Industry
2.4 Related Work on Feature Extraction and Classication Approaches
2.5 Mobile Network Planning and Optimisation
2.5.1 Related work on Network Planning and Optimisation
2.6 Channel Allocation Strategies in Mobile Networks
2.6.1 Related Work on Channel Allocation Approaches
2.7 Approaches for Solving Combinatorial Optimisation Problems
2.7.1 Related work on the use of Combinatorial Optimisation Solvers
2.8 Conclusion
3 Feature Extraction for Subscriber Classification in Mobile Cellular Networks
3.1 Introduction
3.2 Selecting a Suitable Feature Extraction Approach
3.2.1 Multi-resolution Based Approaches
3.2.2 Time Series Based Analysis
3.3 Background on Feature Extraction Approaches Considered in this Study
3.3.1 The Empirical Mode Decomposition Approach
3.3.2 Wavelet Based Approaches
3.3.2.1 Choice of Analysing Wavelet
3.3.3 The Dierence Histogram Approach
3.3.4 Dimensionality Reduction for the Improvement of Classication
3.4 First-Phase Development of a Feature Extraction and Mobile Cellular Network Subscriber Classication Approach
3.4.1 Mobile Cellular Network Trac Data Characteristics
3.5 Signal Decomposition and Feature Extraction for Trac Data Sets
3.5.1 Cluster Analysis of Extracted Features
3.6 Detailed Analysis of Feature Extraction and Classication Approach
3.6.1 Analysis of the Proposed Subscriber Classication Approach using Selected Feature Extraction Approaches
3.6.2 Analysis Based on the EMD Approach
3.6.3 Analysis Based on the DWPT Approach
3.6.4 Analysis using the Dierence Histogram Approaches
3.7 Cluster Analysis Results
3.7.1 Cluster Analysis using the EMD Approach
3.7.2 Cluster Analysis using the DWPT Approach
3.7.3 Cluster Analysis using the Dierence Histogram Approaches
3.8 Conclusion
4 A Two-Level Hybrid Channel Allocation Approach for Mobile Cellu-lar Networks
4.1 Introduction
4.2 Background of the Problem
4.3 Solving Combinatorial Optimisation Problems
4.4 The Mathematical Programming Approach for Solving Linear Problems
4.4.1 Representation of a Linear Programming Model
4.4.2 The Capacitated Facility Location Problem
4.4.3 Facility Location Problem with Incremental Costs
4.5 Solving Mixed-Integer Linear Problems
4.5.1 The Branch-and-Bound Approach
4.5.2 Relaxation and Duality
4.5.3 Lagrangian Relaxation in Capacitated Facility Location Problems
4.6 Formulation of the Two-Level Hybrid Channel Allocation Approach
4.7 Simulation and Performance Evaluation
4.7.1 First Scenario: Fixed Channel Cost per Frequency
4.7.2 Second Scenario: Increased Cost per Frequency Allocated
4.8 Summary of Results
4.9 Conclusion
5 Conclusions and Recommendations
5.1 Introduction
5.2 Stated Objectives and Achievements of Study
5.3 Benets of Study
5.4 Contributions of Work
5.5 Recommendations for Future Study
5.6 Final Conclusions
