Automatic Planning of 3G UMTS All-IP Release 4 Networks with Realistic Traffic

166 Pages·2011·1.39 MB·English

Automatic Planning of
3G UMTS All-IP Release 4 Networks
with Realistic Tra(cid:14)c
by
Mohammad Reza Pasandideh
A thesis submitted to The Faculty of Graduate and Postdoctoral Affairs
in partial fulfillment of the requirements for the degree of
Master of Applied Science in Electrical and Computer Engineering
Ottawa{Carleton Institute for Electrical and Computer Engineering (OCIECE)
Department of Systems and Computer Engineering
Carleton University
Ottawa, Ontario, Canada, K1S 5B6
Copyright 2011, Mohammad Reza Pasandideh
The undersigned recommend to
the Faculty of Graduate and Postdoctoral Affairs
acceptance of the thesis
Automatic Planning of 3G UMTS All-IP Release 4 Networks with
Realistic Tra(cid:14)c
submitted by
Mohammad Reza Pasandideh, B.A.Sc.
in partial fulfillment of the requirements for
the degree of Master of Applied Science in Electrical and Computer Engineering
Chair, Howard Schwartz, Department of Systems and Computer Engineering
Thesis Supervisor, Marc St-Hilaire
Carleton University
January 2011
Abstract
This thesis focuses on designing automatic planning tools for the planning problem
of 3rd Generation (3G) Universal Mobile Telecommunication System (UMTS) all-IP
Release 4 networks. A new mathematical model for the design problem of such archi-
tecture was proposed. The main advantage of the proposed model is to incorporate
a realistic traffic profile taken from real live networks. Two approximate algorithms
based on the local search and tabu search principles are adopted to solve the problem.
Numerical results show that “good” solutions are found with the proposed heuristics.
Results demonstrate that the local search algorithm produces solutions that are, on
average, at 4.98% of the optimal solution, and in the worst case at 11.31% of the
optimal solution. Better solutions are obtained using the tabu search algorithm. In-
deed, tabu search is able to provide solutions with an average gap of 2.82% and a
maximum gap of 7.51% from the optimal solution.
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Acknowledgments
I wish to express my deepest gratitude to Prof. Marc St-Hilaire, my supervisor, for
many suggestions and constant supports during this thesis work. I would have been
lost without them. His tireless and detailed involvement in my research has been an
invaluable asset for me. I would also like to thank my thesis readers Prof. Amiya
Nayak and Prof. Thomas Kunz for their time and constructive comments.
I would like to thank my parents, Eynollah (RIP) and Rezwan Pasandideh, and
my sisters; Shamsi, Shahnaz, Shahla and Sholeh for their encouragement and love.
This thesis would not have been possible without their countless sacrifices. I am
very thankful to my brothers Alireza and Morteza for their continuous presence and
support.
I have been very fortunate to have so many friends who have always supported
me and enriched my life. To name a few, I would like to thank Masud Naaseri,
Behzad Khalvati, Farzad Khalvati, Nader Javani, Payvand Parvizi, Yasin Miyar,
Armando Espana, Arash Shokrani, Reza Yazdani, Bagher Khanloo, Ali, Reza and
Saeed Roshani, Hamid Sakhidel, Amir Kharrazi, Siamak kashanichi, and Rostam
Shirmardian.
I am grateful to Mohammad Zulhasnine, Sebastian Szyszkowicz and Frank Cer-
vantes for very fruitful discussions that helped me to solve some of my research
problems. I would also like to thank my ex-colleagues in Nokia Siemens Network
Company; Hamid Dabir, Sanaz Alizadeh, Zakaria Hadi and Rogin Thomas for their
support during my research.
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I am deeply grateful to my wife, Narges Karimi Tabar, for all the love, support
and encouragement that she has given me. She always gave me hope and energy to
complete this thesis.
Finally, I would like to dedicate this thesis to my father, Eynollah, may his soul
rest in peace.
v
To my father, Eynollah (may your soul rest in peace)
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Contents
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1 3G UMTS Networks . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.2 Network Planning Process . . . . . . . . . . . . . . . . . . . . 6
1.1.3 Network Planning Techniques . . . . . . . . . . . . . . . . . . 8
1.1.3.1 Exact Algorithms . . . . . . . . . . . . . . . . . . . . 9
1.1.3.2 Approximate Algorithms . . . . . . . . . . . . . . . . 10
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.4 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.5 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.6 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2 Literature Review on the Planning of UMTS Networks 18
2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2 Evolution of Cellular Networks . . . . . . . . . . . . . . . . . . . . . 19
2.2.1 1G Cellular Networks . . . . . . . . . . . . . . . . . . . . . . . 20
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2.2.2 2G Cellular Networks . . . . . . . . . . . . . . . . . . . . . . . 21
2.2.3 2.5G Cellular Networks . . . . . . . . . . . . . . . . . . . . . . 23
2.2.4 2.75G Cellular Networks . . . . . . . . . . . . . . . . . . . . . 25
2.2.5 3G Cellular Networks . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.6 3G Transitional Cellular Networks . . . . . . . . . . . . . . . . 28
2.2.7 4G Cellular Networks . . . . . . . . . . . . . . . . . . . . . . . 29
2.3 Sequential Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.1 The Cell Planning Sub-Problem . . . . . . . . . . . . . . . . . 31
2.3.1.1 Cell Planning Objectives . . . . . . . . . . . . . . . . 33
2.3.1.2 Cell Planning Inputs and Outputs . . . . . . . . . . 34
2.3.1.3 Traffic Modeling of Mobile Users . . . . . . . . . . . 35
2.3.1.4 Air Interface Propagation Models . . . . . . . . . . . 36
2.3.1.5 Air Interface Power Control . . . . . . . . . . . . . . 37
2.3.1.6 Cell Planning Algorithms . . . . . . . . . . . . . . . 38
2.3.2 The Access Network Planning Sub-Problem . . . . . . . . . . 41
2.3.2.1 Cost-effective Access Networks . . . . . . . . . . . . 43
2.3.2.2 Reliable Access Networks . . . . . . . . . . . . . . . 46
2.3.3 The Core Network Planning Sub-Problem . . . . . . . . . . . 47
2.3.4 Remarks on Sequential approach . . . . . . . . . . . . . . . . 50
2.4 Global Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
2.5 Section Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3 Network Model Formulation and Planning Tools 55
3.1 Basic Concepts in Optimization . . . . . . . . . . . . . . . . . . . . . 55
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3.2 Global Planning Problem: Inputs, Outputs and Objectives . . . . . . 58
3.3 Model Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.3.1 Node B Traffic Record . . . . . . . . . . . . . . . . . . . . . . 60
3.3.2 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.3.2.1 Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.3.2.2 Decision Variables . . . . . . . . . . . . . . . . . . . 64
3.3.2.3 Traffic variables . . . . . . . . . . . . . . . . . . . . . 66
3.3.2.4 Cost Parameters . . . . . . . . . . . . . . . . . . . . 67
3.4 Cost Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.5 The Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.6 Exact Methods for the Design Problem . . . . . . . . . . . . . . . . . 81
3.7 Heuristics for the Design Problem . . . . . . . . . . . . . . . . . . . . 82
3.7.1 Solution Representation and Initial Solution . . . . . . . . . . 82
3.7.2 Local Search Heuristic . . . . . . . . . . . . . . . . . . . . . . 84
3.7.3 Tabu Search Heuristic . . . . . . . . . . . . . . . . . . . . . . 87
4 Experiment Design and Result Analysis 92
4.1 Experiment Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.1.1 Implementation of the Exact Algorithm . . . . . . . . . . . . . 97
4.1.2 Implementation of Approximate Algorithms . . . . . . . . . . 98
4.1.2.1 Local Search . . . . . . . . . . . . . . . . . . . . . . 98
4.1.2.2 Tabu Search . . . . . . . . . . . . . . . . . . . . . . . 99
4.2 Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.3 Result Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
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4.3.1 Numerical Analysis . . . . . . . . . . . . . . . . . . . . . . . . 105
4.3.2 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . 111
4.4 Section Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5 Conclusions and Future Work 114
Appendix A 117
Appendix B 121
References 133
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