Resource Allocation Algorithm Using Directional Antennas in WiMAX

120 Pages·2009·2.68 MB·English

“RESOURCE ALLOCATION ALGORITHM USING DIRECTIONAL ANTENNAS IN
WIMAX”

by

Neeraj Gurdasani

A project submitted in partial fulfillment
of the requirements for the degree

of

Master of Science

in

Computer Science

MONTANA STATE UNIVERSITY
Bozeman, Montana

November, 2009
©COPYRIGHT

by

Neeraj Gurdasani

2009

All Rights Reserved
ii

APPROVAL

of a project submitted by

Neeraj Gurdasani

This thesis has been read by each member of the thesis committee and has been
found to be satisfactory regarding content, English usage, format, citation, bibliographic
style, and consistency, and is ready for submission to the Division of Graduate Education.

Dr. Brendan Mumey

Approved for the Department of Computer Science

Dr. John Paxton

Approved for the Division of Graduate Education

Dr. Carl A. Fox
iii

STATEMENT OF PERMISSION TO USE

In presenting this thesis in partial fulfillment of the requirements for a
master’s degree at Montana State University, I agree that the Library shall make it
available to borrowers under rules of the Library.
If I have indicated my intention to copyright this thesis by including a
copyright notice page, copying is allowable only for scholarly purposes, consistent with
“fair use” as prescribed in the U.S. Copyright Law. Requests for permission for extended
quotation from or reproduction of this thesis in whole or in parts may be granted
only by the copyright holder.

Neeraj Gurdasani

November, 2009
iv

ACKNOWLEDGEMENTS

I am grateful to acknowledge and thank all of those who have assisted me in my
graduate program at Montana State University. First, I would like to thank Dr. Brendan
Mumey, my academic advisor who has been a huge inspiration for me here at MSU.
Without his valuable guidance and quick feedbacks, this project would not have been
possible. I take this opportunity to convey my deepest thanks to Dr. Richard S Wolff of
Electrical and Computer Engineering department. His constant encouragement and
support has made my stay here a memorable one. He has been a huge inspiration for me
and over the past 2 years and I have learnt a lot under him. Special thanks are extended to
Dr. Jian Tang for his regular inputs and prompt feedbacks.
I also want to thank project mate and friend Vishwanath Annavarapu for his
guidance in this work. Finally, I would like to thank my parents and sisters for their
unconditional support throughout my life.
v

TABLE OF CONTENTS

1. INTRODUCTION ……………………………….…………………………………….1
Directional Antennas ………………...………….……………………………….……3
Less Interference ………………...………………………………..………………4
Higher Gain………………….……………………...…….……………………….6
Higher Adaptive Modulation Coding (AMC)….………………..…………..…….7
Project Definition……………...………………….……….…………………………...9
2. ANTENNA PATTERN CREATION IN OPNET ……………………………………10
Methods of creating antenna patterns in OPNET………..……………………………11
Antenna Patten Editor ….……………….…………….….…….....……………..12
External Model Access ………………..………….……………………………..13
Automatic Creation of Antenna Patterns ………..…….………………..…………….13
Cosine Squared Gain ………...……………………...….……………….…………….17
Implementation in OPNET..……..…….………………….…………….…………….18
Tracking in OPNET.......…..…….……………….……………………………...…….19
Pencil Beam Antenna Patterns ………..…….…………………………..…………….23

3. MAX-MSRS-THROUGHPUT ALGORITHM ……….…………………………….26
ILP Formulation ……………………………...……………..…………….………….27
Variables and Constraints ……...………………………………………………29
Rounding Algorithm ……………….………...………………………………………32
Simulation on OPNET coordinates …………………………….……..………….…..33
Simulation on random coordinates ………..………………….……..………………..37

4. SIMULATION REULTS ………………………………..…………………………...38
Conclusion …………………………………………………...…………...…………..42

REFERENCES ……...……………………..…….…………………………….……......44

APPENDIX A: Antenna pattern creation and tracking code in OPNET …….…………45

APPENDIX B: Cosine Squared gain Antenna pattern creation code in OPNET …….…65

APPENDIX C: Pencil Beam Antenna Pattern creation code in OPNET..…...……….…69
vi

TABLE OF CONTENTS-CONTINUED

APPENDIX D: ILP formulation for OPNET coordinates…………..…….......….….…75

APPENDIX E: Rounding Code for OPNET coordinates………………..…...…..….…85

APPENDIX F: ILP formulation for NP Hard coordinates………………..……...….…101
vii

LIST OF FIGURES

Figure Page
1.1. WiMAX Technology usages worldwide …………………..…….………………..………2
1.2. Performance Comparison of today’s Wireless Technologies.……...……..…...…..……3
1.3. Example of a directional antenna (Yagi Antenna)…...………..….………………..……4

1.4. Directional Antenna.…………….………………………………………………...…….….5
1.5. Directional Antenna Vs Omni-Directional Antenna……….......................…...…………6
1.6. Adaptive Modulation Coding (AMC)..…..……………………….…………………………...8

1.7. entry and exit SNR threshold for different modulation in OPNET simulator ……...…9

2.1. θ (Azimuth plane) and Φ (Elevation plane) in OPNET …………….………...………..10

2.2. 36 gain definitions for a value of θ……..................................................................……...11
2.3. Result Antenna Pattern of gain 10 dB for θ from 0 to 15 degrees..……..………......…12
2.4. Example network in OPNET ………………………………….……………...….…...…14
2.5. Input to the C code ……………….……………….…………………………………….…15
2.6. Creation of antenna pattern …….……………………………………..………………….16

2.7. Antenna Pattern “mont”…………………………………………………...….......................16
2.8. Given value of Φ, θ is always constant….………...………...………..…………………17
2.9. Gain values following a cosine squared curve….…..……………………………...…..17

2.10. Upper view of antenna pattern “mont” for the simulation as in Figure 2.5…......….18

2.11. op_ima_obj_pos_get( )…….................................................…………..…..………...…..19
viii

LIST OF FIGURES-CONTINUED

Figure Page
2.12. Tracking Scenerio…………………………..…………..…………………..………..…..20
2.13. Traffic received by SS when tracking disabled ………..…..…..……………...………21

2.14. Traffic received by SS when tracking enabled ………..…….…………………..……..22
2.15. tracking disabled Vs tracking enabled ……………….…..…....…..……… …………..22
2.16. High gain values of θ for a conical antenna pattern.…….…....…..………… ………..23
2.17. High gain values of θ for a pencil beam antenna pattern ……....………..…....…..…..24
2.18. beam antenna pattern for scenario in figure …...……………...…..…………………..25
3.1. example network …………………………………………......…....…..…………………..28
3.2. The ILP created …………………………………….…….…..…....…..…………………..30
3.3. Output of Lp solve …………………………………..………..…....…..…………………..31
3.4. Example Network ………………………………..……….…..…....…..…………………..33
3.5. LP output …………………………………………….………..…....…..…………………..34
3.6. Output of rounding algorithm …………………………..…...…....…..…………………..35
3.7 Assignment …...…………………………………….…………..…....…..…………………..36
4.1. traffic sent by BS of omnidirectional (red curve) VS directional(blue curve) ….……39
4.2. Sum of traffic sent by BS of relay station using omnidirectional antenna……...……..40
4.3. Sum of traffic sent by BS of relay station using directional antenna…………………..40
4.4. Sum of traffic received by SS using omnidirectional antenna…….…………..………..41
4.5. Sum of traffic received by SS using directional antenna ………….……………..……..41
ix

ABSTRACT
This paper discusses different algorithms to create directional antenna patterns in
OPNET Modeler. We describe algorithms to create conical and pencil beam antenna
patterns. We also present a version of this algorithm that creates antenna patterns whose
gain follows a cosine squared curve. We have also implemented tracking in OPNET to
utilize these directional antenna patterns. These algorithms can be used to create antenna
patterns for any wireless technology in OPNET such as WiFi and WiMAX.

This paper also discusses an integer linear programming (ILP) formulation for a
resource allocation problem. This is a centralized optimization algorithm where the base
station decides which subscriber station will be assigned to which relay station in the
network such that the throughput of the entire network is maximized. We present some
simulation results showing 10Mbps improved throughput using directional antennas with
the assignment strategy. This is a centralized algorithm and can be used in any
technology that has a centralized resource allocation scheme such as WiMAX.