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TIME DIVERSITY ANALYSIS BASED ON PREDICTED RAIN ATTENUATION AT KA AND V BANDS USING

SYNTHETIC STORM TECHNIQUE

BY

MOHAMMAD ROFIQUL HASSAN

A dissertation submitted in fulfillment of the requirement for the degree of Master of Science

(Computer and Information Engineering)

Kulliyyah of Engineering

International Islamic University Malaysia

JANUARY 2020

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II

ABSTRACT

Future satellite communication services are moving towards higher frequency Ka and V- bands. The use of these frequency bands is limited by different propagation impairments in atmosphere. Rain fade is the main challenge to design reliable earth to satellite communication links above 10 GHz. The problem becomes severe in tropical regions because of high rainfall occurs most of the time in a year. Time diversity technique is one of the potential mitigation techniques because this technique is cost effective and efficient mitigation techniques to overcome the attenuation due to rain (Del Pino et al, 2005). For time diversity analysis, measured real-time rain attenuation data are needed to design. But the problem is in the higher frequency bands like Ka and V bands, those data are not available. Hence, Synthetic Storm Technique (SST) can be utilized because it can convert the measured real-time rain rate data to rain attenuation data. This thesis presents analysis of one year measured rain rate data with 1-minute integration time which has been collected at IIUM, Kuala Lumpur campus. One year measured rain rate data are converted into equivalent attenuation data using Synthetic Storm Technique (SST). The Cumulative Distribution function of all converted rain attenuation is calculated without time delay and with time delays of 1, 3, 5, 10, 20 and 30 minutes respectively for Ku, Ka and V-bands. Time diversity gain is also analyzed and found that gain is higher with the increasing of time delay. It has been also observed that improvement is higher at a lower percentage of outages. The gain at 0.01% are found 4.7 and 27.8 dB for Ku-band, 6.8 and 58.7dB for Ka-band and 10.5 and 94.2 dB for V-band with the time delays for 1 and 30 min respectively. For comparison, the gains predicted by Matricciani model are compared with SST predictions for Ku, Ka and V-bands for all percentages of outages and for 1, 3, 5, 10, 20 and 30 minutes delays. Since the analysis is done based on measurement in tropical region, it is very significant that Matricciani model gain is found comparatively much higher than SST predicted rain attenuation gain in all the frequency bands. For the purpose of validation, SST predicted gain has been compared with the available Kuala Lumpur measurement at Ku-band. After comparison, it has been found that the SST predicted gain is much closer to measured one than gain predicted by the Matricciani model. Hence, a model can be proposed to predict the time diversity gain using measured rain rate time series and Synthetic Storm Technique (SST) with a correction which depends on frequency and time delay. For Ku-band, the correction function is developed and presented. For any other bands, the functions can be developed using available measured gains.

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III

ثحبلا ةصلاخ

ٟلبطٔ ٛسٔ خ١ٍجمزسٌّا ذ٠لاربسٌا دلابصرا خّظٔا دبم١جطرٚ دبِذخ ٗدزر ٚ Ka

ٌٟبؼٌا V

فلاغٌا ٟف ٌٟبؼٌا ددشزٌا دبلبطٔ َاذخزسا ِٓ ذسر خفٍزخِ سبشزٔا كئاٛػ حذػ نبٕ٘ .ددشزٌا خلٛثِٛ دلابصرا دلاصٚ ُ١ّصزٌ ٟس١ئشٌا ٞذسزٌا ٛ٘ ٞشطٌّا ٟشلازٌا ذؼ٠ .ٞٛدٌا قٛف خ١ػبٕصٌا سبّللأا ٌٝإ ضسلأبث 01

ٟف ٖذز شثوا خٍىشٌّا ٖز٘ رجصر .ضرش٘ بد١خ

خ١ئاٛزسلاا كطبٌّٕا ِٟٕضٌا عٕٛزٌا شجزؼ٠ . ٕٗسٌا ساذِ ٍٝػ سبطِلأا يٛط٘ يذؼِ عبفرسا تجسث

ً١ٍسر ٚ ُ١ّصزٌ.شطٌّا ٓػ حربٌٕا ٓ١٘ٛزٌا ٍٝػ تٍغزٌٍ خفٍىزٌا ث١ز ِٓ ٌٗبؼفٌا دب١ٕمزٌا ٜذزا ٟف شطٌّا ٓػ ُخبٌٕا حسبشلاا ٓ١٘ٛزٌ خسبمِ ٗجم١مز دبٔب١ث َاذخزسا َضٍ٠ ، ذلٌٛا عٕٛر خ١ٕمر .ٍٟؼفٌا ذلٌٛا ٟلبطٔ ًثِ ٍٝػلأا ددشزٌا دبلبطٔ ٟف ٟ٘ خٍىشٌّا ٓىٌٚ

ٚ Ka ٖزٙف ، V

( خ١ػبٕطصلاا خفصبؼٌا خ١ٕمر َاذخزسا ٓىّ٠ , ٌٟبزٌبثٚ .حشفٛزِ ش١غ دبٔب١جٌا ٓىّ٠ بٙٔلأ ) SST

ٖز٘ َذمر .شطٌّبث ٓ١٘ٛزٌا دبٔب١ث ٌٝإ ٍٟؼفٌا ذلٌٛا ٟف شطٌّا يذؼِ دبٔب١ث يٛسر ْأ

ِ دبٔب١جٌ الا١ٍسر خزٚشطلأا خم١لد ٗرذِ ًِبىر ذلٚ غِ ذزاٚ َبػ حذٌّ خسبمٌّا شطٌّا يذؼ

ٟؼِبدٌا َشسٌا ٟف بٙؼّخ ُر حذزاٚ

شطٌّا يذؼِ دبٔب١ث ً٠ٛسر ُر .سٛجٌّ لااٛو IIUM

( خ١ػبٕطصلاا فصاٛؼٌا خ١ٕمر َاذخزسبث خئفبىِ ٓ١٘ٛر دبٔب١ث ٌٝإ َبػ حذٌّ خسبمٌّا ُر .) SST

٘ٛزٌا غ١ّدٌ ّٟواشزٌا غ٠صٛزٌا خٌاد ةبسز هٌازو ،ِٟٕص ش١خأر ْٚد شطٌّا ٓػ ُخبٌٕا ٓ١

ٖسذل ِٟٕص ش١خأزث 0

, 3 , 5 , 01 , 01 , 31 دبلبطٌٕ ٌٟاٛزٌا ٍٝػ خم١لد ٚ Ku

ٚ Ka . V

عزٌٛ ذلٚ .ِٟٕضٌا ش١خأزٌا داص بٍّو ٍٝػأ رثشٌا ْأ ذخٚٚ ِٟٕضٌا عٕٛزٌا تسو ً١ٍسر ُر باض٠أ لاا خجسٔ ذضفخٔا بٍّو ٍٝػأ ءادلأا ٟف ٓسسزٌا ْأ بض٠أ ذٕػ تسبىٌّا ٍٝػ سٛثؼٌا ُر . عبطمٔ

1.10 ٪ 7.4 ٚ 04.2 قبطٌٍٕ dB

ٚ Ku 8.2 ٚ 52.4 قبطٌٍٕ dB

ٚ Ka 01.5 ٚ 27.0 dB

قبطٌٍٕ

حذٌّ ِٟٕضٌا ش١خأزٌا غِ V 0

ٚ 31 .ٌٟاٛزٌا ٍٝػ خم١لد

خٔسبمِ ذّر ، حئبزٌٕا خٔسبمٌّ

جرّٛٔ بٙث أجٕر ٟزٌا تسبىٌّا Matricciani

داؤجٕر غِ

دبلبطٌٕ SST ٚ Ku

ٚ Ka V

حذٌّ ش١خأزٌاٚ دبػبطمٔلاا تسٔ غ١ّدٌ

0 ٚ 3 ٚ 5 ٚ 01 ٚ 01 ٚ ً١ٍسزٌا ْلأ ا اشظٔ .خم١لد 31

جرّٛٔ تسو ْٛى٠ ْأ ااذخ ٌُّٙا ِٓ ، خ٠ساذٌّا خمطٌّٕا ٟف طب١مٌا طبسأ ٍٝػ ُز٠ Matricciani ٗث أجٕر ٞزٌا شطٌّا ٓػ ُخبٌٕا ٓ١٘ٛزٌا تسو ِٓ با١جسٔ ٍٝػأ

غ١ّخ ٟف SST

لبطٔ

ِٓ ٗث أجٕزٌّا تسىٌا خٔسبمِ ذّر ، حئبزٌٕا خلد ِٓ كمسزٌا ضشغٌ .ددشزٌا دب ُ١مث SST

قبطٔ ٟف سٛجٌّلااٛو ٟف ٗسبمِ

ِٓ غلٛزٌّا رثشٌا ْأ ذخٚ ، خٔسبمٌّا ذؼث . Ku ةشلأ SST

جرّٛٔ ٗث أجٕر ٞزٌا تسىٌّا ِٓ طب١مٌا ٌٝإ ش١ثىث Matricciani

ذاشزلا ٓىّ٠ بٕ٘ ِٓٚ .

تسىث ؤجٕزٌٍ جرّٛٔ

خ١ٕمرٚ خسبمٌّا شطٌّا يذؼٌّ خ١ِٕضٌا ًسلاسٌا َاذخزسبث ِٟٕضٌا عٕٛزٌا

( خ١ػبٕطصلاا خفصبؼٌا ٌٝإ خجسٌٕبث .ذلٌٛا شخأرٚ ددشزٌا ٍٝػ ذّزؼ٠ ر١سصر غِ ) SST

Ku-

ياٚذٌا ش٠ٛطر ٓىّ٠ ، ٜشخأ دبلبطٔ ٞلأ .بّٙ٠ذمرٚ ر١سصزٌا خف١ظٚ ش٠ٛطر ُر ، band

ٌٍ ٗزبزٌّا ُ١مٌا َاذخزسبث ٗ١ثبسسٌا

. طبمٌّا تسى

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IV

APPROVAL PAGE

I certify that I have supervised and read this study and that in my opinion, it confirms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Master of Science (Computer and Information Engineering)

Md.Rafiqul Islam Supervisor

Mohamed Hadi Habaebi Co-Supervisor

Khairayu Badron Co-Supervisor

I certify that I have supervised and read this study and that in my opinion, it confirms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Master of Science (Computer and Information Engineering)

Ahmad Fadzil Ismail Internal Examiner

Siti Noorjannah Ibrahim Internal Examiner

This dissertation was submitted to the Department of Electrical and Computer Engineering and accepted as a fulfillment of the requirement for the degree of Master of Science (Computer and Information Engineering)

Mohamed Hadi Habaebi Head, Department of Electrical

& Computer Engineering

This dissertation was submitted to the Kulliyyah of Engineering and is accepted as a fulfillment of the requirement for the degree of Master of Science (Computer and Information Engineering)

Ahmad Faris Bin Ismail

Dean, Kulliyyah of Engineering

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V

DECLARATION

I hereby declare that this dissertation is the result of my own investigations, except where otherwise stated. I also declare that it has not been previously or concurrently submitted as a whole for any other degrees at IIUM or other institutions.

Mohammad Rofiqul Hassan

Signature... Date...

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VI

INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA DECLARATION OF COPYRIGHT AND AFFIRMATION

OF FAIR USE OF UNPUBLISHED RESEARCH

TIME DIVERSITY ANALYSIS BASED ON PREDICTED RAIN ATTENUATION AT KA AND V BANDS USING SYNTHETIC

STORM TECHNIQUE

I declare that the copyright holder of this dissertation is jointly owned by the student and IIUM.

Copyright © 2020 Mohammad Rofiqul Hassan and International Islamic University Malaysia, All rights reserved

No part of this unpublished research may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without prior written permission of the copyright holder except as provided below

1. Any material contained in or derived from this unpublished research may be used by others in their writing with due acknowledgement.

2. IIUM or its library will have the right to make and transmit copies (print or electronic) for institutional and academic purposes.

3. The IIUM library will have the right to make, store in a retrieved system and supply copies of this unpublished research if requested by other universities and research libraries.

By signing this form, I acknowledged that I have read and understand the IIUM Intellectual Property Right and Commercialization policy.

Affirmed by Mohammad Rofiqul Hassan

……..………. .…………...……

Signature Date

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VII

ACKNOWLEDGEMENTS

Praise to Allah, the Creator, the almighty, whose Grace and Mercies have been with me throughout the duration of my research. This work could not be completed without His guidance and grant. I pray to Allah that He fulfills me this humble work.

I sincerely appreciate from the bottom of my heart to Professor Dr. Md.Rafiqul Islam, whose tremendous supervision, kindness, promptitude, support, patient, continuously encouragement and friendship have facilitated the successful completion of my work. His motivational speech inspired me to concentrate of my research even though he took time to listen and attend to me whenever requested. His brilliant grasp of the aim and content of this work led to his insightful comments, suggestions and queries which helped me a great deal. I would like also to express my deep gratitude to my co-supervisors, Professor Dr.Mohamed Hadi Habaebi, Assistant Professor Dr. Khairayu Badron for their excellent suggestion, consultation and assistance. May Allah reward and bless them all.

Special thanks my mother A.K.M Forhad Ara Begum who always wishes me success to Allah Subahna Taa Alah. Thanks are also to my beloved wife Fawzya Sultana, who always helps me to be strong in critical moments and my siblings, my children and my friends for their consistently encouragement, supporting me to fulfill my study. Without them, I may not accomplish. May Allah bless and reward them all for this Dunia and hereafter.

Once again, we glorify Allah for his endless mercy on us one of which is enabling us to successfully round off the efforts of writing this thesis. Alhamdulillah

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VIII

TABLE OF CONTENTS

Absract..……….. ... II Abstract in Arabic….. ... Error! Bookmark not defined.

Approval Page………….. ... IV Declaration………... ... V Copyright Page….. ... VI Acknowledgements ... VII List of Tables…... ... X List of Figures…. ... ...XI List of Abbreviations ... XIII List of Symbols…. ... XIV

CHAPTER ONE:INTRODUCTION ... 1

1.1 Background ... 1

1.2 Problem Statement ... 3

1.3 Objectives of the Research ... 4

1.4 Research Methodology ... 4

1.5 Thesis Layout ... 5

CHAPTER TWO:LITERATURE REVIEW ... 6

2.1 Introduction ... 6

2.2 Rain Effect ... 6

2.3 Rain Attenuation Prediction Model ... 7

2.3.1Statistical Model: ITU-R ... 7

2.3.2Synthetic Storm Technique (SST) ... 10

2.4 Mitigation Technique ... 15

2.4.1Time Diversity ... 15

2.4.2Site Diversity ... 16

2.4.3Frequency Diversity ... 17

2.4.4Polarization Diversity ... 17

2.4.5Orbital Diversity ... 18

2.5 Previous works related with time Diversity ... 18

2.5.1Ismail et al ... 19

2.5.2Fukuchei et al ... 21

2.5.3Fabbro et al ... 22

2.5.4Matricciani et al ... 22

2.5.5Udofia et al ... 24

2.6 Summary ... 26

CHAPTER THREE:METHODOLOGY ... 27

3.1 Introduction ... 27

3.2 Measurement Setup ... 27

3.3 Data processing ... 29

3.4 Data Analysis ... 32

3.5 Effect of Wind Velocity ... 34

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IX

3.6 Time Diversity Analysis ... 35

3.7 CDF for SST Converted Rain Attenuation ... 38

3.8 Summary ... 41

CHAPTER FOUR:RESULTS AND ANALYSIS ... 42

4.1 Introduction ... 42

4.2 Attenuation Prediction by SST ... 42

4.2.1Attenuation Prediction at Ku-Band (12 GHz) ... 43

4.2.2Attenuation Prediction at Ka Band ... 44

4.2.3Attenuation Prediction at V Band ... 45

4.3 Comparison of attenuation gain among different Brands ... 46

4.4 Comparison of attenuation gain and Matricciani’s Prediction ... 48

4.5 Comparison between Measured (Ku band) and SST PREDICTION Gain ... 50

4.6 Modification of SST ... 51

4.6.1Proposed Correction Factor for SST ... 52

4.6.2Proposed Correction Factor for Time Diversity Gain ... 54

4.7 Summary ... 56

CHAPTER FIVE:CONCLUSION ... 59

5.1 Conclusion ... 59

5.2 Future Recommendation ... 61

REFERENCES……….………...62

APPENDIX A: LIST OF PUBLICATION ... …66

APPENDIX B: RAINRATE TO RAIN ATTENUATION USING SYNTHETIC STORM TECHNIQUE PROGRAM ... 67

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X

LIST OF TABLES

Table 4.1 Percentage of corresponding rain rate, Attenuation 53 Table 2.1 Comparison among previous works done on the time diversity 25

Table 3.1 The Technical specifications of the Casella 28

Table 3.2 One event sample raw data of 29th April , 2014 29 Table 3.3 The Availability of rain rate measured in 2014 31 Table 3.4 This is a one event converted attenuated sample 38

Table 3.5 Percentage of month of May, 2014 for CDF 39

Table 3.6 Percentage for CDF of 2014 41

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XI

LIST OF FIGURES

Figure 2.1 Schematic diagram of rain structure for Synthetic Storm

Technique (Shukla, Das, & Roy, 2009) 12 Figure 2.2 Comparison among rain rate, measured rain attenuation

and rain attenuation time series converted by SST for a

rainy event on 16/8/2012.(Lwas et al., 2013) 14 Figure 2.3 Comparison among rain rate, measured rain attenuation

and rain attenuation time series converted by SST for a

rainy event on 30/8/2012.(Lwas et al., 2013) 15 Figure 2.4 The time diversity technique is illustrated on the signal

of a satellite-Earth link with a raining event measured

in Malaysia. (Rafiqul ,I.M et al.2018) 19 Figure 2.5 Percentage time given attenuation exceeded with

time diversity for delays in range 1-60 min. measurement

conducted in Kuala Lumpur. 20

Figure 2.6 Time-diversity performance for various delays

(20 GHz data for earth-satellite links in Japan) 21 Figure 2.7 Long-term average CDF of exceeding in abscissa, at 20 GHz,as

a function of time delay T, from 1 minute to 60 minute,

T=0 min in the marginal distribution with no time diversity 23 Figure 2.8 Gain as a function of time delay (min) for several

values of attenuation from 5dB to 20dB at 20 GHz 23

Figure 2.9 Time diversity statistics measured at Dunde 25

Figure 3.1 Casella Tipping Bucket Rain Gauge 28

Figure 3.2 Tipping Bucket Mechanism 29

Figure 3.3 Conversion from rain rate data to rain attenuation data at

12 GHz of 29th April, 2014 using Synthetic

Storm Technique with velocity 11 m/s 33

Figure 3.4 Code for wind effects with various velocities 34 Figure 3.5 Rain rate and predicted rain attenuation with various storm speeds

from 2 m/s to 20 m/s for one rain event measured on April 29, 2014 35

Figure 3.6 MATLAB code for time diversity analysis 36

Figure 3.7 Without time delay and with time delay improvement for 1, 3, 5 min. 37 Figure 3.8 Without time delay and with time delay improvement for 1,3,5,10,20 37 Figure 3.9 Improvement of time diversity and received signal

after 30 minutes delay. 37

Figure 3.10 MATLAB code for CDF, 2014 39

Figure 3.11 CDF figure for month of May, 2014 40

Figure 3.12 MATLAB code for CDF, 2014 40

Figure 3.13 CDF for 2014 at the 0.001% to 1%. 41

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XII

Figure 4.1 Cumulative distributions of predicted rain attenuation of

2014 at Ku- band for several time delays. 43 Figure 4.2 Cumulative distributions of predicted rain attenuation of 2014 45 Figure 4.3 Cumulative distributions of predicted rain attenuation of

2014 at V- band for several time delays 46 Figure 4.4 Predicted rain attenuation gain for 0.1% percentage of

time at Ku, Ka and V bands with several time delays 47 Figure 4.5 Predicted rain attenuation gain for 0.01% percentage of

time at Ku, Ka and V bands with several time delays 47 Figure 4.6 Predicted rain attenuation gain for 0.001% at

Ku, Ka and V bands with several time delays 48 Figure 4.7 Comparison between Matricciani model gain and SST

Predicted rain attenuation gain at 0.001% for Ku , Ka and V bands 49 Figure 4.8 Comparison between Matricciani model gain and SST

Predicted rain attenuation gain at 0.01% for Ku, Ka and V bands 49 Figure 4.9 Comparison between Matricciani model gain and SST

Predicted rain attenuation gain at 0.1% for Ku , Kaand V bands 50 Figure 4.10 SST predicted gain is more closer to measurement than those

predicted by Matricciani at 0.01% for 12 GHz 51 Figure 4.11 Comparison between Measured rain attenuation and

Predicted rain attenuation for 12 GHz 51

Figure 4.12 Rain Rate VS time exceedance % 52

Figure 4.13 Difference between SST predicted and measured

Attenuation in dB for the proposed model 53 Figure 4.14 Attenuation of measured, SST predicted and modified SST 54 Figure 4.15 Difference between SST predicted and measured

gain in dB for the proposed model 55

Figure 4.16 Comparison among those predicted by SST,

Matricciani, measured and the proposed model 55

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XIII

LIST OF ABBREVIATIONS

CDF Cumulative Distribution Function

IIUM International Islamic University Malaysia

ITU- R International Telecommunication Union - Radio communication SST Synthetic Storm Technique

TD Time Diversity

Time Diversity Gain min Minute

Td Time Delay

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XIV

LIST OF SYMBOLS

A Attenuation

dB A unit of power in decibel scale f Frequency (GHz) in operating

Height of 0°C isotherm Effective height of rain (km)

Height of the earth station (km) above mean sea level I Diversity improvement factor

k and Coefficients related with frequency and polarization that given

Effective Length Length of the slant path

R Rainfall rate

Rain rate for the location for 0.01% of an average year (mm/h) Rain rate of rain layer

Rain rate of melting layer

T Time duration

β Baseline angle

δt Time delay

θ Elevation angle (deg.) of the satellite -Earth link

σ Standard deviation

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1

CHAPTER ONE INTRODUCTION

1.1 BACKGROUND

C and Ku bands are congested for the satellite communication services(Space

& Company, n.d.). Hence, the future direction of satellite communication system is going away to higher frequencies such as at the Ka-and V-bands. Higher frequencies band are of preliminary interest in satellite communication systems, since they provide sufficient transmission bandwidth and higher data rate. However, higher frequencies are severely affected by different propagation deprivations in atmosphere, such as rains, cloud, snowfall, fog etc. But the rain is one of the main challenges to design reliable earth to satellite communication links for higher frequencies. Rain fade is more severe in tropical regions(Yussuff, 2016). Therefore, to overcome the rain fade, several mitigation techniques have been proposed such as site diversity(Panagopoulos, Arapoglou, & Cottis, 2004)(Castanet, Bolea-Alamañac, & Bousquet, 2003),frequency diversity(Capsoni, D’Amico, & Nebuloni, 2009), and time diversity(Ismail & Watson, 2000) and all the techniques show promising results.

Time diversity technique is one of the potential mitigation techniques because this technique is cost effective and efficient mitigation techniques to overcome the attenuation due to rain (Del Pino et al., 2005) and this technique is also used in satellite communication to improve the performance over a link with fading.

For time diversity, measured rain attenuation data are needed otherwise the gain and improvement of the time diversity cannot be estimated. However recent studies show that in tropical climate, melting layer is disappeared during convective type of rains (Azlan, et al,2011).The Synthetic Storm Technique (SST) is a suitable method to

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2

convert the instantaneous rain rate measurements to rain-attenuation time series for Ku, Ka and V bands (Kadhim, 2017).

In present communication system measured rain attenuation data are not available at the higher frequency bands but measured rain rate data are available in many locations. By using SST rain rate data are converted into equivalent measured rain attenuation data as a result we can check the time diversity for higher frequency bands. SST was developed based on data collected from temperate regions (Sánchez-Lago et al, 2007)

An epitome of the fundamentals of the SST developed by Matricciani, (1996) is converting a rain rate time series, which is measured using a rain gauge at a point for 1-minute integration time, to a rain rate space series along a line, using an estimate of the storm translation speed to transform time to distance. Mathematically, this is carried out by convolution. The SST is also called physical-mathematical radio propagation method. This process requires knowledge about the length of the signal path through the rain cell, the rain cell velocity and the rain rate at the site under investigation(E Matricciani, 2006). Moreover, by applying the SST can generate rain attenuation time series at any frequency and polarization and for any slant path above approximately 10° as well as Matricciani et al (Matricciani et al, 2006) stated that the SST can be used to generate rain attenuation time series to slant paths of very low elevation angle with caution and a number of restraints. As a result, the SST is one of the most authentic methods to estimate rain attenuation time series and consequently long-term rain attenuation expedience probability, diurnal and service-oriented statistics (Kanellopoulos et al, 2006). The SST is very feasible for designing communications satellite systems and improves its performance(E Matricciani, 2006).

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3

Sánchez-Lago et al (Sánchez-Lago et al, 2007) referred to use of the SST model to generate time-series of signal attenuation on satellite links in system simulation studies is quite safely. This research has focused on the one year rain rate data measured at IIUM in Malaysia converted by the Synthetic Storm Technique.

After conversion of rain rate data, equivalent measured rain attenuation data are obtained. By using equivalent measured rain attenuation data cumulative distribution function is generated to get the gain with different time delays from 1 to 30 minutes. After that gain has been obtained at Ku-, Ka- and V-bands and has also been compared to Matricciani’s proposed model gain and local measured gain. Time diversity with SST at higher frequencies and refers to performance has been analyzed and presented in this dissertation.

1.2 PROBLEM STATEMENT

Rain is a problem at the higher frequency especially in tropical regions due to heavy rainfall with different characteristics (Dao et al, 2013; Das, et al, 2013). Future direction of satellite communication systems is moving towards Ka- and V- bands in which rain attenuation is main challenge to design reliable links. To mitigate this problem, time diversity technique is proposed as one of the potential methods.

However, measured rain attenuation data is required to evaluate time diversity improvement which is not available in tropical region, especially at Ka- and V- bands.

In this situation Synthetic Storm Technique is proposed as a good solution because SST can convert the rain rate time series into a rain attenuation time series which can be utilized to predict time diversity gain.

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4 1.3 OBJECTIVES OF THE RESEARCH

The main objectives of this research are:

1. To predict and analyze rain attenuation at Ku-, Ka- and V-bands using SST based on one year rain rate data measured in Malaysia.

2. To investigate time diversity improvement based on converted rain attenuation series at Ku-, Ka- and V- bands.

3. To compare predicted time diversity gain with those predicted by Matricciani’s model as well as available measurements.

1.4 RESEARCH METHODOLOGY

For obtaining the desired objectives stated above, the following steps are taken into consideration:

Step 1: Rain rate data collection

1 year rain rate data has been collected at IIUM engineering faculty from 1st January 2014 to 31st December 2014.

Step 2: Rain rate data processing

Data have been processed from 10 seconds integration time into 1 minute.

Step 3: Conversion

Rain rate time series data have been converted into rain attenuation time series data at Ku-, Ka- , V- bands using Synthetic Storm technique where MATLAB software has been used.

Step 4: Analysis

Using converted data, attenuation time series with 1, 3, 5, 10, 20, 30 minutes time delay has been presented at Ku-, Ka- and V- bands.

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Step 5: Cumulative Distribution Function (CDF)

CDF has been calculated at Ku-, Ka- and V- bands without delay and with delay of 1, 3, 5, 10, 20, 30 minutes at 0.001%, 0.01% and 0.1% .

Step 6: Attenuation Gain

Gain has been calculated using CDF at Ku-, Ka- and V- bands without delay and with delay of 1, 3, 5, 10, 20, 30 minutes. SST predicted gain has been validated with Matricciani model gain and available measured gain.

1.5 THESIS LAYOUT

Overall preview of the research has been summarized in chapter1.Chapter 2 covers the literature related with rain attenuation and time diversity. Chapter 3 describes about the data process and methodology. All results are discussed in chapter 4 and conclusion is in chapter 5.

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CHAPTER TWO LITERATURE REVIEW

2.1 INTRODUCTION

Propagation effects such as rain effects and its prediction models are elaborated in this chapter. Statistical model like ITU-R and real-time model like Synthetic Storm Technique (SST) are presented in details. The different mitigation techniques are introduced and time diversity is discussed thoroughly. Several previous works related with time diversity have also been presented in this chapter.

2.2 RAIN EFFECT

Rain attenuation, caused by scattering and absorption by water droplets, is one amongst the foremost elementary limitations to the performance of satellite communication links within the microwave region, inflicting giant variations within the received signal power with very little sure thing and lots of abrupt changes. The prevailing propagation impairment at radio frequencies higher than 10 GHz is that the rain attenuation and this can be even a lot of obvious within the tropical regions (Mandeep et al, 2006). There are several factors like frequency, elevation angle, polarization angle, rain intensity, driblet size distribution and driblet temperature that directly contributed to rain attenuation.

There are many prediction models accustomed estimate the rain attenuation.

Most of those models are supported applied mathematics information of rain rate like ITU-R model, Crane model and Garcia-Lopez model. The Synthetic Storm Technique (SST) may be a technique which might rework a precipitation rate statistic directly into a rain attenuation statistic. The SST is one amongst the most effective dependable techniques to estimate rain attenuation statistic.

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2.3 RAIN ATTENUATION PREDICTION MODEL

Rain attenuation prediction models have been discussed here. There are two rain attenuation prediction models are presented that have performed well for many diverse regions and types of rain: the ITU-R Rain Attenuation Prediction Model and SST (Synthetic Storm Technique). The ITU-R model is semi-empirical in nature and this is based on the relationship relating the specific attenuation γ = aRb (dB/km) to the rain rate R (mm/hr) through the parameters a and b. The SST is a technique which can convert a rainfall rate time series directly into a rain attenuation time series.

2.3.1 Statistical Model: ITU-R

The model differs in the method used to convert the specific attenuation to total attenuation over the path of the rain. There are 3 commercial frequencies band that has been used for this chapter. These are Ku-Band (12 GHz), Ka-Band (20GHz) and V-Band (40GHz). It has been analyzed about the effect of polarization on attenuation for every frequency band. There are 3 polarizations which are vertical, horizontal and circular polarization. The most commonly implemented model from the international propagation community is the ITU-R rain attenuation model. The model was first admitted internationally in 1982 and is continuously updated.

The input parameters are required for the ITU-R Rain Model are the frequency of operation, in GHz, the elevation angle to the satellite, in degrees, the latitude of the ground station, in degrees N or S and the altitude of the ground station above sea level, in km (ITU-R P.618-13, 12/2017). In order to obtain the rainfall rate, R0.01, exceeded in 0.01% of an average year, it can be obtained from the map of rainfall rate given recommendation ITU-R P.837 (Fig.1 in Appendix) (ITU-R P.837-7, 06/2017). To obtain the specific attenuation, using the frequency-dependent

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coefficients (K and α, these parameters are dependent on frequency, rain temperature, rain drop size distribution, and polarization) given in Recommendation ITU-R P.838 (ITU-R P.838-3, 2005) and can be determined by

γ = K (2.1)

In order to predict attenuation exceeded in 0.01% of an average year, the following formula is used:

A0.01 = LE ( LE is effective path length) (2.2)

Where LE = LRV0.01 (2.3) To calculate the vertical adjustment factor, V0.01for 0.01% of the time:

ξ =

(hR is the height of the rain) (2.4) Mean rain height above mean sea level, hr can be obtained from 0° isotherm h0 is given:

hr= h0+0.36 km

Where slant path is expressed in km is determined from

LS =

for θ≥5° (2.5) Where hs is the altitude from the receiver site of the sea level and θ is the elevation angle. The horizontal projection of LG of the slant path length is calculated:

LG = LS (2.6)

(2.7)

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9 For δ >θ, =

km Else,

km

If | | | | degrees

Else x=0

=

√ ( ( )

)

(2.8)

υ is the latitude of the earth station (Degrees)

Estimated attenuation to be exceeded for other percentages of an average year in the range 0.001% to 5%, is determined from the attenuation to be exceeded

If p≥ 1% or | |≥ 36° β = 0

If p<1% or | | <36° and θ≥25° β = - 0.005 | |

Otherwise β = - 0.005(|υ|-36°) + 1.8- 4.25

AP = A0.01(

)

(2.9) A new rain attenuation prediction model tropical region was proposed by (Badron,) as shown in equation (2.10).

(

)

+C (2.10)

The multiplication sign (*) is used to distinguish this model from ITU-R model. Since this model was developed using tropical measurement. Therefore, the correction factor C was added to the equation. C is calculated using the regression

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analysis for the local measurements of rain height, rainfall rate and specific attenuation(Badron et al., 2011)which is shown in equation of 2.10.

2.3.2 Synthetic Storm Technique (SST)

A summary of the fundamentals of the SST as developed by Matricciani, (2006) is converting a rain rate time series, which is measured using a rain gauge at a point for 1 minute and the average value is taken, to a rain rate space series along a line, using an estimate of the storm translation speed v to transform time to distance.

Mathematically, this is carried out by convolution. The SST is used to generate reliable rain attenuation time series by converting a rain rate time-series at any frequency and polarization for any slant path above approximately 10°, as long as the hypothesis of isotropy of the rainfall spatial field holds, in the long term. The SST is also called physical-mathematical radio propagation method.

This process requires knowledge about the length of the signal path through the rain cell, the rain cell velocity and the rain rate at the site under investing (E Matricciani, 2006)as well as (Kanellopoulos et al., 2006) stated that the Synthetic Storm Technique can be used to generate rain attenuation time series to slant paths of very low elevation angle with caution and a number of restraints. As a result, the SST is one of the most reliable methods to estimate rain attenuation time series and consequently long-term rain attenuation expedience probability, diurnal statistics and service-oriented statistics (Kanellopoulos et al., 2006).The SST is very useful for designing communications satellite systems and improves its performance (Matricciani et al., 2006). Sánchez-Lago et al., 2007 referred to use of the SST model to generate time-series of signal attenuation on satellite links in system simulation studies is quite safely

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