i RELIABLE COMMUNICATIONS AT FREQUENCIES BANDS ABOVE 25 GHz IN THE TROPICS

RELIABLE COMMUNICATIONS AT FREQUENCIES BANDS ABOVE 25 GHz IN

THE TROPICS

FAIZAH BINTI ABU BAKAR

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

Master of Engineering in Electrical (Electronic & Telecommunication)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

MAY 2008 i

To my beloved family especially my husband, Muzamir bin Isa and my daughters,

Zahirah binti Muzamir and Sakinah binti Muzamir iii

iv

ACKNOWLEDGEMENT

First and foremost, all praise to Allah for giving me strength and opportunity to finish my master’s study and to be able to prepare this thesis till the end. My sincere appreciation to my supervisor, Professor Dr. Tharek Abdul Rahman for his guidance, thought and encouragement. Many thanks also to Associate Professor Dr. Mohd Wazir bin Mustafa for helping us, Kulim’s students a lot in our study time.

Especially to my husband and my children, thank you for your support and patience. Without you standing beside me through ups and downs, I would not make it till the end. To all my family especially my parents and my parents in law, thank you very much for all your kind help and support.

Last but not least, to all my friends at UTM and UniMAP, thank you.

May Allah bless all of you.

v

ABSTRACT

The use of frequencies in the higher bands could tap upon the large spectrum available for communication use. However, it suffers greater propagation losses, making them unsuitable for long range communication. In addition, heavy tropical rain further reduces the reliability of the link and additional link budget has to be set aside for rain fade in order to improve its reliability. Rain attenuation model that has been used widely is currently base on ITU-R model. It gives same rain rate for all places in

Malaysia. However, previous study in Malaysia conducted by researchers in UTM shows that rain rate is not the same for different places in Malaysia. It is localized where some places experience heavier rainfall compared to other places. Hence, the

ITU-R model does not give an accurate prediction of rain attenuation in Malaysia, where the attenuation is supposed to be localized base on the data of the rain rate. This project is aimed to develop a computer program in order to predict localized rain attenuation.

The analysis of calculation to produce rain attenuation is done. The best reduction factor model is chosen to get the most accurate result. Then, the planning is done, followed by the design phase. The most challenging part, which is the development of the program, is done next. To verify the program built, it is tested by entering significant inputs and the outputs are analyzed. As a result, a computer program to predict rain attenuation in

Peninsular Malaysia is successfully built. The results produced by the program are compared to the ITU-R model of rain attenuation. The differences are calculated and the outcome shows that ITU-R model is not suitable to be used as a rain attenuation method in Malaysia.

vi

ABSTRAK

Penggunaan frekuensi di jalur lebih tinggi membolehkan spektra yang lebih lebar digunakan untuk komunikasi. Walau bagaimanapun, ia mengalami kehilangan perambatan yang lebih banyak, menjadikan ia tidak sesuai untuk komunikasi jarak jauh.

Hujan yang lebat di kawasan tropika lebih memburukkan lagi keadaan dan tambahan bajet laluan harus disediakan untuk memperbaiki kebolehpercayaan isyarat. Model pelemahan hujan yang digunakan secara meluas sekarang adalah model daripada ITU-R.

Ia memberikan kadar hujan yang sama bagi semua tempat di Malaysia. Walau bagaimanapun, kajian mendapati kadar hujan adalah terhad kepada kawasan yang kecil dan semua kawasan tersebut mengalami kadar hujan yang berlainan. Dengan ini, model

ITU-R tidak memberikan telahan yang tepat bagi nilai pelemahan hujan di Malaysia kerana satu-satu bacaan hanya terhad kepada satu kawasan kecil sahaja. Projek ini bertujuan untuk membangunkan program simulasi untuk menganggarkan tahap pelemahan hujan di satu-satu kawasan yang terhad. Perkara pertama yang dilakukan ialah menganalisa kiraan untuk mendapatkan tahap pelemahan hujan. Kemudian, model faktor pengurangan yang terbaik dipilih untuk mendapatkan hasil yang tepat. Selepas itu, perancangan yang rapi dilakukan untuk menjayakan program ini, diikuti dengan fasa merekabentuk. Bahagian yang paling sukar iaitu membangunkan program menggunakan perisian MATLAB dilakukan setelah fasa rekabentuk selesai. Untuk mengesahkan kebolehpercayaan keluaran progam ini, ia diuji dengan memberikan masukan-masukan yang sesuai dan keluarannya dianalisa. Hasil akhir yang diperolehi ialah satu program untuk menganggar tahap pelemahan hujan di Semenanjung Malaysia telah berjaya dibangunkan. Keluaran-keluaran yang dihasilkan oleh program ini telah dibandingkan dengan keluaran daripada model pelemahan hujan ITU-R. Perbezaan-

vii perbezaan nilai dikira dan didapati model pelemahan hujan yang telah dibangunkan ini lebih tepat untuk digunakan di Malaysia.

1 viii

TABLE OF CONTENTS

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENTS iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS viii

TABLES xi

FIGURES xii

LIST OF ABBREVIATIONS xiii

LIST OF SYMBOLS xiv

LIST OF APPENDICES xv

INTRODUCTION 1

1.1.1 Effects of High Frequencies to 1-3

1.1.2

Effects of Rain to Electromagnetic 3-4

Wave in High Frequencies

2 RAIN ATTENUATION PREDICTION 8

2.1.1 Rain Attenuation Calculation for 8-10

LOS (Terrestrial) microwave path

Factor ix

2.2 Some Models of Rain Attenuation

Prediction

12

Model

METHODOLOGY

20

4 RESULTS AND ANALYSIS

27

4.6 Additional Features of the Program 37

x

Rain Attenuation

Analysis Results 38

4.8.1 Comparison of the Output of RAPS1 39-40

5

REFERENCES

APPENDIX A -E

4.8.2

Comparison of the Output of RAPS1 41-43 with Results Produced Utilizing

ITU-R Reduction Factor but Using the Local Data Rain

CONCLUSION AND PROPOSED FUTURE

44

WORKS

Future

49-91

46-48

LIST OF TABLES

4.1

4.2

2.1

4.3

4.4

4.5

Some of frequency dependent coefficient to calculate specific attenuation

Comparison between output from RAPS1 and ITU-R model of rain attenuation at 26 GHz

15

Example of program output at three different locations in 37

Peninsular Malaysia

39

Comparison between output from RAPS1 and ITU-R model of rain attenuation at 38 GHz

39

Comparison of the output of RAPS1 with results produced utilizing ITU-R reduction factor at 26 GHz

Comparison of the output of RAPS1 with results produced utilizing ITU-R reduction factor at 26 GHz

41

42 xi

xii

LIST OF FIGURES

FIGURE NO.

1.2

TITLE PAGE

3.1

3.2

3.4

4.2

4.3

4.5

4.7

4.8

4.10

Rain rate (mm/h) exceeded for 0.01% of the average year

6 design 21

Flow Chart of the Methodology 22 message 35

LIST OF ABBREVIATIONS

MHz, MHz - Mega xiii

ITU-R - International Telecommunication Union Radio Section

MATLAB - Matrix

LIST OF SYMBOLS d , l , L length f , F - frequency

Ls - Loss

λ - wavelength c - speed of light

γ

R k , α - functions of frequency for ITU model d eff

, L eff - effective path length r - reduction

A

0.01

- rain attenuation exceeded for 0.01% of time

A p - rain attenuation exceeded for p% of time p percentage p w

R p,

R

-

- worst-month time percentage rain rate in millimeter per hour at p% probability e - natural p1 - modified probability of occurrence xiv

LIST OF APPENDICES

B

APPENDIX

Window

Generated 48-54

MATLAB Self Generated Code for Main Working 55-72

Window

D

E

MATLAB Code Associated with ‘Calculate and 80-87

Plot’ Pushbutton of Main Working Window

MATLAB Code for Hoplength Window 88-90 xv

CHAPTER 1

INTRODUCTION

This chapter covers the literature review and the significance of this project. It also tells about the outline of this thesis.

1.1.1 Effect of High Frequencies to Electromagnetic Wave

Since communication at lower frequencies is getting congested, the use of frequencies in higher spectrum band is currently in demand by the designers. Higher bands provide wider spectrum for communication but in contrast it suffer greater propagation loss. This can be easily determined by the below mathematical formula for free space loss:

Ls = 32 .

45 + 20 log dkm + 20 log fMHz

Higher bands from 1 GHz to 300 GHz are call microwave. Microwave is form of electromagnetic energy and can be described with the term of radio frequency or RF.

RF emission and associated phenomena can be discussed in terms of energy, radiation or fields. In term of radio wave propagation, we can define radiation as the propagation of

2 energy through space in the form of waves or particles [1]. Figure 1.1 below illustrated radiation as waves of electric and magnetic energy moving together through space.

Figure 1.1 Electromagnetic wave

Electromagnetic energy can be characterizes by a wavelength and a frequency.

The wavelength is the distance covered by a complete electromagnetic wave cycle, while the frequency is the number of electromagnetic waves passing a given point in a second. Electromagnetic waves travel through space at the speed of light. The wavelength and frequency of an electromagnetic wave are inversely related by a simple mathematical formula given below:

λ = f c

where:

λ = wavelength c = speed of light f = frequency

The speed of light in a given medium does not change, resulting in shorter wavelength for high frequency electromagnetic waves. Hence, when operating at high

3 frequencies, rain becomes a major obstacle as it will scatter the signals when the size of the raindrops is larger than the waves. To make it worse, places experiencing heavy rainfall will suffer greater interference and consequently degrading the signal or waves.

1.1.2

Effect of Rain to Electromagnetic Wave in High Frequencies

When it comes to tropical countries like Malaysia, Indonesia and Thailand, the losses become higher because of heavy rain. It can degrade the radio wave propagation at frequencies 10 GHz and above [2]. To be more specific, propagation of radio waves through the atmosphere above 10GHz involves not only free space loss and loss due to rain, but other factors listed below also contribute to the additional loss [3]: i) The gaseous of the homogeneous atmosphere due to resonant and

nonresonant polarization mechanism. ii) The inhomogeneties in the atmosphere iii) The particles due to fog, mist and haze (includes dust, smoke and salt

particles in the air)

Earlier approach to deal with rain is on a basis of rainfall given in millimeters per hour. This was usually done with rain gauges, using collected rain averaging over a day or even periods of days. However, for path design above 10 GHz, such statistic are not sufficient where designers may want path availability better than 99.9% and do not want to design using conservative procedures.

A researcher, Hogg, suggests that the use of high speed rain gauges with outputs ready available in computer analysis [3]. These gauges can provide minute by minute analysis of the fall rate, unlike the conventional type of gauges. But it is desirable to have several years’ statistics for a specific path to provide necessary and accurate

4 information on fading caused by rainfall that will determine the parameters such as LOS repeaters, size of antenna and so on.

Realizing the importance of this rainfall data, a large body of information on point rainfall and rain rates has been accumulated since 1940 [3]. This information shows a great variation of short-term rainfall rates from one geographical location to another.

Researchers in countries experiencing heavy rain especially in South East Asia countries including Malaysia have been doing active research regarding rain and its effect to communication system for the past 10 years. The tropical climate makes the research topic relevant to get a better quality of communication in microwave bands throughout the country.

1.2

Problem Statement

Rain attenuation model that has been used worldly is currently base on ITU model. It gives same rain rate for all places in Malaysia. It classified Malaysia under P climatic region where the rain rate for 0.01% of the year (R

0.01

) is given as 145 mm/h

[3], [5], [6]. The latest ITU Recommendation notes peninsular Malaysia experiences

120 mm/h rain rate and West Malaysia 100 mm/h for 0.01% of the year [7]. Figure 1.2 shows the latest rain rates in Malaysia and in its neighbours given by ITU.

However, previous study in Malaysia conducted by researches in UTM shows that rain rate is not the same for different places in Malaysia. It is localized where some places experience heavier rainfall compared to other places.

5

Therefore, the ITU-R model does not give an accurate prediction of rain attenuation in Malaysia, where the attenuation is supposed to be localized base on the data of the rain rate

1.3

Research Objectives

In accordance with active researches in rain that are being done in Malaysia and its relationship with communication, this project is aimed to develop a computer program in order to predict localized rain attenuation for terrestrial microwave links in

Peninsular Malaysia. This program will be based on given data. Once the program has been developed, the result from that simulation of the program is compared with ITU-R rain attenuation model.

This thesis consists of five chapters. Chapter 1, which is this chapter, covers the literature review, the significance of this project and the outline of this thesis.

Chapter 2 gives a brief theory of rain attenuation prediction methods. This includes rain attenuation calculation for terrestrial microwave path, path length reduction factor models and rain attenuation models that are widely used nowadays. Comparison between those models is also done and the reasons why the appropriate models are chosen to complete this project are stated.

In Chapter 3, all the methodology adopted in making this project a success is explained. The phases of methodology are written one by one and are also explained

6 briefly. A little bit of the MATLAB software that is used to build the program is also mentioned and explained.

Chapter 4 covers the results obtained from this project. The results include the program visual design, implementation, testing and user guide to use the program.

Analysis of the results is also done by comparing them with the output from ITU-R model.

Conclusion about the research and the results obtained is discussed in Chapter 5.

It also covers the proposed future works that can be implemented by future researchers to further enhance this project.

7 tude Lati

Figure 1.2 Rain rate (mm/h) exceeded for 0.01% of the average year

CHAPTER 2

RAIN ATTENUATION PREDICTION

This chapter covers brief theory of rain attenuation prediction methods and the models used worldwide.

2.1

Rain Attenuation Calculation

The most used method today for calculating rain attenuation was developed by the International Telecommunications Union Radio Section [1]. There are however many other methods, such as Crane model and methods that are more suitable for specific climates.

2.1.1 Rain Attenuation Calculation for LOS (Terrestrial) Microwave Paths

All measurements when rainfall is discussed are in millimeters per hour of rain and are point rainfall measurements. Previously in chapter 1, it is already known that heavy downpour rain will damage the radio transmission above 10 GHz. Rain is naturally cellular and has limited coverage. One thing that must be addressed is whether the entire hop is in the same heavy rain for the whole period of rain. Rainfall that is light enough (usually less than 2 mm/h) is usually widespread in character and the path

9 average is the same as the local value. Heavier rain happens in convective storm cells that are typically 2-6 km across and often embedded in larger regions measured in tens of kilometers [8]. Thus for short hops (2-6 km) the path average rainfall rate will be the same as the local rate. However, for longer paths it will be reduced by the ratio of the path length on which it is raining to the total path length.

From ITU-R for terrestrial microwave links, the rain attenuation calculation is given as below:

A = γ R .

L .

r

where:

γ R = Specific attenuation

L = Path length r = Reduction factor

The specific attenuation γ R (db/km) is obtained from the rain rate using the power law relationship:

γ R = kR

α

where:

R = rain rate at p% probability level k , α = frequency dependant ITU-R regression coefficients

10

Values and α are determined as functions of frequencies, F (GHz) in the range from 1 to 1000 GHz. Their values also depend on polarization chosen to calculate the attenuation, either horizontal or vertical.

The path length L can be calculated by knowing the geographical positions of the twos stations (transmitter and receiver) [9] [10] [11].

The reduction factor r can be chosen from models provided by a number or researchers as explained in the next part.

2.1.1.1

Path Length Reduction Factors

As what has been shown earlier, there is a reduction factor that must be included and counted in the calculation of rain attenuation. This reduction factor is used to account the inhomogenity of rain along the propagation path. It is multiplied with the actual path length to obtain the effective path length:

L eff

= Lxr

where:

L r

= actual path length

= reduction factor

The reduction factor r depends on the spatial distribution of rain rate and account for the horizontal variations of rain along a propagation path. There are several models proposed by a number of researcher regarding the reduction factor. Among the models

11 are Lin model, Moupfouma model, Assis model, Dissanayake and Allnutt model and as well as ITU-R model [12].

Rain rate and rain attenuation data collected from two different locations in

Malaysia have been used to investigate the various models proposed for the path length reduction factor [12]. Based on the preliminary results, the ITU-R predictions are much lower than the measured attenuation, and Moupfouma model has been found to produce good results [12].

Based on results from the research done, Moupfouma model is used as a reduction factor in this project as it is recommended for the Malaysian region.

2.1.1.2

Moupfouma Model As a Reduction Factor [13]

The reduction factor suggested by Moupfouma is given by: r =

1 + 0 .

03

1

P

0 .

01

− β l m

with m ( F , l ) = 1 + ψ ( F ) log e l

and

ψ ( F ) = 1 .

4 X 10 − 4 F 1 .

76

where:

F = Frequency in GHz

β coefficient is given as a result of best fit by:

12

β = 0.45, for 0.01

≤ P (percent) ≤ 0.01

β = 0.6, b) For l ≥ 50 km for 0.01


β = 0.36,

β = 0.6, for 0.01

≤ P (percent) ≤ 0.01 for 0.01


The effective path length reflects the spatial inhomogenity. Its frequency dependence which appeared here in the reduction coefficient r results from both the nonuniformity of the rain along the radio path link, and the nonlinear dependence of the specific attenuation rain rate.

2.2 Some Models of Rain Attenuation Prediction

2.2.1 ITU-R Model of Rain Attenuation [14]

The prediction procedure below by ITU is considered valid in all parts of the world and may be used for estimating the long-term of rain attenuation. It is valid at least for frequencies up to 40 GHz and path length up to 60 km:

Step 1 : Obtain the rain rate R

0.01

exceeded for 0.01% of the time (with an integration of

13

1 min). If this information is not available from local sources of long-term

measurements, an estimate can be obtained from the information given in

Recommendation ITU-R P.837.

Step 2 : Compute the specific attenuation, γ

R

(db/km) for the frequency, polarization and

rain rate of interest. The specific attenuation is using the power-law

relationship and its computation is as below:

γ R = kR

α

where k

R

,

= rain rate at p% probability

α = functions of frequency, f (GHz) in the range 1 to 1000 GHz.

Values of k and α are given in Table 2.1.

It should be noted that horizontally polarized waves suffer greater attenuation

than vertically polarized waves because larger raindrops are generally shaped as

oblate spheroids and are aligned with the vertical rotation axis [3]. The letter h

and v notates horizontal and vertical polarizations, respectively.

Step 3 : Compute the effective path length, d eff

, of the link by multiplying the actual

path length d by a distance factor r . An estimate of this factor is given by:

where, for R

0 .

01

≤ 100mm/h: r =

1 +

1 d d

0 d o

= 35 e − 0 .

015 R

0 .

01

14

For R

0 .

01

≥ 100mm/h, use the value 100 mm/h in place of R

0 .

01

.

Step 4 : An estimate of the path attenuation exceeded for 0.01% of the time is given by:

A

0 .

01

= γ R .

d eff

= γ R .

d .

r dB

where d = path length r = reduction factor

Step 5 : For radio links located in latitudes and equal to or greater than 30° (North or

South), the attenuation exceeded for other percentages of time p in the range

0.001% to 1% may be deduced from the following power law:

A p

A

0 .

01

= 0 .

12 p − ( 0 .

546 + 0 .

043 log

10 p )

This formula has been determined to give factors of 0.12, 0.39, 1 and 2.14 for

1%, 0.1%, 0.01% and 0.001% respectively, and must be used only within this

range.

Step 6 : For radio links located at latitudes and below 30° (North or South), the

attenuation exceeded for other percentages of time p in the range 0.001% to 1%

may be deduced from the following power law:

A p

A

0 .

01

= 0 .

07 p − ( 0 .

855 + 0 .

139 log

10 p )

This formula has been determined to give factors of 0.07, 0.36, 1and 1.44 for

1%, 0.1%, 0.01% and 0.001% respectively, and must be used only within this

15

range.

Step 7 : If worst-month statistics are desired, calculate the annual time percentages p

corresponding to the worst-month time percentages p w

using climate

information specified in Recommendation ITU-R P.841. The values of A

exceeded for percentage of the time p on an annual basis will be exceeded for

the corresponding percentages of time p w

on a worst-month basis.

16

Table 2.1 Some of frequency dependent coefficient to calculate specific attenuation

Frequency

(GHz) k

H

α

H k

V

α

V

25 0.1571 0.9991 0.1533 0.9491

26 0.1724 0.9884 0.1669 0.9421

27 0.1884 0.9780 0.1813 0.9349

28 0.2051 0.9679 0.1964 0.9277

29 0.2224 0.9580 0.2124 0.9203

30 0.2403 0.9485 0.2291 0.9129

31 0.2588 0.9392 0.2465 0.9055

32 0.2778 0.9302 0.2646 0.8981

33 0.2972 0.9214 0.2833 0.8907

34 0.3171 0.9129 0.3026 0.8834

35 0.3374 0.9047 0.3224 0.8761

36 0.3580 0.8967 0.3427 0.8690

37 0.3789 0.8890 0.3633 0.8621

38 0.4001 0.8816 0.3844 0.8552

39 0.4215 0.8743 0.4058 0.8486

40 0.4431 0.8673 0.4274 0.8421

41 0.4647 0.8605 0.4492 0.8357

42 0.4865 0.8539 0.4712 0.8296

43 0.5084 0.8476 0.4932 0.8236

44 0.5302 0.8414 0.5153 0.8179

45 0.5521 0.8355 0.5375 0.8123

46 0.5738 0.8297 0.5596 0.8069

47 0.5956 0.8241 0.5817 0.8017

48 0.6172 0.8187 0.6037 0.7967

49 0.6386 0.8134 0.6255 0.7918

50 0.6600 0.8084 0.6472 0.7871

51 0.6811 0.8034 0.6687 0.7826

52 0.7020 0.7987 0.6901 0.7783

53 0.7228 0.7941 0.7112 0.7741

17

2.2.2

Crane Model

The Crane models, that is after Robert K. Crane is popular for space earth links.

He first presented his work on prediction of the effect of rain on satellite communication system in 1977. However, the Crane models also have terrestrial models. Actually, there are three versions of Crane models; the global Crane model , the two-component

Crane model and the revised two-component model [1].

The method below is used to predict the attenuation by rain on terrestrial propagation path. As a first step, the rain climate region of the end points of the path has to be determined. Calculating the outage is an iterative process that is based on the calculation of the attenuation.

For 22.5 km,

A = α R p

β

⎡

⎢

⎣

⎛

⎜⎜ e μβ d

μβ

− 1 ⎞

⎟⎟

−

⎛

⎜⎜ b β e c β x c β

⎞

⎟⎟

+

⎛

⎜⎜ b β e c β d c β

⎞

⎟⎟

⎤

⎥

⎦ dB

A = α R p

β

⎛

⎜⎜ e

μβ d

μβ

− 1 ⎞

⎟⎟

dB

μ , , and c can be calculated as follows: c x

=

μ = ln

( )

/ x b = 2 .

3 R

0 .

026 −

= 3 .

8 − 0 .

6 p

− 0

0 .

03

.

17 ln ln

R p

( )

where d = path length in kilometres

18

R p

= rain rate in millimeters per hour, determine from Crane tables e

α

= natural logarithm (log

, β

2.71828

)

= regression coefficients obtained from the table and interpolated if

necessary

First, it is necessary to determine the rainfall rate required to produce attenuation equal to the thermal fade margin. After that, determine the percent of the year this rain is exceeded. This value represents the annual two-way rain outage time for the path and is calculated using the rainfall statistics for the required geographic region.

If d

0

= 22.5 km and a modified probability of occurrence p 1: p 1 = p (22.5/ d )

2.2.3

Comparison of ITU-R and Crane Models

The ITU-R model consists of simple equations whereas the Crane model requires solution of more complex equation to obtain the path-averaged rain rate and a representation of the path profile by exponential functions. Furthermore, Crane’s derivations are overly empirical, sometimes hard to understand and difficult to extend

[1].

Crane model predicts a larger attenuation than the ITU-R model. However, this does not mean that the model’s prediction is not accurate. The Crane method is used mainly in United States while the ITU-R model is used more widely around the world.

It is in users hand to choose between Crane model and ITU model. What is important to remember is the more conservative method does not necessarily have to be more

19 accurate and on the other hand, more conservative method of calculation can lead to more expensive network design [1].

In this project, the ITU model will be used to develop the computer program to predict rain attenuation in Peninsular Malaysia except for its reduction factor because of its simpler way of calculation and has been used by researchers in Malaysia for quite some time, proving its accurateness.

CHAPTER 3

RESEARCH METHODOLOGY

This chapter explains the methodology adopted in making this project a success.

3.1

Phases of Methodology

This research methodology is separated into four phases to ensure the objectives are achieved. These separations contribute to a more arranged work of this project.

3.1.1

Analysis of Calculation

This project involves mainly on calculation of rain attenuation. As discussed in previous chapter, rain attenuation calculation includes specific attenuation and reduction factor. These two main things contribute to the result of attenuation due to rain. The overall calculations need to be understood and the best reduction factor has to be chosen to be implemented in this computer program development.

21

3.1.2

Planning

To achieve the objectives of this project, a good plan on steps to design the program is done. In this phase, a few milestone is marked by dividing the project into two parts, mainly designing and developing the program.

3.1.3

Design Phase

This phase is the most important as this project is mainly on building a computer program to predict rain attenuation. In this phase, all the consideration is made such as how the program is going to operate, what are the files needed to be associated with the program,, what are the output of the program, (examples: graphs and values) and how the interface will look like. The basic outline of the design is as figure 3.1.

3.1.4 Development and Testing Phase

After the design is done, the program is then developed using MATLAB 7.0.

The development process is ended with testing to ensure the result come out as expected and perform as designed.

1. Specific attenuation

2. Path length

3. Reduction factor

Calculation

Interface

• Rain attenuation

• Hop length

•

• Power received

Link budget diagram,

Results

Legend

Graphical User Interface (GUI)

Behind the GUI

Figure 3.1 Program design k, α coefficients file rain rate file

Files associated

22

23

Start

Literature review

Analysis of calculations

Planning

Program Design

Program

Development &

Testing

No

Ok?

Yes

Done

Figure 3.2 Flow Chart of the Methodology

3.2 Introduction to MATLAB

MATLAB (short for MATrix LABoratory) is a special-purpose computer program optimized to perform engineering scientific calculations. It started life as a program designed to perform matrix mathematics, but over the years it has grown into a flexible computing system capable of solving essentially any technical problems.

24

The MATLAB program implements the MATLAB language, and provides a very extensive library of predefined functions to make technical programming tasks easier and more efficient. This extremely wide variety of functions makes it much easier to solve technical problems in MATLAB than in other language such as Fortran and C.

Figure 3.3 Screenshot of MATLAB

MATLAB has many advantages compared to conventional computing language for technical problems solving [15]. Among them are:

1.

Ease of use

MATLAB is very easy to use. The programs may be easily written and modified with the built-integrated development environment, and debugged with MATLAB debugger.

25

2.

Platform independence

MATLAB is supported on many different computer systems, providing a large measure of platform independences. Programs written in MATLAB can migrate to new platforms when the needs of the user change.

3.

Predefined function

MATLAB comes complete with an extensive library of predefined functions that provide tested and prepackaged solutions to many basic technical tasks.

In addition to the large library of functions built into the basic MATLAB language, there are many special-purpose toolboxes available to help solve complex problems in specific areas.

4.

Device-Independent Plotting

Unlike other computer languages, MATLAB has many integral plotting and imaging commands. The plots and images can be displayed on any graphical output device supported by the computer on which MATLAB is running.

5.

Graphical User Interface

MATLAB includes tools that allow a programmer to interactively construct a graphical user interface (GUI) for his or her program. With this capability, the programmer can design sophisticated data analysis programs that can be operated by relatively inexperienced user. Figure 3.3 shows the screenshot of guide.

26

Figure 3.4 Screenshot of guide

MATLAB is chosen to develop this simulator because its program can handle calculation very well and it is associated with Graphical User Interface (GUI) that is going to be used in this project.

CHAPTER 4

RESULTS AND ANALYSIS

This chapter covers the results obtained from this project. The results include the program visual design, implementation, testing and user guide to use the program.

Analysis of the results is also done by comparing them with the output from ITU-R model.

4.1

Introduction

A computer program in MATLAB has been developed to predict attenuation due to rainfall based on the data rain from previous research in UTM. The program is uploaded with rain rate statistic proposed by Chebil [15] for 99 locations in Peninsular

Malaysia. These locations are shown in Figure 4.1.

This program is built using MATLAB GUIs 7.0 (guide). It is called RAPS1 where RAPS stands for Rain Attenuation Prediction Software. It can be used to predict rain attenuation for terrestrial microwave links in Peninsular Malaysia.

28

Figure 4.1 Locations of rain rate collected

4.2

Visual Design

This program has been designed to have two windows; introductory window and main working window.

The introductory window has two push buttons, ‘Yes’ and ‘No’. If the user wants to proceed predicting rain attenuation, he has to click ‘Yes’. Otherwise, he has to click ‘No’.

29

Figure 4.2 Introductory window

The main working window is divided into two parts. The rain attenuation prediction portion is at the left hand side and the link analysis tool is at the right hand side. There are five pushbuttons at the window. They are: a) ‘Predict’ pushbutton b) ‘Calculate and Plot’ pushbutton c) ‘Reset’ pushbutton d) ‘Help’ pushbutton e) ‘Exit’ pushbutton

The main working window also contains thirty three static edit text boxes where text is written in it, twelve edit text boxes for the latitude and longitude of station A and

B, a pop up menu to choose type of polarization (horizontal or vertical), an edit text box to put desired frequency and two edit text boxes to display the predicted rain attenuation and calculated hoplength.

Another three edit text boxes at the main working window are for a user to enter value of power transmitted, transmitter gain and receiver gain. One edit text box to display calculated value of power received at the receiver is also there.

30

Figure 4.3 Main working window

4.3

Implementation

After the visual has been designed, all the components are required to be linked with the code or callbacks to make them perform their specific task. As for the introductory window, the ‘Yes’ pushbutton is linked to the main working window while the ‘No’ pushbutton is linked to the ‘close’ callback.

At the main working windows, there are five pushbuttons. Their specific task is as follows: a) The ‘Reset’ pushbutton is linked with callback to clear the edit text boxes b) The ‘Help’ pushbutton is linked with callback to display Help window c) The ‘Exit’ pushbutton is linked with callback to close the program

31 d) The ‘Predict’ pushbutton is linked with callback that does a number of job before displaying the result e) The ‘Calculate and Plot’ pushbutton is linked with callback that does the same job as ‘Predict’ pushbutton’s callback, but it has additional task before the result is shown

The code linked with the ‘Predict’ pushbutton performs these following tasks before it can display the results: i) Loads the rain data file and the coefficient file ii) Read the user’s data fed in the edit text boxes of latitude and longitude for both station A and B iii) Base on the latitude and longitude entered by the user, this program searches for the nearest location out of 99 locations where rain data is available. After obtaining the rain rates for station A and B, the rain rates are compared and the highest of two is considered for rain attenuation prediction iv) In case where the desired frequency entered by the user is no available in the file uploaded, this program calculates regression coefficient k and

α using ITU-R defined interpolation method v) The hop length is calculated by this program through the geographical position of the two stations, that is the latitude and longitude of both stations. A separate function, ‘Hoplength’ has been defined to calculate the path length. vi) This program then calculates the rain attenuation and displays the results.

The hop length calculated is also displayed.

Example of outputs displayed when the ‘Predict’ pushbutton is clicked after all the necessary values have been entered is as figure 4.4.

32

Figure 4.4 Example of output (1)

The code linked with the ‘Calculate and Plot’ pushbutton performs the same tasks as the code linked with ‘Predict’ pushbutton, except that it has additional tasks: i) Based on gain of transmitter, gain of receiver and power transmitted values entered by the user, this code calculates the power received at the receiver side. ii) It then plots the power level diagram and displays the plotted graph and also the power received at the receiver.

Example of outputs displayed when the ‘Calculate and Plot’ button is clicked after all the necessary values are entered is as figure 4.5.

33

Figure 4.5 Example of output (2)

4.4

Program Limitations

This program that has been built has some limitations. It can only run on

Windows 95, 98 and XP. The frequency range that is valid for calculation is from 1

GHz to 50 GHz only. In addition, the maximum path length that can be considered by this software in predicting the rain attenuation is up to 58 kilometers only. It is in line with the outcome from Moupfouma [6] where it says that predictions derived for path length up to 58 kilometers are in good agreement with the experimental data.

Furthermore, this program can only predict rain attenuation in Peninsular Malaysia since the data rain available is just for that particular part of Malaysia.

34

4.5

Program User Guide

For a user that wants to use this program, he needs to have installed MATLAB

7.0 in his computer or laptop. The program need all the files listed below to be resided in the ‘work’ directory of MATLAB 7.0: i) RAPS1.fig ii) RAPS1.m iii) Projek2c.fig iv) Projek2c.m v) Hoplength.m vi) raindata.mat vii) coefficient.mat

RAPS1.fig and RAPS1.m are figure files. They contain the actual graphical user interface that have been created. RAPS1.m and Projek2c.m contains the code to load the figures and the callbacks for each element in the figure. The Hoplength.m file contains code for hop length function which is to calculate path length between Station A and

Station B. The fraindata.mat holds rain data for Peninsular Malaysia whereas the coefficient.mat file holds ITU regression coefficient.

To use this program, a user has to type RAPS1 in MATLAB command window.

The introductory window will appear. The user has to click ‘Yes’ to proceed using the software or ‘No’ if he wants to exit the program.

If ‘Yes’ button is clicked, the main working window will be displayed. The user can continue using the program by entering the necessary values and by clicking the necessary pushbuttons.

35

If a user entered invalid information or made mistakes, this program can guide him through an ‘Error’ message box indicating the error. Among the ‘Error’ message boxes that might appear are as Figure 4.6, Figure 4.7, Figure 4.8 and Figure 4.9 below.

In case a user wants to know how to use this program, he can click the ‘Help’ button and a ‘Help’ message box will appear. The ‘Help’ message box is as Figure 4.10.

Figure 4.6 ‘Error’ message box (1)




36

Figure 4.10 ‘Help’ message box

37

4.6

Additional Features of the Program

This program is added with some additional feature to give users extra useful information. A user can view power level diagram by entering the value of power transmitted and gain of transmitter and receiver. With this feature, additional link budget for rain fade can be prepared to improve the reliability of the signals that is going to be transmited.

4.7

Example of Program Output For Predicted Rain Attenuation

This program has been run to predict rain attenuation at three different locations in Peninsular Malaysia. The locations chosen are Johor Bahru, Jelebu and Sitiawan.

The rain rate at Johor Bahru is 120.3572 mm/h while at Sitiawan is 103.575 mm/h. The rain rate at Jelebu is 96.4741 mm/h, where Jelebu is the most dry place in Malaysia.

Table 4.1 shows the output predicted by RAPS1 for these three locations.

From the table, the path length chosen is from 2.74 kilometers to 3.69 kilometers.

These path lengths are chosen according to the suitability of wireless communication in millimeter waves.

38

Table 4.1 Example of program output at three different locations in Peninsular Malaysia

Location Rain rate

Path

Rain Attenuation (dB) length 26 GHz 38 GHz

(R

0.01

in mm/h) (km) V H V H

Johor

Bahru 120.3572 2.96 41.0 55.5 62.1 73.3

3.51 47.9 64.7 72.2 85.3

Jelebu 96.4741 2.74 31.0 41.4 47.8 56.2

3.66 40.2 53.7 61.9 72.6

Sitiawan 103.5760 2.76 33.7 45.3 51.7 60.9

3.69 43.7 58.6 66.7 78.5

4.8

Analysis of the Results

The results obtained from RAPS1 program are compared to the results from

ITU-R model. The comparison is done in two parts. First comparison is done by comparing the outcome of RAPS1 with the results from ITU-R model of rain attenuation where the rain rate of 120 mm/h is used by the model. Second comparison is done by differentiating the results from RAPS1 with the results produced utilizing ITU-R reduction factor but using the local rain rate from this project

39

4.8.1 Comparison of the Output of RAPS1 with Results from ITU-R Model of

Rain Attenuation

This firs part of comparison is done to show the differences of the outputs between RAPS1 ITU-R model of rain attenuation. The comparison done is shown as

Table 4.2 and Table 4.3 below.

From Table 4.2, we can see that at 26 GHz, the percentage of differences is between 0.6% to 23.2% for Vertical polarization with and 2.9% to 26.7% for Horizontal polarization. At 38 GHz, the range of differences is between 0.8% to 22.6% for Vertical polarization and 0.4% to 22.6% for Horizontal polarization.

Obviously from these tables, the differences are quite large. Although in numbers, The ITU-R model gives slightly less attenuation due to rain, but it is not reliable due to the rain rates used by it do not represent the actual data. This will certainly affect the reliability of communication here in Malaysia, where communication designers may under estimate the rain attenuation when they want to design their circuits.

40

Table 4.2 Comparison between output from RAPS1 and ITU-R model of rain attenuation at 26 GHz

Location

Rain Attenuation (dB) at 26

GHz

Path length RAPS1 ITU-R

% of difference

(km) V H V H V H

Johor

Bahru 2.96 41.0 55.5 32.8 42.3 20.0 23.8

3.51 47.9 64.7 36.8 47.4 23.2 26.7

Jelebu 2.74 31.0 41.4 31.2 40.2 0.6 2.9

3.66 40.2 53.7 38.3 49.4 4.7 8.0

Sitiawan 2.76 33.7 45.3 31.0 40.0 8.0 11.7

3.69 43.7 58.6 38.1 49.1 12.8 16.2

Table 4.3 Comparison between output from RAPS1 and ITU-R model of rain attenuation at 38 GHz

Location

Path length

Rain Attenuation (dB) at 38

GHz

RAPS1 ITU-R

% of difference

(km) V H V H V H

Johor

Bahru 2.96 62.1 73.3 49.8 58.9 19.8 19.6

3.51 72.2 85.3 55.9 66.0 22.6 22.6

Jelebu 2.74 47.8 56.2 47.4 56.0 0.8 0.4

3.66 61.9 72.6 58.2 68.8 6.0 5.2

Sitiawan 2.76 51.7 60.9 47.1 55.6 8.9 8.7

3.69 66.7 78.5 57.9 68.3 13.2 13.0

41

4.8.2

Comparison of the Output of RAPS1 with Results Produced Utilizing ITU-R

Reduction Factor but Using the Local Rain Rate

The second comparison is done to show the significance of using Moupfouma model of path length reduction factor instead of reduction factor of ITU-R model. The comparisons for both at 26 GHz and 38 GHz are shown in Table 4.4 and Table 4.5.

From Table 4.4, it is clear that at 26 GHz, rain attenuation is lower when reduction factor from ITU-R model is used. It goes the same behavior when rain attenuation is predicted at 38 GHz, as shown in Table 4.5. The percentage of differences varies from 19.8% to 27.5% for attenuation at 26 GHz and from 19.5% to 23.6% for attenuation at 38 GHz.

These outcomes is in line with the research using experimental data by Islam

[12] where it says that the ITU-R predictions are much more lower than the measured attenuation. Consequently, the comparison clearly indicates that the percentages of differences are logical enough and should be noted by communication designers here in

Malaysia.

Table 4.4 Comparison of the output of RAPS1 with results produced utilizing ITU-R reduction factor at 26 GHz

Rain Attenuation (dB) at 26 GHz

% of difference

Location

Path length Rain rate

(R0.01 in

RAPS1

Using ITU-R reduction factor

(km)

Johor

3.51 47.9 64.7 36.9 47.6 23.0 26.4

3.66 40.2 53.7 31.2 39.8 22.4 25.9

Sitiawan 2.76 103.5760 33.7 45.3 27.0 34.6 19.9 23.6

3.69 43.7 58.6 33.2 42.5 24.0 27.5

42

Table 4.5 Comparison of the output of RAPS1 with results produced utilizing ITU-R reduction factor at 38 GHz

Location

Johor

Path length Rain rate

(R0.01 in

Rain Attenuation (dB) at 38 GHz

RAPS1

Using ITU-R reduction factor

% of difference

(km)

3.51 72.2 85.3 56.0 66.1 22.4 22.5

3.66 61.9 72.6 48.3 56.8 22.0 21.8

Sitiawan 2.76 103.5760 51.7 60.9 41.5 48.9 19.7 19.7

3.69 66.7 78.5 51.0 60.0 23.5 23.6

43

CHAPTER 5

CONCLUSION AND PROPOSED FUTURE WORKS

This chapter concludes the research and the results obtained. It also covers the proposed future works that can be implemented by future researchers to further enhance this project.

5.1

Conclusion

The objectives of this project are successfully achieved where the program to predict rain attenuation is built using MATLAB 7.0. Besides using local data rain obtained from previous research in UTM, this program uses Moupfouma model as its reduction factor which is recommended to be used to calculate rain attenuation in

Malaysia.

The simulated results obtained from this program are reliable as it shows the accurateness of rain attenuation prediction. The accuracy of the results is supported by the experimental data done by researches here in Malaysia [12]. These results can be referred by communication designers to design reliable communication circuits in

Malaysia, particularly in Peninsular Malaysia.

45

5.2

Proposed Future Works

The usage of Moupfouma model as a reduction factor is based on outcome from a research in year 2000. Rain rate and rain attenuation data collected from two different locations in Malaysia have been used for the experiment by the researchers. If it is possible, the research on reduction factor has to be done for further verification on the effectiveness of the Moupfouma model to be used in Malaysia.

This program also can be upgraded to predict rain attenuation in East Malaysia as well. This however requires data rain of that particular region to be collected first. If this can be done, then this program is hundred percent reliable to be used in Malaysia.

46

REFERENCES

1.

Lehpamer, H. Microwave Transmission Networks Planning, Design, and

Deployment. United States: McGraw-Hill. 2004.

2.

Yunjiang Liu; Guoce Huang; Shunchun Zhen. Performance Analysis of Ka-

Band Satellite Channel Capacity in the Presence of Rain Attenuation.

Proceedings of the Microwave and Milimeter Wave Technology, 2004.

ICMMT 4th International Conference. 18-21 Aug. IEEE. 2004. 175-177.

3.

Freeman, R.L. Radio System Design for Telecommunications. United States:

John Wiley & Sons. 1997.

4.

Khajepiri, F.; Ghorbanii, A.; Amindavar, H. A new method for estimating rain attenuation at high frequencies. Proceedings of the 9th International

Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and

Acoustic Wave Theory,2004. 11-14 Oct. IEEE. 2004. 43-46

5.

Yagasena, A.; Hassan, S.I.S. Worst-month rain attenuation statistics for satellite Earth link design at Ku-band in Malaysia. Proceedings TENCON

2000. Volume 24-27 Sept.IEEE. 2000. 122-125.

6.

Rec. ITU-R PN.837-1. Characteristic of precipitation for propagation modeling. PN Series Volume. ITU. Geneva. 1994.

47

7.

Rec. ITU-R P.837-4. Characteristics of precipitation for propagation modeling. ITU. Geneva. 2003.

8.

Crane, K.R. Prediction of the Effects of Rain on Satellite Communication

Systems. Proceedings of the IEEE, Vol. 65, No.3. IEEE. 1977. 456-474.

9.

MR. PC+ (1995). “Microwave radio path calculations plus”, Version 2.4,

Harris Corporation, Farinon Division.

10.

Bernhardsen, Tor. Geographic Information Systems, An Introduction. John

Wiley & Sons, Inc. Norway. 2001.

11.

Worboys,M, Duckham, M. GIS A Computing Perspective. CRC Press.

US.2004.

12.

Islam, M.R.; Tharek, A.R.; Chebil, J. Comparison between path length reductionfactor models based on rain attenuation measurements in Malaysia.

Asia Pacific Microwave Conference. 3-6 Dec. IEEE. 2000. 1556-1560.

13.

Moupfouma, F. Improvement of a rain attenuation prediction method for terrestrial microwave links. IEEE Transaction on Antennas and Propagation

[legacy, pre-1988] Volume 32. Dec 1984. IEEE. 1368-1372.

14.

Rec. ITU-R p.530-12. Propagation data and prediction methods required for the design of terrestrial line-of-sight systems. ITU. Geneva. 2007.

15.

Chebil J. Rain Rate and Rain Attenuation Distribution For Microwave

Propagation Study in Malaysia. Ph.D. Thesis. Faculty of Electrical

Engineering,University of Technology Malaysia (UTM). 1997

48

16.

Chapman, S.J. MATLAB ® Programming for Engineers. Second Edition.

Canada: Brooks/Cole. 2002.

APPENDIX A

MATLAB Self Generated Code for Introductory Window function varargout = RAPS1(varargin)

% RAPS1 M-file for RAPS1.fig

% RAPS1 by itself, creates a new RAPS1 or raises the

% existing singleton*.

% H = RAPS1 returns the handle to a new RAPS1 or the handle to

% the existing singleton*.

% RAPS1('CALLBACK',hObject,eventData,handles,...) calls the local

% function named CALLBACK in RAPS1.M with the given input arguments.

% RAPS1('Property','Value',...) creates a new RAPS1 or raises the

% existing singleton*. Starting from the left, property value pairs are

% applied to the GUI before RAPS1_OpeningFunction gets called. An

% unrecognized property name or invalid value makes property application

% stop. All inputs are passed to RAPS1_OpeningFcn via varargin.

% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one

% instance to run (singleton)".

% See also: GUIDE, GUIDATA, GUIHANDLES

% Copyright 2002-2003 The MathWorks, Inc.

49

% Edit the above text to modify the response to help RAPS1

% Last Modified by GUIDE v2.5 25-Mar-2002 12:19:15

% Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ...

'gui_Singleton', gui_Singleton, ...

'gui_OpeningFcn', @RAPS1_OpeningFcn, ...

'gui_OutputFcn', @RAPS1_OutputFcn, ...

'gui_LayoutFcn', [] , ...

'gui_Callback', []); if nargin && ischar(varargin{1})

gui_State.gui_Callback = str2func(varargin{1}); end if nargout

[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); else

gui_mainfcn(gui_State, varargin{:}); end

% End initialization code - DO NOT EDIT

% --- Executes just before RAPS1 is made visible. function RAPS1_OpeningFcn(hObject, eventdata, handles, varargin)

% This function has no output args, see OutputFcn.

% hObject handle to figure

% eventdata reserved - to be defined in a future version of MATLAB

% handles structure with handles and user data (see GUIDATA)

% varargin command line arguments to RAPS1 (see VARARGIN)

% Choose default command line output for RAPS1 handles.output = 'Yes';

50

% Update handles structure guidata(hObject, handles);

% Insert custom Title and Text if specified by the user

% Hint: when choosing keywords, be sure they are not easily confused

% with existing figure properties. See the output of set(figure) for

% a list of figure properties. if(nargin > 3)

for index = 1:2:(nargin-3),

if nargin-3==index, break, end

switch lower(varargin{index})

case 'title'

set(hObject, 'Name', varargin{index+1});

case 'string'

set(handles.text1, 'String', varargin{index+1});

end

end end

% Determine the position of the dialog - centered on the callback figure

% if available, else, centered on the screen

FigPos=get(0,'DefaultFigurePosition');

OldUnits = get(hObject, 'Units'); set(hObject, 'Units', 'pixels');

OldPos = get(hObject,'Position');

FigWidth = OldPos(3);

FigHeight = OldPos(4); if isempty(gcbf)

ScreenUnits=get(0,'Units');

set(0,'Units','pixels');

ScreenSize=get(0,'ScreenSize');

51

set(0,'Units',ScreenUnits);

FigPos(1)=1/2*(ScreenSize(3)-FigWidth);

FigPos(2)=2/3*(ScreenSize(4)-FigHeight); else

GCBFOldUnits = get(gcbf,'Units');

set(gcbf,'Units','pixels');

GCBFPos = get(gcbf,'Position');

set(gcbf,'Units',GCBFOldUnits);

FigPos(1:2) = [(GCBFPos(1) + GCBFPos(3) / 2) - FigWidth / 2, ...

(GCBFPos(2) + GCBFPos(4) / 2) - FigHeight / 2]; end

FigPos(3:4)=[FigWidth FigHeight]; set(hObject, 'Position', FigPos); set(hObject, 'Units', OldUnits);

% Show a question icon from dialogicons.mat - variables questIconData

% and questIconMap load dialogicons.mat

IconData=questIconData; questIconMap(256,:) = get(handles.figure1, 'Color');

IconCMap=questIconMap;

Img=image(IconData, 'Parent', handles.axes1); set(handles.figure1, 'Colormap', IconCMap); set(handles.axes1, ...

'Visible', 'off', ...

'YDir' , 'reverse' , ...

'XLim' , get(Img,'XData'), ...

52

'YLim' , get(Img,'YData') ...

);

% Make the GUI modal set(handles.figure1,'WindowStyle','modal')

% UIWAIT makes RAPS1 wait for user response (see UIRESUME) uiwait(handles.figure1);

% --- Outputs from this function are returned to the command line. function varargout = RAPS1_OutputFcn(hObject, eventdata, handles)

% varargout cell array for returning output args (see VARARGOUT);




% Get default command line output from handles structure varargout{1} = handles.output;

% The figure can be deleted now delete(handles.figure1);

% --- Executes on button press in pushbutton1. function pushbutton1_Callback(hObject, eventdata, handles)

% hObject handle to pushbutton1 (see GCBO)


% handles structure with handles and user data (see GUIDATA) handles.output = get(hObject,'String');


53

% Use UIRESUME instead of delete because the OutputFcn needs

% to get the updated handles structure. uiresume(handles.figure1);




% handles structure with handles and user data (see GUIDATA) handles.output = get(hObject,'String');


% Use UIRESUME instead of delete because the OutputFcn needs

% to get the updated handles structure. uiresume(handles.figure1);

%close(handles.figure1);

% --- Executes when user attempts to close figure1. function figure1_CloseRequestFcn(hObject, eventdata, handles)

% hObject handle to figure1 (see GCBO)


% handles structure with handles and user data (see GUIDATA) if isequal(get(handles.figure1, 'waitstatus'), 'waiting')

% The GUI is still in UIWAIT, us UIRESUME

uiresume(handles.figure1); else

54

% The GUI is no longer waiting, just close it

delete(handles.figure1); end

% --- Executes on key press over figure1 with no controls selected. function figure1_KeyPressFcn(hObject, eventdata, handles)




% Check for "enter" or "escape" if isequal(get(hObject,'CurrentKey'),'escape')

% User said no by hitting escape

handles.output = 'No';

% Update handles structure

guidata(hObject, handles);

uiresume(handles.figure1); end if isequal(get(hObject,'CurrentKey'),'return')

uiresume(handles.figure1); end

55

APPENDIX B

MATLAB Self Generated Code for Main Working Window function varargout = Projek2c(varargin)

% PROJEK2C M-file for Projek2c.fig

% PROJEK2C, by itself, creates a new PROJEK2C or raises the existing

% singleton*.

% H = PROJEK2C returns the handle to a new PROJEK2C or the handle to

% the existing singleton*.

% PROJEK2C('CALLBACK',hObject,eventData,handles,...) calls the local

% function named CALLBACK in PROJEK2C.M with the given input arguments.

% PROJEK2C('Property','Value',...) creates a new PROJEK2C or raises the

% existing singleton*. Starting from the left, property value pairs are

% applied to the GUI before Projek2c_OpeningFunction gets called. An

% unrecognized property name or invalid value makes property application

% stop. All inputs are passed to Projek2c_OpeningFcn via varargin.

% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one

% instance to run (singleton)".

% See also: GUIDE, GUIDATA, GUIHANDLES

% Copyright 2002-2003 The MathWorks, Inc.

56

% Edit the above text to modify the response to help Projek2c

% Last Modified by GUIDE v2.5 15-Feb-2008 14:36:40

% Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ...

'gui_Singleton', gui_Singleton, ...

'gui_OpeningFcn', @Projek2c_OpeningFcn, ...

'gui_OutputFcn', @Projek2c_OutputFcn, ...

'gui_LayoutFcn', [] , ...

'gui_Callback', []); if nargin && ischar(varargin{1})

gui_State.gui_Callback = str2func(varargin{1}); end if nargout

[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); else

gui_mainfcn(gui_State, varargin{:}); end

% End initialization code - DO NOT EDIT

% --- Executes just before Projek2c is made visible. function Projek2c_OpeningFcn(hObject, eventdata, handles, varargin)

% This function has no output args, see OutputFcn.




% varargin command line arguments to Projek2c (see VARARGIN)

% Choose default command line output for Projek2c handles.output = hObject;

57


% UIWAIT makes Projek2c wait for user response (see UIRESUME)

% uiwait(handles.figure1);

% --- Outputs from this function are returned to the command line. function varargout = Projek2c_OutputFcn(hObject, eventdata, handles)

% varargout cell array for returning output args (see VARARGOUT);




% Get default command line output from handles structure varargout{1} = handles.output; function edit1_Callback(hObject, eventdata, handles)

% hObject handle to edit1 (see GCBO)



% Hints: get(hObject,'String') returns contents of edit1 as text

% str2double(get(hObject,'String')) returns contents of edit1 as a double

% --- Executes during object creation, after setting all properties. function edit1_CreateFcn(hObject, eventdata, handles)



% handles empty - handles not created until after all CreateFcns called

% Hint: edit controls usually have a white background on Windows.

% See ISPC and COMPUTER. if ispc

58

set(hObject,'BackgroundColor','white'); else

set(hObject,'BackgroundColor',get(0,'defaultUicontrolBackgroundColor')); end function edit2_Callback(hObject, eventdata, handles)



















59





















60




















% --- Executes during object creation, after setting all properties.

61

function edit6_CreateFcn(hObject, eventdata, handles)




















set(hObject,'BackgroundColor',get(0,'defaultUicontrolBackgroundColor'));

62

end function edit8_Callback(hObject, eventdata, handles)


















% str2double(get(hObject,'String')) returns contents of edit9 as a

63





















set(hObject,'BackgroundColor',get(0,'defaultUicontrolBackgroundColor'));

64

end function edit11_Callback(hObject, eventdata, handles)



















% --- Executes during object creation, after setting all properties.

65

function edit12_CreateFcn(hObject, eventdata, handles)







set(hObject,'BackgroundColor',get(0,'defaultUicontrolBackgroundColor')); end

% --- Executes on selection change in popupmenu1. function popupmenu1_Callback(hObject, eventdata, handles)

% hObject handle to popupmenu1 (see GCBO)



% Hints: contents = get(hObject,'String') returns popupmenu1 contents as cell array

% contents{get(hObject,'Value')} returns selected item from popupmenu1

%To read polarity from popupmenu

% --- Executes during object creation, after setting all properties. function popupmenu1_CreateFcn(hObject, eventdata, handles)

% hObject handle to popupmenu1 (see GCBO)



% Hint: popupmenu controls usually have a white background on Windows.



66




















67







% handles structure with handles and user data (see GUIDATA) function edit14_Callback(hObject, eventdata, handles)














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function edit16_Callback(hObject, eventdata, handles)














% --- Executes on key press over figure1 with no controls selected. function figure1_KeyPressFcn(hObject, eventdata, handles)




% --- Executes when user attempts to close figure1. function figure1_CloseRequestFcn(hObject, eventdata, handles)

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% Hint: delete(hObject) closes the figure delete(hObject); function edit17_Callback(hObject, eventdata, handles)


















70





















set(hObject,'BackgroundColor','white');

71

else




















72




73

74

APPENDIX C

MATLAB Code Associated with ‘Predict’ Pushbutton of Main Working Window

load raindata;

load coefficient;

%To read and convert string to number for latitude of station A

A1=findobj(gcbf,'Tag','edit1');

Lat1a=str2double(get(A1,'string')); u1=[Lat1a];





%To read and convert string to number for logitude of station A


Long1a=str2double(get(A11,'string')); u11=[Long1a];





%To read and convert string to number for latitude of station B

B1=findobj(gcbf,'Tag','edit7');

Lat1b=str2double(get(B1,'string')); v1=[Lat1b];





%To read and convert string to number for logitude of station B


Long1b=str2double(get(B11,'string')); v11=[Long1b];



75

76



%Conversion of Latitude and Longitude of both station to decimal degree

Lata=(((Lat3a./60)+Lat2a)./60)+Lat1a;

LatA=round(20*Lata);

Longa=(((Long3a./60)+Long2a)./60)+Long1a;

LongA=round(20*Longa);

Latb=(((Lat3b./60)+Lat2b)./60)+Lat1b;

LatB=round(20*Latb); if

Longb=(((Long3b./60)+Long2b)./60)+Long1b;

LongB=round(20*Longb);

((Lata<1.4|Lata>6.6)|(Longa<99.6|Longa>104.3)|(Latb<1.4|Latb>6.6)|(Longb<99.6|Lon gb>104.3)) errordlg('Error,Latitude and Longitude must be between (1.5-5.4) and (99.8-103.9) in decimal degree.Please reenter new value','Error') return end

%To read frequency entered fr=findobj(gcbf,'Tag','edit13'); fre=get(fr,'string'); freq=str2double(fre); d=[freq];

77 if(isempty(d)|freq<1|freq>50) errordlg('Value of frequency entered invalid. Valid range is between 1-50 GHz.','Error') return end

%To read either vertical or horizontal pol=findobj(gcbf,'Tag','popupmenu1'); val=get(pol,'Value'); switch val

case 1

i=1;

case 2 i=2; end

%ITU-R interpolation in case the desired frequency entered is not in the list a=exp(interp1(log(f_itu),log(alist(:,i)),log(freq))); b=interp1(log(f_itu),blist(:,i),log(freq));

%To find the estimated rain rate

[XI,YI]=meshgrid(1.5:0.05:6.4,99.8:0.05:103.9);

ZI=griddata(x,y,z,XI,YI,'nearest');

[k,j]=find(round(20*XI)==LatA&round(20*YI)==LongA); y=[k,j];

78

[l,m]=find(round(20*XI)==LatB&round(20*YI)==LongB); g=[l,m]; if (isempty(y)|isempty(g)) errordlg('The Latitude and Longitude box cannot be left out empty,please put numeric 0 if the value for any box is zero.','Error') return end

Rainrate1=ZI(k(1),j(1));

Rainrate2=ZI(l(1),m(1)); if (Rainrate1>Rainrate2)

Rs=Rainrate1; else

Rs=Rainrate2; end if (isempty(Rs)) errordlg('Sorry, this program cannot predict rain attenuation for this location. Please check the Latitude and Longitude values.','Error') return end

%Go to Hop Length function

Hoplength=hoplength(Lata,Longa,Latb,Longb);

HL=Hoplength; if (HL>58)

errordlg('The maximum path length allowable is 58 km. This program cannot be proceeded.','Error'); return end

%To calculate reduction factor base on Moupfouma's formula psi=1.4*(10^-4)*(freq^1.76); em=1+(psi*(logm(HL))); if (HL<50)

rf=1./(1+((0.03)*(1^-0.45)*(HLêm))); else

rf=1./(1+((0.03)*(1^-0.36)*(HLêm))); end

%To calculate overall predicted rain attenuation

Pred_att=a*(round(Rs).^b)*HL*rf;

%To display the result of predicted rain attenuation qHndl=findobj(gcbf,'Tag','edit14'); q=get(gcbo,'string'); q=Pred_att; set(qHndl,'string',sprintf('%.1f',q));

%To display the result of hop length lHndl=findobj(gcbf,'Tag','edit16'); l=get(gcbo,'string');

79

l=HL; set(lHndl,'string',sprintf('%3.2f',l)); format short; clear A1 Lat1a A2 Lat2a A3 Lat3a A11 Long1a A22 Long2a A33 Long3a clear B1 Lat1b B2 Lat2b B3 Lat3b B11 Long1b B22 Long2b B33 Long3b clear Lata LatA Longa LongA Latb LatB Longb LongB clear pol var x_str Polar fr fre freq a b clear i j l m Rainrate1 Rainrate2 Rs Pred_att Hoplength clear 1Hndl1qHndl q Hl ZI

80

81

APPENDIX D

MATLAB Code Associated with ‘Calculate and Plot’ Pushbutton of Main Working

Window

%To read power transmit, transmitter gain and receiver gain entered

P1=findobj(gcbf,'Tag','edit17');

PT=str2double(get(handles.edit17,'string'));


GT=str2double(get(handles.edit18,'string'));


GR=str2double(get(handles.edit19,'string'));

load raindata;

load coefficient;

%To read and convert string to number for latitude of station A




Lat2a=str2double(get(A2,'string'));

u2=[Lat2a];



%To read and convert string to number for logitude of station A







%To read and convert string to number for latitude of station B






82


%To read and convert string to number for logitude of station B







%Conversion of Latitude and Longitude of both station to decimal degree

Lata=(((Lat3a./60)+Lat2a)./60)+Lat1a;

LatA=round(20*Lata);

Longa=(((Long3a./60)+Long2a)./60)+Long1a;

LongA=round(20*Longa);

Latb=(((Lat3b./60)+Lat2b)./60)+Lat1b;

LatB=round(20*Latb);

Longb=(((Long3b./60)+Long2b)./60)+Long1b;

LongB=round(20*Longb);

83

84 if

((Lata<1.4|Lata>6.6)|(Longa<99.6|Longa>104.3)|(Latb<1.4|Latb>6.6)|(Longb<99.6|Lon gb>104.3)) errordlg('Error,Latitude and Longitude must be between (1.5-5.4) and (99.8-103.9) in decimal degree.Please reenter new value','Error') return end

%To read frequency entered fr=findobj(gcbf,'Tag','edit13'); fre=get(fr,'string'); freq=str2double(fre); d=[freq]; if(isempty(d)|freq<1|freq>50) errordlg('Value of frequency entered invalid. Valid range is between 1-50 GHz.','Error') return end

%To read either vertical or horizontal pol=findobj(gcbf,'Tag','popupmenu1'); val=get(pol,'Value'); switch val

case 1

i=1;

case 2 i=2; end

85

%ITU-R interpolation in case the desired frequency entered is not in the list a=exp(interp1(log(f_itu),log(alist(:,i)),log(freq))); b=interp1(log(f_itu),blist(:,i),log(freq));

%To find the estimated rain rate

[XI,YI]=meshgrid(1.5:0.05:6.4,99.8:0.05:103.9);

ZI=griddata(x,y,z,XI,YI,'nearest');

[k,j]=find(round(20*XI)==LatA&round(20*YI)==LongA); y=[k,j];

[l,m]=find(round(20*XI)==LatB&round(20*YI)==LongB); g=[l,m]; if (isempty(y)|isempty(g)) errordlg('The Latitude and Longitude box cannot be left out empty,please put numeric 0 if the value for any box is zero.','Error') return end

Rainrate1=ZI(k(1),j(1));

Rainrate2=ZI(l(1),m(1)); if (Rainrate1>Rainrate2)

Rs=Rainrate1; else

Rs=Rainrate2; end if (isempty(Rs)) errordlg('Sorry, this program cannot predict rain attenuation for this location. Please check the Latitude and Longitude values.','Error') return end

%Go to Hop Length function

Hoplength=hoplength(Lata,Longa,Latb,Longb);

HL=Hoplength; if (HL>58)

errordlg('The maximum path length allowable is 58 km. This program cannot be proceeded.','Error'); return end

%To calculate reduction factor base on Moupfouma's formula psi=1.4*(10^-4)*(freq^1.76); em=1+(psi*(logm(HL))); if (HL<50)

rf=1./(1+((0.03)*(1^-0.45)*(HLêm))); else

86

rf=1./(1+((0.03)*(1^-0.36)*(HLêm))); end

%To calculate overall predicted rain attenuation

Pred_att=a*(round(Rs).^b)*HL*rf; qHndl=findobj(gcbf,'Tag','edit14'); q=get(gcbo,'string'); q=Pred_att;

LS=32.45+(20*log10(freq*1000))+(20*log10(HL));

PR=PT+GT+GR-LS-q;

PHndl=findobj(gcbf,'Tag','edit20');

P=get(gcbo,'string');

P=PR; set(PHndl,'string',sprintf('%.1f',P)); axes(handles.axes4);

%h=axes('XColor',[1 1 1],'YColor',[1 1 1]); x=[1 2 3 4 5]; y=[PT (PT+GT) (PT+GT-LS) (PT+GT-LS-q) (PT+GT-LS-q+GR)]; plot(x,y,'-or','LineWidth',2) set(handles.axes4,'XMinorTick','on') text(1,PT,'\ PT','HorizontalAlignment','left') text(2,(PT+GT),'\ PT+GT','HorizontalAlignment','left') text(3,(PT+GT-LS),'PT+GT-LS \','HorizontalAlignment','right') text(4,(PT+GT-LS-q),'PT+GT-LS-LR \','HorizontalAlignment','right') text(5,(PT+GT-LS-q+GR),'PT+GT-LS-LR+GR \','HorizontalAlignment','right')

87

title('POWER LEVEL DIAGRAM','Color','w'); xlabel('BLOCKS','Color','w'); ylabel('POWER LEVEL (dBm)','Color','w');

88

APPENDIX E

MATLAB Code for Hoplength Function function Hlength=Hoplength(Lata,Longa,Latb,Longb)

Lat_list=[0 1 2 3 4 5 6 7]';

Am_list=[-1.490273 -1.490274 -1.490275 -1.490277 -1.490281 -1.490285 -1.490289 -

1.490295]';

Bm_list=[0.002949 0.002949 0.002946 0.002941 0.002935 0.002927 0.002917

0.002906]';

%To calculate the difference between Lata and Longa and Latb and Longb format long; delta_phi=abs(3600*(Lata-Latb)); delta_gamma=abs(3600*(Longa-Longb)); if(Lata>Latb)

phi=Latb; else

phi=Lata; end phiem=phi+delta_phi/(2*3600);

89

%Calculation with conversion from degree to radian if(delta_gamma==0&delta_phi==0)

sumone=log10(cos((pi/180)*phim))+log10(eps); elseif(delta_gamma==0&delta_phi~=0)

sumone=log10(cos((pi/180)*phiem)); else

sumone=log10(cos((pi/180)*phiem))+log10(delta_gamma); end xx=fix(Lata); nn=find(Lat_list==xx);

Log_Am=Am_list(nn);

Log_Bm=Bm_list(nn); if(delta_gamma==0&delta_phi==0)

Azisum=Log_Bm+log10(cos((pi/180)*phiem))+log10(eps); elseif(delta_gamma==0&delta_phi~=0)

Azisum=Log_Bm+log10(cos((pi/180)*phiem)); else

Azisum=Log_Bm+log10(cos((pi/180)*phiem))+log10(delta_gamma); end if(delta_phi==0)

Azidiff=Azisum-log10(eps); else

Azidiff=Azisum-log10(delta_phi);

Cot_w=10.^(Azidiff); ww=acot(Cot_w);

90

zz=cos(ww); if(zz==0)

diffone=sumone-Log_Am-log10(eps); else

diffone=sumone-Log_Am-log10(zz); end

%Final result for hoplength

HL=(10.^(diffone))/1000; format short;

Hlength=HL; clear delta_phi delta_gamma phi phiem sumone clear xx nn Log_Am Log_Bm Azisum Azidiff Cot_w clear ww diffone HL end

91

i RELIABLE COMMUNICATIONS AT FREQUENCIES BANDS ABOVE 25 GHz IN THE TROPICS

Interface

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