International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Kuala Lumpur, Malaysia

978-1-4673-0479-5/12/$31.00 ©2012 IEEE

Analysis of Rain Fade Duration Over Satellite-Earth Path at Ku-Band in Tropics

Hassan Dao, Md. Rafiqul Islam, Khalid Al-Khateeb and Ahmad Fadzil Ismail Department of Electrical and Computer Engineering

International Islamic University Malaysia Kuala Lumpur, Malaysia

sun.spu@gmail.com, rafiq@iium.edu.my

Abstract—Statistical analysis is fundamental information for system engineer to design and plan satellite communication link. Fade duration is one aspect of fade dynamics that contributes designing of fade mitigation techniques (FMT). This paper presents statistical analysis on fade duration on high elevation angle (77.4̊) in Ku-band carried out in Kuala Lumpur, Malaysia with 12 months duration statistics.

Keywords-Fade duration; rain attenuation; fade mitigation technique.

I. INTRODUCTION Rain attenuation is primary cause for signal outage on

satellite-Earth above 10 GHz. Current demands of communication increase, role of communication design is significant. In order to design of high reliability for Ku-band TV services, a service provider has to employ appropriate of fade mitigation techniques (FMT) during severe rain fade period in overall design of the communications [1]. Common design and implementation of FMT requires first-order and second-order statistics of rain attenuation. Thus, knowledge of second-order statistics can assist service providers to elect appropriate FMT during rain severe rain periods [2].

Statistics of fade duration can be expressed by two different cumulative distribution function (CDF) such as probability of occurrence P(d>D|a>A) of fade duration d longer than D (s), given attenuation a is greater than A (dB) and probability of cumulative exceedance F(d>D|a>A), total fraction of time due to fades of duration d longer than D (s), given that attenuation a is greater than A (dB) [3].

This paper presents fade duration using statistics with two data sets such as unfiltered and filtered signal comparing to ITU-R P.1623 model.

II. EXPERIMENTAL SYSTEM AND DATA PROCESS The experimental system was carried out at faculty of

engineering, International Islamic university Malaysia (IIUM), Kuala Lumpur, Malaysia. Received signal level was collected from MEASAT3 at 10.982 GHz, elevation angle of 77.4 during 1st July 2010 to 30th June 2011. The logging data was sampling rate of 0.1s time interval and subsequently process to 1s. 0.2 mm tipping-bucket rain gauge is integrated in the system and

logged every 10s time interval to measure rainfall rate and determine rainy events. System elaboration can be found in [4].

Once logged data was processed to time interval of 1s, fade duration statistics have been analysed based on unfiltered and filtered signal. Filtered signal data set was discriminated scintillation during a rainy event by implemented of low pass filter (LPF) based on apposite cutoff frequency (fc). Welch method of Power spectral density (PSD) was implemented to obtain apposite fc of 25 mHz [5].

III. ANALYSIS OF FADE AND INTERFADE DURATION STATISTICS AND DISTRIBUTIONS

Fade duration is described as the time interval between two sequential crossings above the same attenuation level whereas interfade duration is defined as the time interval between two sequential crossings below the same attenuation level.

Data points of 1, 10, 30, 60, 120, 180, 300, 600, 900, 1200, 1500, 1800, 2400 and 3600s have been employed to analysed data distribution of fade duration statistics and comparing between measured data to the model recommended by ITU-R311-12 [6].

A. Number of fade events distribution Number of fade events of duration d (second) longer than a

certain duration value D (second), given that the attenuation a (dB) is greater than a certain attenuation value A (dB), N(d>D | a>A). Number of fade event is counted as one if its duration is longer than the given duration (D).

Fig. 1 and 2 present cumulative distribution statistics of number of fade duration and interfade duration events, respectively. These figures are presented with several attenuations of 4dB, 6dB and 8dB and compared between filtered data (dash line) and unfiltered data (solid line). Number of events for fade and interfade durations is reduced if duration time is longer. Unfiltered data has more number of events for short duration time when compared to filtered data due to scintillation effect.

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Figure 1. Number of fade duration events exceeding abscissa

Figure 2. Number of Interfade duration events exceeding abscissa

B. Total time of exceedance distribution The total fading time due to fades of duration d (second)

longer than a certain duration value D (second), given that the attenuation a (dB) is greater than a certain attenuation value A (dB), T(d>D | a>A). Total time value was calculated by duration summing of each event based on calculation in previous section (number of fade events).

Figure 3. Comparison of fade duration exceedance time

Figs. 3 and 4 depict exceedance time of fade and interfade

durations, respectively with different attenuation threshold. The result show that exceedance time is sparse varied for duration time between 1s and 100s for both durations and subsequently, noticeable variant for exceedance time longer than 100s.

Figure 4. Comparison of interfade duration exceedance time

C. Probability of occurrence Probability of occurrence P(d>D | a>A) can be estimated

by ratio of the number of fades of duration longer than D, N(d>D | a>A) to the total number of fades observed, Ntot(A) at given that the threshold A is exceeded presenting as in (1).

)(

)|()|(AtotN

AaDdNAaDdP ����� (1)

Figure 5. Occurrence probability of fade duration

Figure 6. Occurrence probability of interfade duration

Fig.5 depicts probability of occurrence for fade duration among ITU model, unfiltered and filtered data with several

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attenuations. Trend of unfiltered data is fitter to the model compared to filtered data. Comparison of interfade duration between unfiltered and filtered data is shown in fig. 6. Probability of occurrence of filtered data has higher slope at the same time duration.

D. Probability of cumulative exceedance Probability of cumulative exceedance, F(d>D | a>A) is

obtained by ratio of the total fading time due to fades of duration longer than D, T(d>D | a>A) given that the threshold A is exceeded to the total exceedance time Ttot(A) of the threshold A, presenting as in (2).

)(

)|()|(AtotT

AaDdTAaDdF ����� (2)

Figure 7. Probability of Total time of exceedance of fade duration

Figure 8. Total time of Exceedance of Interfade duration

Probability of cumulative exceedance of fade and interfade

durations have been depicted in figs. 7 and 8 respectively. Fade duration probability of exceedance has higher slope with decreasing of attenuation threshold at same time duration. Trend of model has not been agreed to measured data.

IV. AVERAGE FADE DURATIONS Average fade duration is a ratio of annual accumulated time

duration Ttot to annual number of occurrence event Ntot at a given fade threshold as presented in (3) [1] and average interval between fade events can be express by (4) [7].

)(sNTAverage

tot

totduration� (3)

)(24365int hr

NAverage

toterval � (4)

Table I Annual average duration and interval based on Unfiltered Data

Fade (dB)

Annual No. of Events

Accumulated Duration (s)

Average Duration (s)

Average Interval (Hour)

1 2315 1345874 581.37 3.78 2 4336 719683 165.98 2.02

3 1506 282231 187.40 5.82

4 724 146402 202.21 12.10

5 310 92309 297.77 28.26

6 318 61730 194.12 27.55

7 236 37275 157.94 37.12

8 154 19735 128.15 56.88

9 102 6035 59.17 85.88

10 23 1285 55.87 380.87 Table II Annual average duration and interval based on filtered Data

Fade (dB)

Annual No. of Events

Accumulated Duration (s)

Average Duration (s)

Average Interval (Hour)

1 781 1316234 1685.32 11.22 2 1185 669202 564.73 7.39

3 429 246981 575.71 20.42

4 274 139682 509.79 31.97

5 182 85530 469.95 48.13

6 150 59261 395.07 58.40

7 138 37644 272.78 63.48

8 75 18773 250.31 116.80

9 27 6529 241.81 324.44

10 10 836 83.60 876.00 Table I and II show result of annual average durations and intervals based on unfiltered and filtered data, respectively. Average durations and intervals of filtered data have considerably different to unfiltered data in statistical number due to filtered data

V. CONCLUSION Fade duration is analysed based on two data sets such as

filtered and unfiltered data. Unfiltered data is noticeably shown that it has higher number of events and exceedance times than filtered data. Unfiltered data set is fitted with the ITU-R model at a given fade threshold. Annual average

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durations and intervals have also been compared and presented with fade thresholds. Average duration and intervals of filtered data have longer duration due to scintillation removal. Statistical knowledge of fade duration has significant impact in designing earth-to-satellite communication system.

ACKNOWLEDGMENT The authors are very grateful to Research Management

Centre (RMC) of International Islamic University Malaysia (IIUM) for supporting this research through Endowment Type B grant.

REFERENCES 1. Q.W. Pan and J.E. Allnutt, "12-GHz Fade Durations and Intervals in the

Tropics", IEEE Trans. on antenna and propagation, 2004. Vol 52, No. 3.

2. M. Cheffena C. Amaya, "Prediction Model of Fade Duration Statistics for Satellite Links Between 10–50 GHz", IEEE Antennas and Wireless Propagation Letters, 2008. Vol. 7, p. 260 - 263.

3. ITU-R P.1623-1, "Prediction method of fade dynamics on Earth-space paths", 2005, Geneva, Switzerland.

4. Dao H, Islam M.R., Al-Khateeb Kh., "Modification of ITU-R Rain Fade Slope Prediction Model Based on Satellite Data Measured at High Elevation Angle", IIUM Engineering Journal (IIUMEJ), 2012.

5. Dao H., Islam M.R., Al-Khateeb Kh. and Khan Sh., "Preliminary Analysis of Ku-Band Rain Fade Data for Earth-to-Satellite Path Measured in Malaysia" in 10th Malaysia International Conference on Communications (MICC). October, 2011. Sabah, Malaysia: IEEE.

6. ITU-R P.311-12, "Acquisition, presentation and analysis of data in studies of tropospheric propagation", 2005, Geneva, Switzerland.

7. Zyoud, A., "Rain fade dynamics analysis for terrestrial microwave links operating in Malaysia", 2011, Master thesis, International Islamic University Malaysia (IIUM): Kuala Lumpur, Malaysia.

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