International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 127-132. Article ID: IJMET_10_03_012 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed INVESTIGATION AND EVALUATION OF SCINTILLATION PREDICTION MODELS AT OTA S. A. Akinwumi, T. V. Omotosho, M. R. Usikalu, M. E. Emetere, O. O. Adewoyin and T. A. Adagunodo Department of Physics, College of Science and Technology Covenant University PMB 1023, Ota, Ogun state, Nigeria O. O. Ometan and O. M. Adewusi Department of Physics, Lagos State University, Ojo, Lagos State, Nigeria ABSTRACT Understanding of scintillation is a significant occurrence in the design of communication satellite system. In this research, two years (January 2015-December o 2016) tropospheric scintillation records dig out from Astra 2E/2F/2G at 28.2 E o o Satellite path link observation at (Lat: 6.7 N, Long: 3.23 E) at Ota, southwest o Nigeria, at 12.245 GHz and an elevation angle 59.9 . The result and analysis were likened with some reliable tropospheric scintillation estimate models in order to acquire best model for Ota environment. The result findings revealed that the Karasawa model provides the minimum percentage error for scintillation fades and enhancements of approximately 0.57 % at 0.1 unavailability of time and 6.93 % at 0.01 unavailability of time respectively. Hence, Karasawa model is the most found suitable for the estimation of transmission loss in this region. Also, scintillation intensity is noticed to be high throughout the non-rainy season likened to rainy season months. Conversely, the model must be verified more by means of higher frequency band like Ka and V bands to affirm the accurateness of the model. The statistics provided in this work will assistance in fade margin for performance and antenna sizing required for communication satellite link. Keywords: Attenuation prediction, electromagnetic wave, Ku band, Satellite communication Tropospheric scintillation Cite this Article: S. A. Akinwumi, T. V. Omotosho, M. R. Usikalu, M. E. Emetere, O. O. Adewoyin, T. A. Adagunodo, O. O. Ometan and O. M. Adewusi, Investigation and Evaluation of Scintillation Prediction Models at Ota, International Journal of Mechanical Engineering and Technology, 10(3), 2019, pp. 127-132. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3 http://www.iaeme.com/IJMET/index.asp 127 editor@iaeme.com S. A. Akinwumi, T. V. Omotosho, M. R. Usikalu, M. E. Emetere, O. O. Adewoyin, T. A. Adagunodo, O. O. Ometan and O. M. Adewusi 1. INTRODUCTION Scintillation manifestations emerges to be unique of the major signal losses that effect satellite to earth path link in recent communication systems, particularly at Ku-band frequency and above [1, 2, 3, 4]. The impact of tropospheric scintillation on communication signal cannot be over emphasised owing to its continuous deviation in amplitude and phase that interrupt signal strength [5, 6]. At little millimeter-wave or microwave bands tropospheric scintillation intensity rise with fall in size of the antenna, angle of elevation and with surge in frequencies [7]. Nevertheless, scintillation is significant in event of satellite-ground communication pathway, that consist of the occurrence of atmospheric gasses, and boundary close to height above sea level around 20 km contained by the humid atmosphere [8]. The received electric field of the amplitude and phase from the scintillation discrepancies were transformed. In genuine detail, tropospheric scintillation power is a phenomenon which can be affected by tropospheric environments, while resulting variability in scintillation intensity takes an important influence on the information of the scintillation development [9]. Similarly, scintillation is known to demonstrate strong relationship with major meteorology factors like pressure, temperature and relative humidity. Scintillation intensity link budget design normally increase under frequency above 10 GHz, reduced elevation angle and low receiving antenna which are important for low fade margin systems [5]. Although, tropospheric scintillation occurs under during rainy and non-rainy conditions, however, signal fade cause by rain is of less interest to signal fade cause by clear-sky for purpose of little availability of satellite system design. Nigeria been a tropical climate is close to the equator and therefore has high temperature and an increase in relative humidity, whereas, most equipment shipped into the country from European countries that are temperate climate. Also, most tropospheric scintillation models are developed from Europe except Karasawa model that is developed from Japan (Asia) which is also a tropical climate like Nigeria (Africa). Therefore, because of the huge disparity in climate of Nigeria and Europe it is necessary to analyse and compare the scintillation intensity measures in Ota, Southwest, Nigeria, and already established prediction models. 2. METHODS AND DATA ANALYSIS The scintillation data is collected from Astra 2E/2F/2G satellite of 12.245 GHz on Latitude, Longitude and Elevation angle Lat: 6.7 oN, Long: 3.23 oE, Elev. Angle: 59.9o respectively at a sample proportion of 1 second at the Covenant University, Ota. The two year observed data for this research is between January 2015 and December 2016. The rainy days were parted from non-rainy days for this study by means of spectrum analyser and Davis automatic weather stations at rain rate 0 mm/h measured for non-rainy events, however, rain rate directly above 0 mm/h were deducted from the equivalent days and time data within the period of surveillance. A periodic average data were utilised as position data signal level and were minus from everyday observed established data signal level in way to acquire the tropospheric scintillation on every single one minutes for each non-rainy day. Subsequently, pass through a filter process result in data comprises of fade (negative) and enhancement (positive) tropospheric scintillation intensity that is below or above the average level. Furthermore, the measured tropospheric scintillation data at Ota were associated with more or less present scintillation calculation models that predict the variance of signal log-amplitude are: [10, 11, 12, 13] models. Hence, the performance assessment of individual scintillation model were verified founded on the significant percentage error (%) as: http://www.iaeme.com/IJMET/index.asp 128 editor@iaeme.com Investigation and Evaluation of Scintillation Prediction Models at Ota (1) Error ( ) = Table 1: Percentage Error of the Models % OF TIME 0.01 0.1 1 10 ITU-R FADE KASARAWA OTUNG 55.78 22.37 -2.98 -33.29 28.03 0.57 -20.26 -51.33 190.93 45.80 -25.89 -56.62 VAN DE KAMP -39.13 -54.71 -66.61 -78.53 ENHANCEMENT KASARAWA OTUNG 6.93 -10.21 -24.19 -44.93 71.49 1.61 -51.41 -98.28 VAN DE KAMP -31.75 -50.26 -64.61 -77.54 3. RESULT AND DISCUSSION Statistical comparison between enhancement (positive) and fade (negative) of tropospheric scintillation prediction models is shown in Table 1. It can be detected that Karasawa model provided the least error for fade around 0.57 % at 0.1 % and 28.03 % at 0.01 % percentage of time followed by ITU-R model around 22.37 % at 0.1 % percentage of time respectively. Similar was witnessed for enhancement at 0.01 % percentage of time trailed by Van de kamp model. Still, on fade scintillation at 1 % and 10 % of time ITU-R is noticed to have lowest percentage error. Figure 1 revealed the calculation of the measured data in Ota and numerous models estimation for both fade and enhancement, in order to comprehend the limits of individually predicted model and the progression of validity in Ota region. For negative tropospheric scintillation amplitude, Karasawa model (0.1 %) and ITU-R model (1 %) shows a precise near agreement by means of the observed measured data values in Ota practically for entire percentage of time predicted. Otung model followed marginally and deviate from other models at 0.01 % while Van de Kamp model differ from the rest model could be credited to the tropospheric scintillation observation occurrence of rainfall and heavy clouds. Though, scintillation enhancement signal amplitude likewise demonstrates close link amid observed data and predicted Karasawa model at entire level of proportion of time (most particularly at 0.1 %). This nearness could be for the reason that the model been established for the period of non-rainy by means of robust impact of water vapour acquire from surface humidity and temperature. No account for ITU-R model in positive scintillation (signal enhancement) due to the model been designed only to produce result for negative scintillation (signal fade). Figure 2 and 3 shows monthly variation of standard deviation of the tropospheric scintillation intensity of ground measurement and that of the existing prediction models. High scintillation intensity was observed February and March for both Ota (0.081 dB, 0.085 dB) and ITU-R (0.087 dB, 0.088 dB) respectively in figure 2, while others models show a weak intensity during the same period of the months. Increase in temperature and humidity may be attributed for this high scintillation for the period of the month. Actually, the measured temperature of Ota is at 28 oC and that of humidity is at 85.8 % which is the highest that year. Also in figure 3, Ota follows ITU-R closely with high scintillation intensity between April and May of about 0.086 dB. This is closely followed by Karasawa model while Otung and Van de Kamp models are weak and are therefore distance from other models because this models are generated from temperate region. ITU-R indicate high scintillation during rainy season because of its dependence on refractivity (Nwet) which normally occur between http://www.iaeme.com/IJMET/index.asp 129 editor@iaeme.com S. A. Akinwumi, T. V. Omotosho, M. R. Usikalu, M. E. Emetere, O. O. Adewoyin, T. A. Adagunodo, O. O. Ometan and O. M. Adewusi March to October every year. However, scintillation intensity is expected to be stronger during dry term period compare to wet term period of the year as revealed in the figures. FADE 1 0.7 ITU-R KASARAWA OTUNG VAN DE KAMP OTA 0.8 0.6 0.4 scintillation amplitude (dB) scintillation amplitude (dB) 1.2 ENHANCEMENT KASARAWA OTUNG VAN DE KAMP 0.6 0.5 0.4 0.3 0.2 0.2 0.1 0 0.01 0.1 1 10 0 Percentage of time (%) 0.01 0.1 1 10 Percentage of time (%) Figure. 1: Comparison of Ota data with Four existing models for fade and enhancement Scintillation Intensity (dB) 2015 0.13 0.11 0.09 0.07 0.05 0.03 0.01 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Months ITU-R KASARAWA OTUNG VAN DE KAMP OTA Figure.2: Comparison of monthly variability of Standard Deviation of Scintillation Intensity between Ota and prediction models in 2015 http://www.iaeme.com/IJMET/index.asp 130 editor@iaeme.com Investigation and Evaluation of Scintillation Prediction Models at Ota 2016 Scintillation Intensity (dB) 0.12 0.1 0.08 0.06 0.04 0.02 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Months ITU-R KASARAWA OTUNG VAN DE KAMP OTA Figure. 3: Comparison of monthly variability of Standard Deviation of Scintillation Intensity between Ota and prediction models in 2016. 4. CONCLUSION Assessment of four (4) predicted non-rainy scintillation models that is: Karasawa, ITU-R, Van de kamp and Otung models have been offered in this work. This predicted models were likened with the measured data acquired at 12.245 GHz from Astra 2E/2F/2G satellite beacon positioned at Covenant University in Ota. The measurement from Ota established that Karasawa model provided the top prediction for scintillation intensity for Ota and its environs. Also, scintillation intensity is noticed to be high during non-rainy season in comparison to rainy season months. ACKNOWLEDGEMENT The authors would like to appreciate Covenant University for full sponsorship of this research. REFERENCES [1] [2] [3] [4] S. A. Akinwumi, T. V. Omotosho, M. R. Usikalu, M. O. Adewusi, and O. O. Ometan, 2016. Atmospheric gases attenuation in West Africa. 2016 IEEE Radio and Antenna Days of the Indian Ocean, RADIO 2016; Hotel Le Recif Saint-Gilles Les Bains; Reunion. O. O. Afolabi, T. A. Adagunodo, T. T. 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