Determination of Radio Frequency Attenuation Signals of Ajilete FM (92.1MHz) and Compared with Existing Friis Formula, along Gambari-Oyo Road, Nigeria

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slide 1:

International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 12
Determination of Radio Frequency Attenuation Signals of Ajilete
FM 92.1MHz and Compared with Existing Friis Formula
along Gambari-Oyo Road Nigeria
Oyeleke O
1
. Olatinwo M.O
2
. and Sanni M
3
.
Physics Electronics Science Technology Department Federal Polytechnic Offa Kwara State Nigeria.
Abstract — This work measured experimentally and calculated theoretically using the existing Friis Fomula the Attenuation of
92.1 MHz Ajilete FM Signals along GambariLat 8
o
29
1
N Long 4
o
29
1
– Oyo-RoadLat 7
o
50
1
N Long 3
o
56
1
E Oyo State
Nigeria. The two results were compared. The experimental Measurement campaign was achieved by using an appropriate design
dipole antenna well matched to 810 GSP Analyser to determine the attenuation. The calculated results correlated very well
with the measurements Correlation Coefficient Value R
2
1. But they are not accurate when compared with the measurements
Chi- square values equal zero for received power measured attenuation. The inaccuracies of the results for the existing
formula with the measurements may be due to hills valleys trees and bends along the links. Hence the accuracy of the model
used can only be effectively confirmed in areas free of the obstacles mentioned above. By applying LEAST SQUARE fit method to
the experimental measured data the analytical models Px 0.0154x
2
-1.3575x-38.7620 and Ax 0132x
2
-1.2464x-104.8487
in the form of polynomial of degree two were obtained respectively for received power and measured attenuation. The
analytical model obtained is therefore recommended for use in an area characterised with bends valleys hills and trees since
the model has taken into consideration all these factors. In addition repeater stations should be installed for effective
transmission and for wider coverage in forested and valley areas. Moreover transmitter of higher value like ten kilowatts should
be employed for long distance transmission.
Keywords — Attenuation Dipole transmitter model polynomial Friis Fomula.
I. INTRODUCTION
Attenuation is the reduction in power density of electromagnetic waves as it propagates through space. This term is
commonly used in wireless communication and signal propagation. Attenuations may be due to many effects such as free
space loss refraction diffraction reflection aperture-medium coupling loss and absorption. Attenuation is also influenced
by terrain contours environments urban or rural vegetation and foliage propagation medium the distance between the
transmitter and the receiver and height and location of antenna Rhodes 2001. The causes of attenuation are enumerated
further.
However the reflected waves may reduce or increase attenuation. Often it is possible to communicate beyond the normal
LOS distance by exploiting the reflection from a tall building nearby mountain or water tower. If the top portion of a
structure or hill can be seen readily by both transmitting and receiving antennas it may be possible to achieve practical
communication by directing both antennas towards the point of maximum reflection. If the reflecting object is very large in
term s of a wavelength the path loss including the reflection can be very low. If a structure or hill exists adjacent to an LOS
path reflected energy may either add to or subtract from the energy arriving from the direct path. If the reflected energy
arrives at the receiving antenna with the same amplitude strength as the direct signal but has the opposite phase both
sandals will cancel and communication will be impossible.
However if the same conditions exist but both signals arrive in phase they will add and double the signal strength. These
two conditions represent destructive and constructive combinations of the reflected and direct waves. Reflection from the
ground at the common midpoint between the receiving and transmitting antenna may also arrive as constructive or
destructive manner. Generally in the VHF 7 UHF range the reflected wave is out of phase destructive with respect to the
direct wave at vertical angles less than a few degrees above the horizon. Meanwhile since the ground is not a perfect
conductor the amplitude of the reflected wave seldom approaches that of the direct wave. Thus even though the two arrive
out of phase complete cancellation does not occur. Some improvement may result from using vertical polarization rather
than horizontal polarization Rhode 2001
Several models have been obtained by different researchers for predicting signal attenuations of radio signal by various
attenuating factors. Some of these models do agree with the experimental measured values. This is evident in Sarat et al.
2004 as the model used could not be used to determine the rain attenuation of Hassan town in Indian and another model

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International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 13
was necessary for the town. Barwick et al. 2004 measured the attenuation of radio frequency through the situ-ice at scout-
Amuden station. The measured power was compared with power expected in the absence of attenuation using Frii equation
shown below
Pr/Pt GtGrλ
2
/16π
2
d
2
L 1
Where
P
r
the power received
P
t
the power input to the transmitter
G
t
the gain of the transmitter
G
r
the gain of the receiver
D the distance from the transmitter to receiver
λ the broadcast wavelength
L the known system loss faction
The experimental results showed that attenuation length decreases as temperature decreases and it also confirmed that the
attenuation length at radio frequencies is approximately larger than the attenuation length at optical frequencies Barwick al.
2004
The choice of the instrument used to measure the strength of radio signal among others is the type of the factor causing the
attenuation. Barrel et al 2011 used a Horn Antenna due to the high reflectivity at the ice and sea surface at Moore
Embayment South of Minna Bluff to measure the in-situ average electric attenuation length for radio frequency signals
broadcasted vertically the Rose-Ice Shelf Antarctica. After comparing the confirmed and the returned pulse he ascribed the
loss to be attenuation. He used the formula below to find the attenuation length of 75-1250 to be between 500 to 300m. In
the cause of determining the best condition for radio communication Shoewu and Edoko 2009 concluded that fog weather
is better for radio communication compare to rain weather. The measured the radio frequency signals of Nigeria
telecommunication at 7.2Ghz between Lagos Latitude 6
o
26
1
N longitude 3
o
27
1
E and distance of forty-eight kilometres
from Epe Latitude 6
o
32
1
Longitude 3
o
52
1
E.
The inaccuracy of these model is further confirmed Al-Basheir 2004 when he measured radio attenuation signal at 2.1
GHz through a date palm trees in Abu Dhabi in Saudi Arabia. The measured results was were compared with existing model
namely Exponential decay Model and maximum attenuation ModelEDM the model gives a poor fitting and which
suggests that ITU-R model need to be re-visited.
Regression analysis can also be used to determine attenuation as Okumbor et al. 2014 used the method with Mat lab
programme to characterise signal attenuation using pathloss exponent in South-South part of Nigeria to ascertain the rate of
signal attenuation during dry season.
Cloud attenuation due to cloud liquid water content has been obtained from the radiosonde measurements using Salonel
Model at a tropical location. The linear relationship was obtained between LWC and attenuation over the frequency range
10-100GHz give an estimate of cloud contribution to signal attenuation if cloud water content is known Bijoy et al. 2014.
II. METHODOLOGY
The following procedures were taken in order to determine the attenuation values measured of 92.1 radio frequency signals
along Ogbomosho/Gambari- oyo links
The attenuation was calculated using the Sanjaya and Jingsu formula of 2004 expressed as
AdB 10log
10
P
r
/P
t
Sanjaya and Jingsu 2004 2
where:
A- The attenuation in decibel
P
r-
power received by a receiver at a particular distance
P
t
- power transmitted from the station
For Ajilete FM the transmission power is 2500W and the operating frequency is 92.1MHz.

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International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 14
The Friis formula was used to calculate the power received which were expressed as below
P
r
dBm P
t
+ G
t
dB +G
r
dB- FSLdB-A
t
dB-A
r
dB 3
Sanjaya and Jingsu 2004
Where
P
r
power received
P
t
power transmitted
G
t
Transmitting antenna gain
G
r
receiving antenna gain
FSL free space loss path loss
A
t
transmission line loss between transmitter and transmitting antenna
A
r
transmission line loss between receiver and receiving antenna
Where
FSL dB 32.4 + 20logd 4
Where f is measured in MHz and d in km
Substituting for FSL in equation 3 using equation 4
P
r
dB P
t
dBm+G
t
dB+G
r
dB-32.4+20logf+20logd where A
t
dBA
r
dB are negligible or equal zero.
P
r
dB P
t
dB+G
t
dB+G
r
dB -32.4- 20logf-20logd 5
Where 20 log d varies with distance
For the power received to be calculated the power transmitted needs to be converted to dBm with the formula stated below
Power transmitted P
t
in milliwat 10
dB/10
Sanjaya and Jingsu 2004 6
dBm 10logPmw 7
dBm 10log2500000
63.979dBm
Where 20logf39.28dB
From equation 3
PrdBm 63.979 +9+1.5- 32.4-39.285-20log d
Where 20logd varies with distance
PrdBm 2.794-20logd 8
Equation 8 was used to calculate the power received at regular interval of 2km and the values are recorded in table 1
Recall from equation 2
AdB 10log
10
Pr/Pt
Substitute for Pr in equation 2 using equation 8
A 10log
10
2.794-20logd/2500 since P
t
2500W 9
Equation 9 was used for attenuation calculation and the values obtained are shown in table 2
III. EXPERIMENTAL MEASURED VALUE OF ATTENUATION
To measure the attenuation the half wave dipole was used because it is very useful as a mobile antenna and the car body can
be used as conducting plane. The antenna was used to pick the being transmitted from 92.1MHz broadcasting station. The

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International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 15
antenna was connected to the analyser to determine the attenuation of the signal as the distance from the transmitting station
increases. Lead accumulator cell was used to power the analyser to prevent interference while the earpiece was used to
monitor the audio signals transmitted.
To measure the attenuation a designed and constructed dipole antenna was needed and to determine the length the following
parameters were taken into consideration the wavelength λ the speed of light in vacuum c and frequency f are related by
Cf λ where c is the speed of light in vacuum f is the frequency and λ is the wavelength. Since the radio station in concern
is operating at frequency of 92.1MHz then the wavelength of the signal is
λ 3x10
8
/92.1x10
6
3.2572 m 10
The length of the antenna constructed is λ /40.814m
The antenna constructed was attached to analyser and it was used to take measurement of power received in dBm from 92.1
MHz at regular interval of 2km.
The readings taken were in dBm shown in table 1. It was converted to milliwatt using equation 6 P
r
10
dBm/10
and then to
watt. The attenuation of the measured received power was determined using equation 2 expressed below as
AdB 10log
10
P
r
/P
t
.
IV. RESULTS AND DISCUSSION
The various readings taken are as shown in the tables below
TABLE 1
VARIATION OF DISTANCE WITH POWER RECEIVED AND POWER CALCULATED
Distance
KM
Power ReceivedW Power CalculatedW
2.0 1x10
-5
4.758x10
-4
4.0 1.3183x10
-7
1.189x10
-4
6.0 1.2023x10
-7
5.286x10
-5
8.0 3.1623x10
-10
2.978x10
-5
10.0 1.0x 10
-9
1.903x10
-5
12.0 2.5119x10
-10
1.321x10-5
14.0 1.0233x10
-9
9.707x10
-6
16.0 1x10
-9
7.432x10
-6
18.0 6.3096x10
-10
5.872x10
-6
20.0 6.3096x10
-10
4.757x10
-6
22.0 6.3096x10
-10
3.937x10
-6
24.0 6-3096x10
-10
3.304x10
-6
26.0 6.3096x10
-10
2.815x10-6
28.0 3.9811x10
-10
2.427x10
-6
30.0 3.9811x10
-10
2.114x10
-6
32.0 2.5119x10
-10
1.858x10
-6
34.0 2.5119x10
-10
1.646x10
-6
36.0 1.4791x10
-10
1.468x10
-6
38.0 1.4791x10
-10
1.318x10
-6
40.0 1.4791x10
-10
1.189x10
-6
42.0 1.4791x10
-10
1.09x10
-6
44.0 2.5119x10
-10
9.829x10
-7
46.0 2.5119x10
-10
8.993x10
-7
48.0 1.5849x10
-7
8.259x10
-7
50.0 1.5849x10
-7
7.610x10
-7
52.0 1x10
-10
7.037x10
-7
54.0 1x10
-10
6.25x10
-7
56.0 1.4791x10
-10
6.067x10
-7
58.0 8.5114x10
-10
5.656x10
-7
60.0 1x10
-10
5.286x10
-7
62.0 1.0233x10
-10
4.950x10
-7
64.0 1.0233x10
-10
4-645x10
-7

International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 17
FIGURE 2: GRAPH OF ATTENUATION MEASURED AND ATTENUATION CALCULATED AGAINST DISTANCE
TABLE 3
STANDARD DEVIATION CHI- SQUARE PEARSON CORRELATION COMPARING POWER MEASURED AND
POWER CALCULATED
mean Std. Deviation N Df chi-square Asymp. Sig
Peareson Correlation
significant
Power Measured
dBm
-62.7781 10.73895 32 13 14.375a 0.348 1
Power Calculated
dBm
-25.3627 7.4334 32 31 .000b 1.666 0.881
TABLE 4
STANDARD DEVIATION CHI- SQUARE PEARSON CORRELATION AND STANDARD ERROR COMPARING
MEASURED ATTENUATION AND CALCULATED ATTENUATION
Mean Std. Deviation N Df Chi-Square Asymp. Sig
Peareson Correlation
significant
Power Measured
dBm
-62.7781 10.73895 32 13 14.375a 0.348 1
Power Calculated
dBm
-25.3627 7.4334 32 31 .000b 1.666 0.881
V. COMPARISON OF CALCULATED POWER USING FRIIS FORMULA AND MEASURED POWER RECIED
RESULTS
There was a sharp deviation between calculated power received results and measured power received result when chi square
test and standard deviation were calculated and the graph was plotted in which all these may be due to some factors not
considered in the formula like hills valleys and forested areas. However there is correlation between the two power because
they are function of distance- as the distance increase from the transmitting station the signal power continue to decrease
Using the method of least square fit the analytical model was obtained from the graph of the received powerexperimental
measured data in the form of polynomial equation of degree two
Px p
1
x
n
+ p
2
x
n-1
+ ----+p
n
x+p
n+1
Px 0.0154x
2
-1.3575x-38.7620
VI. COMPARISON OF CALCULATED AND EXPERIMENTAL VALUE OF ATTENUATION PLOTTED AGAINST
DISTANCE
The attenuation against distance for the experimental values plotted is not a smooth curve in comparison with the
experimental value. Also there were deviations when chi square test standard deviation and Pearson correlation coefficient

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International Journal of Engineering Research Science IJOER ISSN: 2395-6992 Vol-4 Issue-2 February- 2018
Page | 18
was calculated the unsmooth curve and the deviation may be due to hills valleys trees and bends along the along the road.
The standard mean square error of calculated attenuation was very high when compared with measured attenuation result.
The variation in the measured results and the calculated results which could be due to the above mentioned factor has
revealed that the accuracy of friis model is subject to the availability of obstacles. This implies that the model would not be
suitable for use
In an area that is characterised with hills valley trees and bends. Hence the obtained model which takes into consideration
the presence of the obstaches will always give a better result in experimental determination of attenuation.
The model obtained by Barrela et al 2011 was quiet difference from the model obtained in this work. This is
understandable because the charatrics feature of that area was high reflectivity which is complexly deferent from the
condition surrounding this research work.
Using the method of least square fit the analytical model was obtained from the graph of attenuation measured experimental
measured data in the form of polynomial of degree two
Px p
1
x
n
+p2x
n-1
+----+ p
n
x+p
n+1
Ax 0132x
2
-1.2464x-104.8487
Comparison of calculated and experimental values of attenuation plotted against distance
VII. CONCLUSION AND RECOMMENDATION
7.1 Conclusion
The measured results were compared with the calculated results using existing Friiis formula. The existing formula
correlated very well with the measurement R
2
1. But the existing model is not accurate when compared with the
measurements chi-square gives value of zero. The inaccuracy of the existing formula may be due to hill valleys trees and
bends along the road. The obtained analytical modelsAx 0132x
2
-1.2464x-104.8487 and Px 0.0154x
2
-1.3575x-
38.7620 obtained for both power measured and attenuation measured are more reliable having taken into consideration the
factors such as hill bends valleys forest and trees which have limited the accuracy of the friis model.
7.2 Recommendations
To obtain reliable results of signal attenuation measurement in an area characterised with valleys hills bends and forest the
models obtained in this work is recommended. Hence the Friis Model needs to be reviewed. A repeater station should be
installed for effective transmission and for wider coverage in forested and valley areas. Moreover transmitter of higher value
like ten kilowatts should be employed for long distance transmission.
REFERENCES
1 Al- Basheir M.S. Shubair R.M. and Shariff S.M.2006. Measurement and Analysis for Signal Attenuation through Date Palm
Trees at 2.1 GHz Frequency. Sudan Engineering Society Journal 5245 pp. 17-22
2 Barwick S. Benson D. Gorha P. and Saltzberg. 2004. South Polar in SITU Radio Frequency Attenuation. Journal of Glaciology
32180 pp. 1-27
3 Barrilla T. Barwick S. and Saltzberg D. 2011. Rose Ice ShelfAntarctica in SITU Radio Frequency Attenuation. Journal of
Glaciology 52201 pp. 61-66
4 Bijoy K.M. and Debnath 2014. Attenuation of Signal at a Tropical Location with Radiosonde Data due to Cloud. International
Journal of Smart Home 81 pp. 15-22
5 Okumbor N. Anthony and Okonkwo Obikwelu Raphael2014. Characterization of Signal Attenuation using Pathloss Exponent in
South-South Nigeria. International Journal of Emerging Trends Technology in Computer Science IJETTCS 33 pp.100-104
6 Oyetunji S. A. and Alowolodu O. D. 2013. Determination of Propagation Path Loss and Contour Map for Adaba FM Radio
Station in Akure N igeria. International Journal of Science and Technology 2 9 pp. 661-668
7 Sanjaya G. and Jinghsu Z. 2004. Attenuation of Microwaves Signal and its Impacts on Communication System. Department of
Engineering College of Engineering University of North Texas pp 1-10.
8 Sarat k.k. Vijaya B.R.S. and Rao D.N. 2008. Prediction of KU Band Rain Attenuation Using Data and Simulation for Hassan
India. International Journal of Computer and Network Security. 84. pp. 10-15
9 Shoewu O and Edeko F.O. 2005. Microwave Signal Attenuation at GHz in Rain and Harmattan Weather. American Journal of
Scientific and Industrial Research 23 pp.332-345.

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