Journal of Engineering Path Loss Model Using Geographic

International Journal of Engineering and Technology Volume 3 No. 3, March, 2013

Path Loss Model Using Geographic Information System (GIS) Biebuma, J.J, Omijeh. B.O Department of Electrical/Electronic Engineering, University of Port Harcourt

ABSTRACT This paper presents Geographic Information System (GIS) as an invaluable tool in path loss modeling. It shows how GIS can reveal features through its visualization capabilities. A program was written in Visual Basic for Applications (VBA) to automatically compute the path loss using Cost 231 Hata Model, and display it spatially on an administrative map and satellite imagery (Land Use/Land Cover) using ArcMap 9.0 Application. The results gotten were tested to be consistent with results of previous study done in Southern Nigeria and it shows how the excellent visualization and spatial handling capabilities of GIS gives it an extra advantage as a path loss modeling tool. Thus, the integration of GIS into existing path loss analysis applications is recommended for fast, accurate and exciting results brought about by the ability to visualize the terrain and other great features. Keywords: Geographic Information Systems, Path Loss, Cost 231 Hata, Model

1. INTRODUCTION A Geographic Information System is a system of hardware, software and procedures to facilitate the management, manipulation, analysis, modeling, representation and display of geo-referenced data to solve complex problems regarding planning and management of resource. But GIS is much more than maps. A GIS can perform complicated analytical functions and then present the results visually as maps, tables or graphs, allowing decision-makers to virtually see the issues before them and then select the best course of action. There are several spatial applications in use such as ArcGIS, MapInfo etc. The most prominent of which is the ArcGIS developed by ESRI (Environmental System Research Institute), Redlands. ArcGIS is a suite of software product lines produced by ESRI. At the desktop GIS level, ArcGIS can include: ArcReader, which allows one to view and query maps created with the other Arc products; ArcView, which allows one to view spatial data, create maps, and perform basic spatial analysis; ArcEditor which includes all the functionality of ArcView, includes more advanced tools for manipulation of shapefiles and geodatabases; or ArcInfo the most advanced version of ArcGIS, which includes added capabilities for data manipulation, editing, and analysis. Path loss is a major component in the analysis and design of the link budget of a telecommunication system. It is the attenuation undergone by an electromagnetic wave in transit between a transmitter and a receiver in a communication system. Path loss may be due to many effects, such as free-space loss, refraction, diffraction,

reflection, aperture-medium coupling loss, and absorption. Path loss is also influenced by terrain contours, environment (urban or rural, vegetation and foliage), propagation medium (dry or moist air), the distance between the transmitter and the receiver, and the height and location of antennas. There are several path loss models, prominent of which are reviewed below.

2. LITERATURE REVIEWS The Okumura et al. method is based on empirical data collected in detailed propagation tests over various situations of an irregular terrain and environmental clutter[1]. The results are analyzed statistically and compiled into diagrams. The basic prediction of the median field strength is obtained for the quasi-smooth terrain in an urban area[2]. A correction factor for either an open area or a suburban area is also taken into account. Additional correction factors, such as for a rolling hilly terrain, an isolated mountain, mixed land-sea paths, street direction, general slope of the terrain etc., make the final prediction closer to the actual field strength values [3] . The Okumura model is formally expressed as: L = LFSL + AMU – HMG - HBG

(1)

where, L = Median path loss (dB). LFSL = Free Space Loss (dB). AM = Median attenuation (dB). HMG = Mobile station antenna height gain factor.

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013 HBG = Base station antenna height gain factor.

achieved. In addition, the prediction algorithm is simple and fast.

2.1 Lee Model

2.2 COST-231 Hata Model

Lee.W.C.Y proposed this model in 1982 [4]. In a very short time it became widely popular among researchers and system engineers mainly because the parameters of the model can be easily adjusted to the local environment by additional field calibration measurements (drive tests). By doing so, greater accuracy of the model can be

The Hata Model [5] is an empirical formulation of the graphical path loss information provided by Okumura. Hata presented the urban area propagation loss as the standard formula and supplied correction equations to the standard formula for application to other situations [6].

PL = 46.3 + 33.9 log10 (f) – 13.82log10 (hb) - ahm + (44.9 – 6.55log10 (hb)) log10 d + cm Where, f is the frequency in MHZ, d is the distance between the transmitting and the receiving antennas in km; hb is the transmitting antenna height above ground level in meters. The parameter cm is defined as 0 dB for suburban or open environments and 3 dB for urban environments. The parameter ahm is define for urban environments, ahm = 3.20 (log10 (11.75hr)) 2 – 4.97, for f > 400MHz

(3)

for suburban or rural (flat) environments, ahm = (1.1log10f – 0.7) hr – (1.56log10f – 0.8),

(4)

where, hr is the receiver antenna height above the ground level. Equally make a provision for rain attenuation that is the total path loss to be added to the rain attenuation.

3. DESIGN METHODOLOGY

(2)

In this design, the Cost 231-Hata Model was used[7]. Using Microsoft Access, a database to capture the parameters in the COST-231 Hata model and the geographic Coordinates of the transmitter and receiver stations was set up. A form to link to the database was created. The path loss was calculated using VBA code which was linked to a button in the form. The table was imported into ArcCatalog as a geodatabase and displayed as an ESRI shapefile on ArcMap. The points were joined and the calculated pathloss displayed. This was overlayed with administrative boundaries and satellite imagery (land use/ land cover). Results gotten were tested to be consistent with a previous research carried out [8][9][10].

3.1 Mathematical Model In carrying out Path loss analysis, COST-231 Hata Model equation was used to model the path loss using industry data from the region.

PL=46.3 + 33.9log10 (f) – 13.82log10 (hb) - ahm +(44.9 – 6.55log10 (hb))log10d + Cm Where, f is the frequency in MHZ, d is the distance between the transmitting and the receiving antennas in km; hb is the transmitting antenna height above ground level in meters. The parameter Cm is defined as 0 dB for suburban or open environments and 3 dB for urban environments. The parameter ahm is define for urban environments,

(5)

coordinates both for receiving and transmitting stations ii.

Create a table in a database with the declared variables as the fields

iii.

Create a form containing identical fields with the table created

iv.

Link the table with the form

v.

Input Cordinates and Station information

(7)

vi.

Set values for the terrain (Urban, Suburban and Rural)

where, hr is the receiver antenna height above the ground level.

vii.

Define the parameter ahm for different terrain conditions, that is: Urban - ahm = 3.20 (log10 (11.75hr)) 2 – 4.97 Surburban/Rural - ahm = (1.1log10f – 0.7) hr – (1.56log10f – 0.8)

viii.

Define value of Cm for the different terrain conditions:

ahm = 3.20 (log10 (11.75hr)) 2 – 4.97, for f > 400MHz

(6)

for suburban or rural (flat) environments, ahm = (1.1log10f – 0.7) hr – (1.56log10f – 0.8)

3.2 Algorithm i.

Declare all variables using the appropriate format/structure (PL, f, hr, hb, ahm, Cm and

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013 PL = 46.3 + 33.9 log10 (f) – 13.82log10 (hb) - ahm + (44.9 – 6.55log10 (hb)) log10 d + cm

Urban, Cm = 3, Suburban/Rural, Cm = 0 ix.

Input other Parameters (f, hr, hb and d)

x.

Compute Pathloss the Cost 231-Hata model showed below:

xi.

Output Computed value of Pathloss

Figure 1 shows the Flowchart for Path loss Analysis using Cost 231-Hata Model

Fig 1. Flowchart for Path loss Analysis using Cost 231-Hata Model

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013

Fig 2 Path loss calculation application interface Table 1 Pathloss results for Different stations Link Name, Latitude, Longitude

Antenn a

Antenna Height

MO DE

Tx Power

Gain

LOS

32 dBm

46.5 dBi

Cable type With Losses Distance

Fade Path loss

Margin

Rx Level

Odeama creek /Soku 04 33 39 N 007 00 00 E 04 39 29.40 N 006 36 35 E

Ughelli / Afiesere

22.6km 103m/ 118m

LOS

32 dBm

46.5 dBi

72m/68 m

31.84km

05 29 19 N 006 00 24 E 05 19 59 N 006 14 59 E Diebu creek / Nun River 05 03 36 N 006 27 17.60 E 04 53 23 N 006 22 22 E

LOS

32 dBm

46.5 dBi

LMR600 Coax at 110m 14.29 dB

LMR600 Coax at 78m 6.43 dB

112m/

LMR900 Coax at 120m

118m

11.50 dB

152.6 dB

12 dBm

-68.0 dBm

165 dB

13.7 dBm

-66.3 dBm

153.3d B

11.2 dBm

-68.8 dBm

25.4km

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013

Fig 3 Odeama creek /Soku displayed on land use on administrative boundaries.

Fig 4 Odeama creek/Soku stations displayed land cover showing the legend.

going to do real field survey, preliminary planning can be done based on this analysis.

4. RESULTS AND DISCUSSION Figure 2 shows a screen capture of the form view of the path loss calculation interface. The program was tested with a previous research done and the results were compared with the output of the application. Table 1 below summarizes the results obtained (Edeh, 2008) From this legend, it is clear that that Odeama creek and Soku (a built up area) are separated basically by Tall Mangrove forest. This alongside other attenuation factors explains the high value of path loss calculated, thus the received signal will be low if measures are not taken to improve signal quality. This makes better understanding than when it is merely described with words. Even before

Figure 4 above shows Odeama creek/Soku stations displayed on administrative boundaries and river layer. This is necessary for the planner to know the administrative delineations so he can plan towards complying with the respective state and local government statutory requirements. Figure 5 shows Ughelli/Afiesere stations and computed pathloss displayed on land use land cover. Using the legend in fig 3 it is clear that Ughelli and Afiesere are separated by heavy forests which include palm, rubber etc. This alongside other attenuation factors explains the high value of path loss calculated, thus the received signal

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013 will be low if measures are not taken to improve signal

Fig 5 Ughelli/Afiesere stations displayed on LULC

It is clear that Diebu Creek and Nun River are separated by mangrove and forests as seen in fig 6. This alongside other attenuation factors explains the high value of pathloss calculated, thus the received signal will be low if measures are not taken to improve signal quality.

5. CONCLUSION While classic path loss models alone can form the basis of correct analysis, it only relies on descriptions of terrain and other geographical parameters which are quite important. Thus, the planner in the office, who never went to the field, may not have a visual description of the terrain, distance between transmit and receiving stations and other geographical parameters. This paper addressed this problem using Geographic Information Systems, customized for this purpose. The visual and spatial handling capabilities brought an extra edge into the study of path loss analysis. Thus achieving the same result (faster) but with an extra advantage of allowing the planner see the terrain parameters from his desktop while making accurate decisions. Apart from this, certain other analysis (Proximity, Network and Overlay) can be used to further simplify the work of the telecommunications engineer.

REFERENCES [1] Okumura, Y. (1968). Field strength and it’s variability in VHF and UHF land-mobile radio-

quality.

Fig 6 Diebu creek/Nun River stations and Calculated pathloss displayed on land use land cover.

services. Review of the Electrical Communications Laboratory, vol. 16. [2] Baldassaro,P.M, Bostian.C.W, Carstensen.L.M, and Sweeney.D.G (2002): “Path Loss Predictions and Measurements over urban and rural terrain at frequencies between 900 MHz and 28 GHz.” Proc. IEEE AP-S2002 International Symposium, in press. [3] Neskovic .A(2000); Modern Approaches in Modeling of Mobile Radio Systems Propagation Environment; IEEE Communiation Surveys. [4] Lee, W. C. Y(1998): Mobile Communications Engineering: Theory and Applications, McGrawHill, 1998. [5] Hata, M. (1980); Empirical Formula for Propagation Loss in Land Mobile Radio Services; IEEE Trans. Vehicular Technology. [6] Sweeney, D (2003); Propagation Issues for Land Mobile Radio (LMR) in the 100 to 1000 MHz Region; Center for Wireless Telecommunications, Virgin [7] 231 Final Report, Digital Mobile Radio(1990): COST 231 View on the Evolution Towards 3rd Generation Systems, Commisiion of the European Communities and COST Telecommunications, Brussels, 1999. [8] Edeh, P.O (2008); Path Loss Model for Microwave radio link in Southern part of Nigeria; University of Port Harcourt

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International Journal of Engineering and Technology (IJET) – Volume 3 No. 3, March, 2013

[9] Prasad. M.V.S.N and A. Iqbal (1997): “Comparison of some path loss prediction methods with VHF&UHF measurements”, IEEE Transactions On Broadcasting, Vol. 43, No. 4, pp. 459-486, 1997.

[10] Rama.T, Rao, S. Vijaya Bhaskara Rao, M.V.S.N. Prasad, Mangal Sain, A. Iqbal, and D. R. Lakshmi(2000): “Mobile Radio Propagation Path Loss Studies at VHF/UHF Bands in Southern India”, IEEE Transactions On Broadcasting, Vol. 46, No. 2, pp. 158-164, 2000.

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