Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria by Michael U

Global Journal of Researches in Engineering: D Aerospace Science Volume 17 Issue 2 Version 1.0 Year 2017 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN:2249-4596 Print ISSN:0975-5861

Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria By Michael U. Onuu & Emem M. Usanga University of Uyo Abstract- Path loss prediction for some Global System of Mobile Communication (GSM) networks for Akwa Ibom State in the Federal Republic of Nigeria was undertaken in this study in order to obtain a suitable path loss model for path loss prediction for the State. Received Signal Strength (RSS) and path loss were obtained from MTN and GLO base stations (networks) located in Uyo, Eket, Ikot-Ekpene, Onna, Etinan and Oruk-Anam which are some major towns in Akwa Ibom State. Path loss plots from theoretical models and experimental data against Basic Transceiver System (BTS), mobile device distance, gave positive linear relationships resulting in the proposed path loss model for Akwa Ibom State. Comparative analysis of Mean Square Error (MSE) obtained showed Hata model to be the most reliable and suitable path loss prediction model for Akwa Ibom State. The MSE value for each town was 5.9dB, 4.09dB, 5.93dB and 4.03dB for Uyo, Eket, Onna and Etinan, respectively. It was found that Egli model with MSE value of 5.97dB is suitable for path loss prediction in Ikot-Ekpene due to its irregular terrain. Keywords: path loss, global system of mobile communication (GSM), base transceiver station (BTS), received signal strength (RSS), networks and akwa ibom state. GJRE-D Classification: FOR Code: 290299

PathLossPredictionforSomeGSMNetworksforAkwaIbomStateNigeria

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Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria

Michael U. Onuu α & Emem M. Usanga σ

Abstract- Path loss prediction for some Global System of waves [19]. The use of GSM has bridged the Mobile Communication (GSM) networks for Akwa Ibom State communication gap between urban and rural dwellers. in the Federal Republic of Nigeria was undertaken in this study Since the inception of commercial operation of GSM in order to obtain a suitable path loss model for path loss globally in 1991 and in Nigeria in 2001, the demand for prediction for the State. Received Signal Strength (RSS) and good delivery of voice and data services by subscribers path loss were obtained from MTN and GLO base stations 201 (networks) located in Uyo, Eket, Ikot-Ekpene, Onna, Etinan is high.

and Oruk-Anam which are some major towns in Akwa Ibom It has been observed that even with the Year

operation of four telecommunication giants and other State. Path loss plots from theoretical models and experimental data against Basic Transceiver System (BTS), communication industries in Nigeria, there is still an 15 mobile device distance, gave positive linear relationships outcry by subscribers on poor quality network. This is resulting in the proposed path loss model for Akwa Ibom due to the fact that GSM faces the problem of reduction State. Comparative analysis of Mean Square Error (MSE) in power density (path loss) in electromagnetic wave as obtained showed Hata model to be the most reliable and it propagates between the BTS and mobile device. suitable path loss prediction model for Akwa Ibom State. The A particular BTS has a limit to which it can cover MSE value for each town was 5.9dB, 4.09dB, 5.93dB and 4.03dB for Uyo, Eket, Onna and Etinan, respectively. It was for effective communication; thus locating a ue II Version I ue II Version found that Egli model with MSE value of 5.97dB is suitable for communication mast and BTS must be done such that s path loss prediction in Ikot-Ekpene due to its irregular terrain. the number is minimized through proper link design and Results also showed that none of the models being path loss prediction. Poor network coverage brings considered gave acceptable MSE value for Oruk-Anam. In this about frequent drop calls, poor quality of service, poor case, the proposed path loss prediction model for Akwa Ibom inter -connectivity, echoes and general congestion [12]. State should be used for Oruk-Anam. The results of this This is due to the fact that signal value and investigation therefore lend credence to the fact that terrain signal level for voice and data service for a network and infrastructural development affect not only path loss, but Volume XVII Is depend on the power density of an electromagnetic also the suitability of a given path loss model for a particular environment. wave as it propagates through the space from the () Keywords: path loss, global system of mobile source to the mobile device. communication (GSM), base transceiver station (BTS), The gradual loss in power density of an received signal strength (RSS), networks and akwa ibom electromagnetic wave as it propagates from the source state. to the receiver is a problem to network providers. For cellular network to effectively cover a terrain or I. Introduction environment, accurate prediction of the coverage of the radio frequency signal is highly needed. Wave a) Overview propagation models are essential and very important ince the advent of telecommunication, there have tools in determining the propagation characteristics for a been researches on how to improve and enhance Researches in Engineering particular environment [12]. communication between people at various S Path loss prediction is a necessary tool for GSM locations. This resulted in Global System for Mobile network design, location of BTS and coverage area for Communication (GSM) which is a wireless form of such a network. Path loss is due to several effects such of ournal communication that propagates information (voice and as free space path loss, refraction, diffraction, reflection, data) in the form of an electromagnetic (EM) wave. absorption, coupling and cable loss. Path loss depends obal J

It is a fact that cellular phones have Gl on several factors which are; type of propagation, revolutionized personal communications for millions of environment, distance between the transmitter and people around the globe. Like any mobile radio, a receiver, height and location of antennas [1]. From the cellular phone transmits and receives electromagnetic foregoing, it means that the area to which a particular

BTS can cover is not fixed but depends on the nature of Author α: Department of Physics/Geology/Geophysics, Federal the environment, terrain and the level of infrastructural University, Ndufu-Alike, Ikwo, Nigeria. development of such a location. In urban areas with Author σ: Department of Physics, University of Uyo, Uyo, Nigeria. dense population, high rise buildings and structures, e-mails: [email protected], [email protected]

reflection and absorption of radio energy by buildings is urban environments. After comparing the empirical high, thus loss in power density will be high. models such as Hata, costs-231 Hata, International According to Mawjoud [6], networking Telecommunication Union - Radio (ITU-R), Ericson and planning is vital in the prediction of path loss and hence Stanford University Interim (SUI) with the experimental the coverage area, frequency assignment and measured path loss for urban areas in Mosul city, the interference which are the main concerns in mobile result showed that at 900MHz frequency, the best fit network planning. The available empirical formulae model for urban and sub-urban is Hata and Ericson cannot be generalized to different environments (urban, models and for 1800MHz frequency, the best fit model sub-urban, rural). In general, suitability of these models for industrial and sub-urban areas is the Costa-Hata differ for different environment. model. This shows that every environment has its Several propagation models have been distinctive characteristic factors and features that affect formulated for prediction of path loss, but due to the propagation of wave differently. This, thus, precludes difference in terrain and level of development of a the generalization of a particular model for different particular environment, appropriate model for a environment. Various works [10,11] also showed that a 201 particular environment differs. This study is aimed at path loss model cannot be generalized for different obtaining a propagation model that is suitable, reliable environment. Year and most accurate for path loss prediction in an Also Isabona and Konyeha [5] in their study on

16 environment and terrain like Akwa Ibom State in the urban area path loss propagation prediction and Federal Republic of Nigeria. optimization using Hata model at 800MHz showed how Okumura Hata model is chosen and optimized for urban II. Review Of Previous Works outdoor coverage in the Code Division Multiple Access

Path loss is the gradual reduction in power (CDMA) system operating in 800MHz UHF frequency density of an electromagnetic wave as it propagates band in South South Nigeria. They compared measured through the space from a source. Electromagnetic path loss with theoretical path loss obtained from Hata, SUI, Lee and Egli models. In their result, Hata model

sue II Versionsue I wave propagates through space from one region to another even when there is no matter in the intervening was the nearest in agreement with the measured values. region. Electromagnetic wave, when traveling through Based on these, they developed an optimized Hata an unguided medium, undergoes different kinds of model for the prediction of path loss experienced by XVII Is propagation effects such as reflection, diffraction, free CDMA 2000 signal in 800MHz band. space loss, absorption, aperture medium, coupling loss a) Reasons and causes of path loss and scattering. These propagation effects are the

Volume The reduction in power density (path loss) of a causes of reduction in power density (path loss). Path signal as it propagates from a source is caused by

() loss is as a result of received signal becoming weaker various factors which includes free space loss, due to increasing distance between the base station diffraction, multipath fading, buildings and vegetation, and the transceiver system. This occurs even when terrain and atmosphere. there are no obstacles between the transmitting antenna and the receiving antenna. Radio wave propagation b) Theoretical path loss models through a city is greatly affected depending on whether Theoretical models were derived based on the

there is line- of- sight (LOS) between transmitting and physical laws of wave propagation [10]. The theoretical receiving antennae or not. This is because propagation path loss prediction models are divided into two basic characteristics of the radio wave, such as path loss, types, namely; free space path loss model and plane fading and attenuation do not only depend on the earth propagation model. Researches in Engineering distance and frequency, but also on the scatter angle i. Free space propagation model

that depends on what is causing the obstruction to the In free space, the wave is not reflected or

nal of nal propagated wave [13]. absorbed. Ideal propagation implies equal radiation in

our A number of researchers have worked on path all direction from the radiating source and propagates to loss prediction which is of vital importance in GSM an infinite distance with no degradation. The free space

obal J network design, planning, location of BTS, coverage path loss model is used to predict received signal

Gl area, frequency assignment and interference for strength when the transmitter and receiver have a clear effective cellular networks aimed at achieving effective unobstructed line-of- sight, LOS, path between them signal values and levels between a transceiver and a [10]. In satellite communication, microwave in LOS radio mobile device. links typically undergo free propagation. According to Mawjoud [6] in his work on path loss [2,8,10], the power flux is given by propagation model prediction for GSM network planning studied the outdoor path loss behavior in Mosul city in P P = t 2.1 Iraq to predict a suitable propagation model at the d 4πd 2 frequencies of 900MHz and 1800MHz in urban and sub-

©2017 Global Journals Inc. (US) Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria where P is known as transmitted power ( mW 2 )/ and t The actual power received by the antenna is the power at a distance from the antenna. The Pd d depends on the aperture of the receiving antenna A0 , effective power of an isotropic antenna is given by the wave length of the received signal λ and the power 2 λ flux density at the receiving antenna Pd . Path loss is A = 2.2 e π given by the equation 4 and the received power by

λ2 Pr = Pd × PA te ×= 2.3 ()4πd 2

L =Power transmitte (Pd ) − power received (P ) 2.4 P t r

Substituting equation 2.3 into 2.4 gives plane earth loss increases far more rapidly than the free 201 space loss and it is independent of carrier frequency.

Year In plane earth model [14,18],

L = 20log (4π ) + 20log (d) − 20log (λ) 2.5 P 10 10 10 hh 22 17 = rt 2.7 0.3 L p 4 Also substituting λ (in km) = in MHz)( and d f rationalizing the equation produces the generic free where d is the distance (in metres) between the space path loss formula as given below: transmitter and receiver, h is the height (in metres) of t the transmitter antenna and is the height (in metres) += + 2.6 hr LP (dB) 32.5 20log10 (d) 20log10 f )( I ue II Version of the receiver antenna. s where f is the carrier frequency in MHz, d is the T-R In practice, a correction factor a is added to distance in km. equation 2.7 to yield

ii. The plane earth model hah 22 L = rt 2.8 According to [14,18], path loss experience is p 4 d worse in terrestrial environment than in free space. The Volume XVII Is most significant difference between terrestrial The correction factor depends on the a environment and free space is the presence of ground frequency of the carrier. Converting equation 2.8 to () (and ground reflection) in a terrestrial environment. The decibel gives.

L =10log )( + 20 ha )log( + 20log(h ) − 40 og(d)l 2.9 p t r The plane earth loss is rarely an accurate model within the range of 150 to 1920 MHz, but is extrapolated of real-world propagation when taken in isolation. It only to 3000 MHz. For Okumura model, the prediction area holds for long distance and for cases where the is divided into terrain categories; open areas, suburban amplitude and phase of the reflected wave is very close area and urban area [15]. Nadir and Ahmad showed

to the idealized in case a equals 1. that the signal strength decreases at much greater rate Researches in Engineering with distance than that predicted by free space model c) Empirical Models [7]. Empirical models, also known as stochastic Okumura developed a set of curves giving the

models, are models obtained from experimental of ournal median attenuation relation to free space ( ), in an observation. There are of various types and their urban area over a quasi-smooth terrain with a base 𝑚𝑚𝑚𝑚 suitability differs with respect to terrain. In this work, obal J station effective antenna height of 200m𝐴𝐴 and a Okumura model, Hata model, Cost-231 model and Egli hb )( Gl model will be discuss. mobile antenna height hm )( of 3m. The curves are i. Okumura Model plotted as a function of frequency in the range of According to [10], the Okumura’s model is an 100MHz to 1920MHz and as a function of distance from empirical model based on extensive drive test the base station in the range 1km to 100km. measurements made in Japan at several frequencies The empirical path loss formula of Okumura is expressed as [10,15]

L50 dB F += mu GdfAL hb hG m )()(),()( −−− GAREA 2.10

where L (dB) is the medium value of the path, L is The value of A ( ,df ) and G are 50 F mu AREA the free space path loss as given in equation (2.6), obtained from Okumura’s empirical plots shown in Amu is the median attenuation relation to free space, figure 1. Okumura derived empirical formula for hG b )(

hG b )( is the base station antenna height gain factor, and hG m )( as follows:

G(hm ) is the mobile antenna height gain factor, GAREA is the gain or correction factor due to the type of environment.

G(hb ) = 20log10 ()hb 200 : 30m < hb < 1000m 2.11a

G hm )( =10log10 ()hm 3 m < 3: mh 2.11b

G hm )( = 20log10 ()hm 3 3: m m ≤≤ 10mh 2.11c 201

Table 2.1: Range of validity for Okumura model Year PL = PL freespace Aexc cb −−+ HH cm 2.12

Parameter Symbol Range 18 where PL free space is the free space path loss, Aexc is Carrier frequency F 150 to 1920 MHz the excess path loss (as a function of distance and Base station antenna height h 30 to 1000m b frequency) for a base station height, h , 200m and Mobile antenna height h 1 to 10m b m mobile station height, h , 3m. Distance D 1km to 100km m The more common form is a curve fitting of ii. Hata Model Okumura’s original result. In that implementation, the

The Hata model is an empirical formulation of path loss is written as [17] sue II Versionsue I the graphical path loss data provided by Okumura PL A B )log( −+= Cd 2.13 model (Hata, 1980). It is valid over roughly the same range of frequencies 150MHz to 1500MHz. This where and are factors that depend on XVII Is , BA C empirical formula simplifies the calculation of path loss because it is closed form formula and it is not based on frequency and antenna height according to the following empirical curves for different parameters. Two forms of equations: Volume the Okumura-Hata model are available [20]. In the first

() form, the path loss (in dB) is written as

A=69.55 + 26.16log( f c ) −13.82log(hb ) − ha m )( 2.14a

B −= log55.69.44 h )( 2.14b b where f is given in MHz and d in km, ha )( is a correction factor for mobile antenna height. c m

The function ha m )( and C depend on the environment for small and medium-size cities. = −− − Researches in Engineering ha m ( c )(hf m 56.17.0)(log1.1)( log( fc 0) .8)  2.14c C = 0  nal of nal For metropolitan areas or la rge cities our  29.8 (log h 2 − 1.1))54.1( ffor ≤ 200MHz  obal J  m c ha )( =   Gl m 2 2.14d 3. (log(2 11.75hm )) − 4.97 for f c ≥ 400MHz  C =0 

For suburban environment The function ha m )( in suburban and rural area 2 is the same as urban (small and medium-size cities) = []fC /log(2 28) − 5 4. 2.14e c areas. For rural area The Hata model will approximate the Okumura model for distance > km. Hence, it is a good 2 d 1 C = 4.78log( f c ) −18.33log( f c ) − 40.98 2.14f model for first generation cellular system, but it does not

©2017 Global Journals Inc. (US) Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria model propagation well in current cellular system with iii. COST-231 Model smaller cell size and higher frequencies. The table below The COST-231 model sometimes called the shows the validity range for Okumura-Hata model. Hata model PCS extension is an enhanced version of Table 2.2: Range of validity for the Okumura-Hata model the Hata model that includes 1800-1900MHz [15]. COST-231 model is for propagation in the PCS band. Parameters Symbol Range According to Nkordeh, COST-231 model is Carrier frequency 150 … 1500 MHz f c limited to cases where base station antenna is placed

Effective base station h 30 … 2000m higher than the surrounding building. COST-231 model antenna height b is given by [9,15,16]: Effective mobile station 1 … 10m hm antenna height LP = A+ B log10 (d) +C 2.15 Distance D 1…20km where

A = 46 3. + 33 9. log f )( −13.82 log (h ) − ha )( 2.16a 10 10 b m 201 B = 44.9 − 6.55log10 (hb ) 2.16b Year

 ,0 mediumfor city and suburban areas with moderatetree density C =  2.16c 19  ,3 for metropoli tan centres

ha m = f )log(1.1)( −13.82log10 hb a hm )()( [44 −+− .69. 55log]10 hb )( log10 ( ) + Cd 2.16d

Thus

2.17 L p = 46.3 + 33.9log( f ) −13.82log 10 (hb ) − a(hm ) +[44 .9 − 6.55log10 (hb )log10 (d) + C] ue II Version I ue II Version s Table 2.3 Validity Range for COST-231 Model where is the gain of the base antenna and is the Gb Gm

Parameters Symbol Range gain of the mobile antenna, hb is the height of the base Carrier frequency 1800MHz < f < f c antenna, h is the height of the mobile antenna and d c 2000 MHz m is the propagation distance and

Effective base station 30m

Distance D 1000m > d >  

40 () 200m β =   2.19  f  iv. Egli Model where f is the frequency in MHz combing equation Egli model is an irregular terrain model for radio frequency propagation [10,15]. Egli model provides the 2.18 and 2.19, Egli model is given by median path loss due to terrain loss. It predicts the total 2 2  hh   40  path loss for point-to-point link (link-of-sight = mb   L50 Gb Gm  2    transmission). Typically, it is suitable for cellular  d   f  communication scenarios where one antenna is fixed and another is mobile. Egli model is expressed as [15] Researches in Engineering The gain for mobile station, Gm and gain for 2 base station, Gb are zero in decimal unit, so the path  hh mb  L = G G β 2.18 loss in this case can be simplified by 50 b m  2  of ournal  d 

obal J

L = 40log d)( − 20log h )( − 20log (h ) −10log β )( 2.20 Gl 50 10 10 b 10 m 10

III. Cell, BTS And Mobile Device located within that range can connect reliably is the

transceiver (Figure 2.1). The size of a cell is not fixed, it Global system for mobile communication (GSM) depends on several factors such as line-of-sight, is made up of a BTS and a mobile device enclosed reflection and absorption of radio frequency by within a cell. obstacles and vegetation, height of the antenna, In GSM, a cell is the geographical area covered transmitters rate power, the required uplink/down link by radio frequency from BTS which a mobile device data rate of the subscribers device and the terrain.

Sharma and Singh showed that these cells joined A NET monitor software installed in a Samsung together to provide radio coverage over a large galaxy phone was used to obtain the received signal geographical area [16]. Path loss determines the cell strength from a fixed BTS at selected locations while range. For GSM, there are three cell ranges. Table 2.4. GPS was used to measure the BTS – mobile device Hamad-ameen from his research showed that the distance while a Personal Computer (PC) was used to accuracy of cell planning depends on several factors save the collected data. and accuracy of propagation model is one of them [3]. This study was conducted in December, 2015 in selected cities of Akwa Ibom State at a temperature of

27oC. The Local Government Areas in which the investigation was carried out were Uyo, Eket, Ikot- Ekpene, Onna, Etinan and Oruk-Anam (Table 3.1). b) Description of the study area Akwa Ibom State lies between latitudes 4.32o o o o 201 and 5.33 N and longitudes 7.35 and 8.25 E, the State is in the South-South geopolitical zone of Nigeria,

Year bounded by Rivers State on the West, Cross River State

on the East, Abia State on the north and Gulf of Guinea. 20 The State is in Niger Delta and one of the 36 states in the Federal Republic of Nigeria with a total land mass of 7,249 square kilometers. About 13% of the 960km of Nigeria’s Atlantic Ocean runs through Akwa Ibom State. Akwa Ibom State falls within the tropical zone of Nigeria with a dominant vegetation of green foliage of sue II Versionsue I trees and shrubs. Most parts of the state are coastal Fig. 2.1: cell areas with Atlantic coastlines that stretch 129km from Table 2.4: Cell Range Oron in the east to Ikot Abasi in the west. XVII Is Cell Cell Radius c) Receiver Signal Strength (RSS) Large cells 1km ≥ r ≥ 30km In telecommunications, Received Signal Strength is the power present in a received radio signal Volume Small cells 1km to 30km Micro cells 200m to 300m and it is express in decibel (dB).

() Below is a range of signal strength and its effect Base Transceiver Station (BTS) in mobile on quality of service. communications holds the radio transceiver that defines

a cell and co-ordinate the radio-link protocols with the Table 3.1: Signal Strength on GSM mobile device. The BTS is the networking component of

a mobile communications system from which all signals Signal Strength Quality of are sent and received. Thus it facilitates wireless (dB)

communication between a device and network thereby 105 100 Bad/drop call

creating the cell in a cellular network. A BTS consist of

the following: antennas that relay radio message, − 99 𝑡𝑡𝑡𝑡 − 90 Getting bad/signal may break up

Researches in Engineering transceivers, duplexers and amplifiers while a mobile

device is a portable, wireless computing device that is − 89 𝑡𝑡𝑡𝑡 −80 Quality of service should not have problem

small enough to be used while held in the hand; a hand- nal of nal − 𝑡𝑡𝑡𝑡 − held. These include mobile phones, PDA, computers. 79 65 Quality of service is good our A mobile phone operates on a cellular network − 𝑡𝑡𝑡𝑡 − 65 Quality of service is excellent which is composed of cells. If a subscriber (user) is obal J 𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑡𝑡𝑡𝑡 −

Gl located outside the cell belonging to the cellular network IV. Results And Discussion provider the user subscribed to, such a user cannot place or receive calls in that location. The empirical path loss result was evaluated a) Experimental Design using four different path loss models, namely, free space model, Hata model, COST -231 model and Egli The methods employed in this study include physical site survey, collection of data, GPS model. The experimental results were subjected to measurement and analysis (graphs and regression). A regression analysis to obtain path loss model for each detailed field study exercise for collection of data was of the locations and path loss model for the entire study carried out in selected cities of Akwa Ibom State using a area. The Mean Square Error (MSE) was used to pick an mobile phone. empirical path loss model suitable for Akwa Ibom State.

Table 3.1 Cities and their characteristics

City Classification Characteristics

Uyo Urban (coastal/hinterland) Level terrain, presence of industries and institutions, heavy road traffic, large number of cluster high – rise building and telecommunication companies. Etinan Urban (hinterland) Moderate road traffic, sparsely distributed buildings, few trees, hill and telecommunication companies

Eket Urban (hinterland) Heavy road traffic, oil exploration companies, institutions, large number of cluster high – rise building, level terrain and telecommunication companies. Onna Suburban(coastal/hinterland) Very high road traffic, tall trees, sparsely distributed building and telecommunication companies Ikot-Ekpene Urban (hinterland) Heavy road traffic sparsely distributed high – rise building few

trees, hills 201 Oruk-Anam Urban (hinterland) Very high road traffic, thick vegetation with tall trees

and telecommunication companies Year

Ibom State. The minimum MSE Value for good Table 4.3: Measurement for Eket 21 signal propagation is 6dB. Network Distance (km) RSS (dB) Path loss (dB) a) Empirical path loss result The result from the four empirical path loss MTN 1.0 -78 125 model used are as shown in table 4.1. A frequency (f) of 2.0 -81 128 900MHz, Base Transceiver height of 45m and mobile receiver height ( ) of 1.5m was used in the evaluation. 3.0 -87 134 ue II Version I ue II Version The result is as shown in table 4.1. 4.0 -91 138 s 𝑚𝑚 ℎ 5.0 -97 146 Table 4.1: Empirical result for different path loss models GLO 1.0 -81 128 Distance Free Cost- 231 Hata (dB) Egli (dB) 2.0 -89 136 (km) space (dB) (dB) 3.0 -95 142 Volume XVII Is 1.0 91.58 123.97 123.59 110.46 4.0 -101 148

5.0 -107 154

2.0 97.61 133.95 133.84 122.50 () 3.0 101.13 139.79 139.84 129.35 4.0 103.63 143.65 144.10 134.54 Table 4.4: Measurement for Ikot-Ekpene 5.0 105.56 146.86 146.86 138.42 Network Distance (km) RSS (dB) Path loss (dB) V. Experimental Result MTN 1.0 -69 116 The collected measurement for MTN and GLO 2.0 -74 121 bass stations for the selected cities are shown below. 3.0 -79 126 Researches in Engineering Table 4.2: Measurement for Uyo 4.0 -85 132 5.0 -95 142 Network Distance RSS (dB) Path loss (km) (dB) GLO 1.0 -71 118 2.0 -79 126 of ournal MTN 1.0 -71 118 3.0 -83 130

2.0 -78 125 obal J 4.0 -97 144 3.0 -81 128 Gl 5.0 -103 150 4.0 -89 136

5.0 -97 144

GLO 1.0 -79 126 2.0 -85 132 3.0 -89 136

4.0 -95 142

5.0 -101 148

Table 4.5: Measurement for Onna Table 4.6: Measurement for Etinan

Distance Path loss Distance Path Network RSS (dB) Network RSS (dB) (km) (dB) (km) loss(dB) MTN 1.0 -70 117 MTN 1.0 -83 130 2.0 -75 122 2.0 -91 138 3.0 -83 130 3.0 -97 144 4.0 -89 136 4.0 -99 146 5.0 -97 144 5.0 -107 154 GLO 1.0 -79 126 GLO 1.0 -79 126 2.0 -83 130 2.0 -83 130 3.0 -87 134 3.0 -91 138 201 4.0 -93 140 4.0 -95 142 5.0 -101 148

Year 5.0 -97 144

22 Table 4.7: Measurement for Oruk Anam

Network Distance RSS (dB) Path loss (km) (dB)

MTN 1.0 -83 131 2.0 -92 140

sue II Versionsue I 3.0 -98 146

4.0 -107 155 5.0 -113 161

XVII Is GLO 1.0 -75 122 2.0 -81 128

Volume 3.0 -87 134

4.0 -91 138 () 5.0 -99 144

160 Free 140 space 120 (dB) Hata (dB) 100

) Early View Researches in Engineering B 80 d COS T-231 (dB)

ss ( 60 o nal of nal

h 40 Egli (dB) our at P 20 obal J MTN (dB) Gl 0 0 2 4 6

Distance (Km)

Figure 4.1: Graph of path loss against distance for Uyo L. G. A

160 Free 140 space 120 (dB) Hata 100 (dB)

loss dB 80 h COST- 60 Pat 231 40 20 Egli (dB) 0

0 2 4 6 201 Distan ce (Km)

Year

Figure 4.2: Graph of path loss against distance for Ikot Ekpene L. G. A 23 160 Free 140 space (dB) 120 Hata (dB)

100 I ue II Version s 80 COST- 231 (dB) 60

oss (dB) Egli (dB) 40 ath l P

20 Volume XVII Is MTN

0 () (dB) 0 2 4 6 Distance Km

Figure 4.3: Graph of path loss against distance for Eket L. G. A

160 Free 140 space

(dB) Researches in Engineering 120 Hata

) B

d 100 (dB) ( ss

80 of ournal

lo COST- h t 60 231 obal J Pa (dB) 40 Gl Egli 20 (dB)

0 MTN 0 2 4 6 (dB) Distance (Km)

Figure 4.4: Graph of path loss against distance for Onna L. G. A

180 Free 160 space (dB) 140 Hata

120 (dB) dB 100 COST- oss 80 231 th l

Pa 60 Egli 40 (dB)

20 MTN

(dB) 201 0 0 2 4 6 GLO Year Distance (Km) (dB)

Figure 4.5: Graph of path loss against distance for Etinan L. G. A

180 160 Free space 140 (dB) sue II Versionsue I 120 COST-

100 231 80 (dB)

XVII Is oss oss (dB) 60 Egli

h l (dB) 40 pat

Volume 20 MTN

0 () 0 2 4 6 Distance (Km)

Figure 4.6: Graph of path loss against distance for OrukAnam L. G. A

The equation of the line of regression of Y on X (4122) (1325) is given as = 10 30 10(110) (30)2

= + 3.1 𝛼𝛼𝑡𝑡 − = 5.85 where 𝑡𝑡 Researches in Engineering 𝑌𝑌 𝑎𝑎 𝑎𝑎 𝑋𝑋 𝑡𝑡 1335 (3 ) 𝛼𝛼 = 5.85 3.2 10 10 0= 2 ( )2 𝑡𝑡 nal of nal 𝑁𝑁 ∑ 𝑋𝑋𝑌𝑌−∑ 𝑋𝑋𝑌𝑌 𝛼𝛼 − 𝑎𝑎 𝑁𝑁 ∑ 𝑋𝑋 − ∑ 𝑋𝑋 = 11 5.95 our = 3.3 ∑ 𝑌𝑌 𝑋𝑋 𝛼𝛼 = 11 5. 95 + 5. 85 𝑡𝑡 obal J 𝑎𝑎 𝑁𝑁 − 𝑎𝑎 ∑ 𝑁𝑁 The proposed path loss model will be given by For Eket 𝐵𝐵𝐵𝐵 Gl 𝑃𝑃𝐿𝐿 𝑋𝑋 (4253) (1379) = + 0 + 3.4 = 10 30 10(110) (30)2 where 𝐿𝐿 𝐵𝐵𝐵𝐵 𝑃𝑃 𝑎𝑎 𝑎𝑎 𝑋𝑋 𝐶𝐶 𝑡𝑡 𝛼𝛼 = 5.8 − PL is the path loss is the BTS to mobile receiver distance 𝑡𝑡 1379 (3 ) 𝛼𝛼 = 5.8 C is correction factor for the environment Equations 3.2, 10 10 𝑋𝑋𝐵𝐵𝐵𝐵 𝑡𝑡 3.3 and 3.4 were used to find equation of line of 𝛼𝛼 = 12 0.5 − regression for the study areas. For Uyo L.G.A 𝛼𝛼 = 120. 5 + 5. 8 4.2 𝐵𝐵𝐵𝐵 ©2017 Global Journals Inc. (US) 𝑃𝑃𝐿𝐿 𝑋𝑋 Path Loss Prediction for Some GSM Networks for Akwa Ibom State, Nigeria

For Ikot-Ekpene The Mean Square Error (MSE) compares the measured data with the data obtained from each of the (4060) (1305) = 10 30 empirical models to determine the minimum MSE. The 10(110) (30)2 model that gives the least MSE and also not greater 𝑜𝑜 𝛼𝛼 = 7.25 − than 6dB, the minimum value of Mean Square Error for good signal propagation is suitable for prediction of 𝛼𝛼𝑜𝑜 1305 (3 ) path loss in the area in consideration. The Mean Square = 7.25 10 10 Error is expressed as 𝑜𝑜 𝛼𝛼 = 108.75− ( )2 = 108. 75 + 7. 25 4.3 = 𝛼𝛼 𝑚𝑚 𝑀𝑀 𝑃𝑃 − 𝑃𝑃 For Onna 𝐵𝐵𝐵𝐵 𝐵𝐵𝑀𝑀𝑀𝑀 � 𝑃𝑃𝑃𝑃 𝑋𝑋 where PM is the measured value,𝑁𝑁 PE is the empirical (4099) (1321) value and N is the values of data taken. = 10 30

10(110) (30)2 201 For Uyo 𝛼𝛼𝑜𝑜 − = 6.8 Year 𝑜𝑜 1321 11552.42 (30) 𝛼𝛼 = 6.8 ( ) = = 38.99

10 10 10 25 𝐵𝐵𝑀𝑀𝑀𝑀 𝑓𝑓𝑂𝑂𝑂𝑂𝑂𝑂 𝑠𝑠𝑠𝑠𝑎𝑎𝑠𝑠𝑂𝑂 � 𝛼𝛼 = 111.7− 347.74 𝛼𝛼 = 111. 7 + 6. 8 4.4 ( ) = = 5.9 10 For Etinan 𝐵𝐵𝐵𝐵 𝑃𝑃𝑃𝑃 𝑋𝑋 𝐵𝐵𝐵𝐵𝑀𝑀 𝐻𝐻𝑎𝑎𝑡𝑡𝑎𝑎 � 10(4280) (1392) = 10 30 533.59 10(110) (30)2 ( 231) = = 7.31 ue II Version I ue II Version 10 s 𝛼𝛼𝑜𝑜 − = 5.2 𝐵𝐵𝑀𝑀𝑀𝑀 𝑠𝑠𝑡𝑡𝑠𝑠𝑡𝑡 − �

𝑜𝑜 1392 (3 ) 𝛼𝛼 = 5.2 558.61 10 10 ( ) = = 7.47 𝑜𝑜 10 𝛼𝛼 = 123.6 − 𝐵𝐵𝑀𝑀𝑀𝑀 𝑀𝑀𝐸𝐸𝐸𝐸𝐸𝐸 � = 123.6 + 5.2

4.5 Volume XVII Is For Eket

𝐵𝐵𝐵𝐵 For Oruk-Anam𝑃𝑃 𝑃𝑃 𝑋𝑋 14525.18 () ( ) = = 38.11 10(4336) (1401) 10 = 30 10(110) (30)2 𝐵𝐵𝑀𝑀𝑀𝑀 𝑓𝑓𝑂𝑂𝑂𝑂𝑂𝑂 𝑠𝑠𝑠𝑠𝑎𝑎𝑠𝑠𝑂𝑂 � 𝑜𝑜 166.38 𝛼𝛼 = 6.65 − ( ) = = 4.09 10 √ 𝑜𝑜 1401 (3 ) 𝛼𝛼 = 6.65 𝐵𝐵𝐵𝐵𝑀𝑀 𝐻𝐻𝑎𝑎𝑡𝑡𝑎𝑎 10 10 196.95 𝑜𝑜 ( 231) = = 4.44 𝛼𝛼 = 120.15− 10

𝐵𝐵𝑀𝑀𝑀𝑀 𝑠𝑠𝑡𝑡𝑠𝑠𝑡𝑡 − � 𝛼𝛼 = 120. 15 + 6. 65 4.6 Researches in Engineering 1406.38 𝐵𝐵𝐵𝐵 ( ) = = 11.86 The proposed𝑃𝑃𝑃𝑃 path loss 𝑋𝑋model for Akwa Ibom 10 State is inducted as follows: 𝐵𝐵𝑀𝑀𝑀𝑀 𝑀𝑀𝐸𝐸𝐸𝐸𝐸𝐸 � ournal of ournal 60(25133) For Ikot-Ekpene (8124)

= 180 obal J 60(660) (180)2 96 98.72 ( ) = = 31.14 Gl 𝑜𝑜 𝛼𝛼 = 6.34 − 10 𝐵𝐵𝑀𝑀𝑀𝑀 𝑓𝑓𝑂𝑂𝑂𝑂𝑂𝑂 𝑠𝑠𝑠𝑠𝑎𝑎𝑠𝑠𝑂𝑂 � 𝑜𝑜 8124 (180) 𝛼𝛼 = 6.34 772.34 60 60 ( ) = = 8.79 10

𝛼𝛼 = 116.34− 𝐵𝐵𝑀𝑀𝑀𝑀 𝐻𝐻𝑎𝑎𝑡𝑡𝑎𝑎 � 857.11 ( 231) = = 9.26 𝛼𝛼 = 116. 38 + 6. 34 4.7 10

𝑃𝑃𝐿𝐿 𝑋𝑋𝐵𝐵𝐵𝐵 𝐵𝐵𝑀𝑀𝑀𝑀 𝑠𝑠𝑡𝑡𝑠𝑠𝑡𝑡 − �

to 4.7. Regression analysis carried out on the results of 356.54 ( ) = = 5.97 each location gives equation 4.1 to 4.6. Figure 4.1 to 10 4.6 show plots of path loss in decibel against distance in 𝑀𝑀𝑀𝑀𝑀𝑀 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 � For Onna kilometres for the six study area. The graph shows a

linear relationship between path loss and distance, 11135.98 increase in distance led to increase in path loss. ( ) = = 33.37 The MSE compares the measured data with the 10 data obtained from each of the empirical model to � 𝑀𝑀𝑀𝑀𝑀𝑀 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 determine the minimum MSE. The model that gives the

352.06 least MSE and also not greater than 6dB, the minimum ( ) = = 5.93 10 value of MSE for good signal propagation is suitable for 𝑀𝑀𝑀𝑀𝑀𝑀 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 � prediction of path loss in the area in consideration. From

446.66 the evaluation, MSE value obtained for Hata model (5. ( – 231) = = 6.68 9dB, 4.09dB, 5.93dB, 4.03dB) for Uyo, Eket, Onna and

201 10 Etinan LGA respectively falls within the acceptable 𝑀𝑀𝑀𝑀𝑀𝑀 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 � values of MSE for good signal propagation while Egli Year 518.74 ( ) = = 7.20 model (5.97) for Ikot-Ekpene is the acceptable value.

26 10 From the evaluation, the least MSE value for Oruk- 𝑐𝑐 𝑀𝑀𝑀𝑀𝑀𝑀 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 � Anam, Hata model (7.44) is above the minimum MSE For Etinan value of 6db for a good signal propagation.

15633.09 VII. onclusion ( ) = = 39.54 C 10 From the investigation, Hata model has the 𝐵𝐵𝑀𝑀𝑀𝑀 𝑓𝑓𝑂𝑂𝑂𝑂𝑂𝑂 𝑠𝑠𝑠𝑠𝑎𝑎𝑠𝑠𝑂𝑂 � minimum means square error (MSE) of 5.9dB, 4.09dB, 162.32 sue II Versionsue I 5.93dB and 4.03dB for Uyo, Eket, Onna and Etinan, ( ) = = 4.03 10 respectively. These values fall within the acceptable

𝑀𝑀𝑀𝑀𝑀𝑀 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 � value of minimum MSE of 6dB for a good signal propagation. Hata model is more reliable and suitable

XVII Is 174.2 ( 231) = = 4.17 for accurate path loss prediction in these areas while 10 Egli model with MSE value of 5.97db for Ikot -Ekpene is 𝑀𝑀𝑀𝑀𝑀𝑀 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 − � suitable for path loss prediction for Ikot-Ekpene. This Volume 1670.1 investigation also shows that the least MSE value of

( ) = = 12.92 () 10 7.44db for Oruk-Anam was obtained from Hata model 𝑀𝑀𝑀𝑀𝑀𝑀 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 � but it is greater than the minimum MSE of 6dB for a For Oruk-Anam good signed propagation. In these cases the proposed

model ( = 116.38 + 6.3 ) obtained from this study

16664.94 can be used Oruk-Anam. ( ) = = 40.82 𝐵𝐵𝐵𝐵 10 𝑃𝑃𝐿𝐿From this study, Hata𝑋𝑋 model gives a fairer result 𝑀𝑀𝑀𝑀𝑀𝑀 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 � for path loss prediction for Akwa Ibom State. The study 554.11 also shows that no generic model is suitable for ( 231) = = 7.44 10 generalized used since each model differs in their applicability over different terrain. For effective path loss

Researches in Engineering 𝑀𝑀𝑀𝑀𝑀𝑀 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 − � 566.64 prediction in Akwa Ibom State and network coverage ( ) = = 7.82 10 performance, the proposed path loss model in equation

nal of nal 𝑀𝑀𝑀𝑀𝑀𝑀 𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 � 4.7 obtained from the experimental results from the state our is reliable, suitable and more accurate. 2188.3 ( ) = = 14.79 10 obal J References Références Referencias

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Nigerian Journal of Technology, 30(3). 11. Ogbulezie, J. C., Onuu, M. U., Bassey, D. E. and () Etienam-Umoh, S. (2013). Site specific measurement and propagation models for GSM in Three cities in Northern Nigeria. American Journal of Scientific and Industrial Research, 4(2), 238-245. 12. Ogbulezie, J. C., Onuu, M. U., Ushie, J. O. and Ushie, B. E. (2013). Propagation models for GSM 900 and 1800 MNZ for Port Harcourt and Enugu, Nigeria. Network and Communication Technologies,

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