International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 Implementation of Cellular Propagation Models in Diverse Environments Deepak Katiyar#1 , Vikas Mittal*2 #1 M.Tech. Student, Dept. of ECE, Maharishi Markandeshwar University, Mullana, Ambala, Haryana, India. *2 Asst. Prof., Dept. of ECE, Maharishi Markandeshwar University, Mullana, Ambala, Haryana, India. Abstract— This paper presents the implementation and analysis of different propagation models in cellular communication system under different environmental conditions. The paper discusses the various factors which influence the propagation of wireless signal in free space thereby causing the degradation of signal quality. The propagation models implemented are: free space path loss, Okumura model, COST 231 Hata model, SUI, ECC-33models and Ericsson model. These models are simulated with respect to standard parameters for Cellular transmission. The results analysed were stated for each model in respective environmental locations. The results show that the multipath and Non-Line-Of-Sight scenarios in urban area, all models experiences higher propagation losses in urban area compare to suburban and rural areas. Keywords— Propagation models, cellular communication system, free space path loss, Okumura model, COST 231 Hata model, SUI, ECC-33models and Ericsson model. I. INTRODUCTION Modern wireless communication technology has revolutionized the field of telecommunication. Today, the wireless networks have far succeeded in complimenting the traditional communication networks in aspects of system capacity, network connectivity, signal strength and power usage [1]. Inspite of the reliability of wireless communication technology, implementation of mobile communication is burdened with certain propagation complications. Over the last decade, a number of wireless propagation models have emerged on the basis of different user requirement and environmental conditions like as geographical location factor, user density, vegetation density, network applicability, data rate, fading and other path losses etc [2]. The environmental factors greatly impact the propagation mechanisms of wireless signals through the free space, causing subsequent loss in signal power. Thus, the characteristic features of wireless communication networks are often evaluated on the basis of applied propagation model. The implementations of various cellular propagation models in communication networks for respective wireless services are geographically selective. Therefore, the environmental factors play an important role in estimation of signal strength, interference optimization, network design and estimation of number of users allocated per cell [3]. ISSN: 2231-5381 II. FACTORS AFFECTING SIGNAL PROPAGATION The parameters for the signal transmission should be selected in a manner so that it maximizes the quality of service for the user and minimizes the use of system resources. A number of algorithms are being employed or investigated to optimize the signal transmission process [4]. Traditional cellular networks are primarily focused on voice applications and consequently there are fewer worries associated with degradation of signal quality, poor data rate or poor signal strength. Traditional algorithms employ simple intuitive rules to compare the received signal strength from different points of connection and then decide the best algorithm suitable for transmission [5]. Degradation of the signal level, however, is a major point of consideration, and the mechanisms followed by traditional algorithms degrade the service provided by the network. Consequently, more complex algorithms are needed to be employed for the optimal propagation of signal in free space. To select an appropriate algorithm, a comparative performance evaluation of a variety of algorithms is required. However, the comparative performance evaluation of different propagation algorithms is an extremely challenging subject. Performance criteria for selecting the optimum propagation algorithm are affected by the type of network. The performance criteria for cellular phone networks such as GSM, UMTS and CDMA2000, rate adaptive wireless data networks such as WLAN and WPANs, and inter-technology heterogeneous networks are different [2]. For this purpose, the received signal strength (RSS) at base station is calculated to quantify the signal quality as well as calculate the path loss.The rate adaptive and heterogeneous data networks are focused on optimizing the delivered average throughput to the user. However, this average throughput is affected by different factors in a heterogeneous and in a homogeneous multi-rate network. Typical factors include free-space loss, refraction, diffraction, reflection, aperture-medium coupling loss, and absorption. The propagation of signal from wireless networks across heterogeneous space 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. Signal propagation can be affected by many factors, as mentioned in Table I. http://www.ijettjournal.org Page 1 International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 TABLE I FACTORS CAUSING THE PROPAGATION LOSS Factors (Propagation Loss) Free Space Loss Absorption Scattering Reflection Description Free space loss describes the loss that occurs as a signal travels through space with no other attenuation caused by outside influences. This occurs because the signal spreads out as the distance from the transmitter increases. Absorption is a loss that occurs if the signal passes through varying mediums or obstacles in which some of the transmitted signal is converted into another form of energy, usually thermal, and some of it continues to propagate. Any material or atmospheric condition that is non-transparent to electromagnetic signals will result in absorption of the transmitted signal. The conversion of energy occurs at the molecular level, resulting from the interaction of the energy of the radio wave and the material of medium or obstacle. Scattering is a condition that occurs when a radio wave encounters small disturbances of a medium, which alters the direction of signal. Scattering is difficult to predict because of the random nature of the medium or objects that causes it. Reflection occurs when a radio wave approaches the boundary of two mediums and redirects back into the original medium in a different direction, rather than permeating through into the new medium. Refraction Refraction occurs when a radio wave passes from one medium to another with different refractive indices resulting in a change of velocity within an electromagnetic wave that results in a change of direction. Diffraction Diffraction losses occur when there is an obstacle in the path of the radio wave transmission and the radio waves either bend around an object or spread as they pass through an opening. Diffraction can cause great levels of attenuation at high frequencies. However, at low frequencies, diffraction actually extends the range of the radio transmission. Polarization is used in an electromagnetic wave to describe the direction of the electric field vector. Fading is a radio wave variation in signal strength, caused by a change in the polarization of the transmitted radio wave. Fading can result from reflection, refraction, or absorption. It is a significant problem because antennas are designed to receive a radio wave in a certain polarization, and when the polarization of signal is changed, the receiving antenna is incapable of receiving the polarization changes. Polarization Fading Multipath Fading Multipath fading refers to the fading that occurs as a result of the multiple paths that a signal ends up taking between the transmitter and receiver. Because of the varying arrival times of the signals from the various paths, the signals may or may not be in phase with each other. If the radio waves are received in phase, they combine to form a stronger signal. If the radio waves are out of phase, a weaker signal is produced. Multipath fading is the primary concern in the urban environment. Terrain The terrain over which a signal propagates accounts for a great deal of the loss it experiences along its path. As expected, mountainous terrain can significantly degrade or completely block a signal, but the composition of the terrain can also cause attenuation, especially at low altitudes. Radio waves tend to travel better over more conductive mediums such as water, but encounter more attenuation travelling over areas of dirt or sand. Vegetation Just like the terrain, vegetation can impact the transmission of radio waves. Solid trees can cause significant attenuation, but even leaves can cause scattering of a signal. Buildings Buildings and other man-made structures can cause losses due to all of the above factors, and are by far the main source of attenuation in an urban environment. This study is designed to attempt the difficult task of accurately accounting for the losses caused by these structures. ISSN: 2231-5381 http://www.ijettjournal.org Page 2 International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 III. CELLULAR PROPAGATION MODELS A wireless communication terminal needs to connect to multiple points of connection and perhaps multiple networks as it moves from one location to another. The method of using different networks with the same terminal for inter-network mobile communications is often referred to as intertechnology, heterogeneous, or non-homogeneous networking. That’s why the system applications of a wireless network are dependent on propagation models that describe the attenuation of the transmitted signal as a function of the distance between network terminals. Propagation models are classified as deterministic, empirical and semi-empirical [6]. Deterministic models make use of the physical laws governing radio wave propagation mechanisms to predict transmission loss at a particular location. The models involve detailed and accurate description of all the objects in the propagating channel. Empirical model is based on statistical characterization of the received signal extensive measurements conducted with respect to several different parameters. It requires less computation effort unlike deterministic model that is site specific. A semi-empirical or semi-deterministic model combines the analytical formulation of physical phenomena with statistical fitting of variables by adjustment using experimental measurements. Hence, the choice of propagation model plays an important role in the performance of a cellular network. The standard propagation models are implemented in different environments like suburban area scattered with trees, houses and urban areas with large building and houses or village with close houses and tall trees. These propagation models are described below: where, PLOM : Median path loss [dB], Lf : Free space path loss [dB], Amn (f,d): Median attenuation relative to free space [dB], G(hte): Base station antenna height gain factor [dB], G(hre): Mobile station antenna height gain factor [dB], GAREA: Gain due to the type of environment [dB] and parameters, f: Frequency [MHz], hte: Transmitter antenna height [m], hre: Receiver antenna height [m] and d: Distance between transmitter and receiver antenna [km]. Figure I provides the values of Amn (f,d) and GAREA. Attenuation and gain terms in this model are given as: 20 log10 (hte/200) for 1000 > hre > 10m G(hte) = 10 log10 (hre/3) for hre ≤ 3m 20 log10 (hre/3) for 10m > hre > 3m where, G(hte): Base station antenna height gain factor [dB], hte: Transmitter antenna height and hre: Receiver antenna height. A. Free Space Path Loss Model (FS) Free space model defines the strength of the signal lost during propagation from transmitter to receiver. The free space path loss calculation is done using the following equation: PLFS = Gt – Gr + 32.44 + 20 log(d) + 20log(f) 2.1 where Gt and Gr are transmitted and received antenna gains in dB; d is T-R separation in Km and f is frequency in MHz [7]. B. Okumura Model The Okumura model is a well known classical empirical model to measure the radio signal strength in build up areas. The model was built by the collected data in Tokyo city in Japan. This model is perfect for using in the cities having dense and tall structure, like Tokyo. In this model, while dealing with areas, the urban area is sub-grouped as big cities and the medium city or normal built cities. Okumura model can predict path loss in urban, suburban and rural area up to 3 GHz and the median path loss model can be expressed as [8]: PLOM = Lf + Amn (f,d) – G(hte) – G(hre) – GAREA 2.2 FIGURE I: MEDIAN ATTENUATION AND AREA GAIN FACTOR [9] ISSN: 2231-5381 2.3 http://www.ijettjournal.org Page 3 International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 C. COST 231 Hata Model The Hata model was introduced as a mathematical expression to mitigate the best fit of the graphical data provided by the classical Okumura model [10]. Hata model is used for the frequency range of 150 MHz to 1500 MHz to predict the median path loss for the distance d from transmitter to receiver antenna up to 20 km, and transmitter antenna height is considered 30 m to 200 m and receiver antenna height is 1 m to 10 m. To predict the path loss in the frequency range 1500 MHz to 2000 MHz, the COST 231 Hata model was initiated as an extension of Hata model. It is used to calculate path loss in three different environments like urban, suburban and rural (flat). The basic path loss equation for this COST-231 Hata Model can be expressed as [11]: PLCOST = 46.3 + 33.9log10(f) – 13.82log10(hb) – ahm + (44.9 - 6.55log10(hb))log10(d) + cm 2.4 where d: Distance between transmitter and receiver antenna [km], f: Frequency [MHz], hb: Transmitter antenna height [m]. The parameter cm has different values for different environments like 0 dB for suburban and 3 dB for urban areas and the remaining parameter ahm is defined in urban areas as: ahm = 3.20 (log10 (11.75))2 – 4.70, for f > 400MHz where, the parameters are d: Distance between BS and receiving antenna [m], Xf: Correction for frequency above 2 GHz [MHz], Xh: Correction for receiving antenna height [m], S: Correction for shadowing [dB] and Y: Path loss exponent The random variables are taken through a statistical procedure as the path loss exponent Y and the weak fading standard deviation s is defined. The log normally distributed factor S, for shadow fading because of trees or other clutter on a propagations path and is between 8.2 dB and 10.6 dB [11]. The parameters A and path loss exponent Y are defined as [12]: where, the parameter hb is the base station antenna height in meters. This is between 10 m and 80 m. The constants a, b, and c depend upon the types of terrain, given in Table II. The value of parameter Y = 2 is for free space propagation in an urban area, 3 < Y < 5 for urban NLOS environment, and Y > 5 for indoor propagation [12]. TABLE II PARAMETER VALUES OF DIFFERENT TERRAIN FOR SUI MODEL Model Parameter a 2.5 The value for ahm in suburban and rural (flat) areas is given as: Terrain C 4.0 3.6 b (m ) 0.0075 0.0065 0.005 c (m) 12.6 17.1 20 The frequency correction factor Xf and the correction for receiver antenna height Xh for the model are expressed as: Stanford University Interim (SUI) Model X f = 6.0 log 10 (f/2000) The IEEE 802.16 Broadband Wireless Access working group proposed the standards for the frequency band below 11 GHz, containing the channel model developed by Stanford University, namely the SUI models. This prediction model came from the extension of Hata model with frequency larger than 1900 MHz. The correction parameters are allowed to extend this model up to 3.5 GHz band. In the USA, this model is defined for the Multipoint Microwave Distribution System (MMDS) for the frequency band from 2.5 GHz to 2.7 GHz [11]. The base station antenna height of SUI model can be used from 10 m to 80 m. Receiver antenna height is from 2 m to 10 m. The cell radius is from 0.1 km to 8 km [12]. The SUI model describes three types of terrain: A, B and C. Terrain A can be used for hilly areas with moderate or very dense vegetation. This terrain presents the highest path loss. Terrain B is characterized for the hilly terrains with rare vegetation, or flat terrains with moderate or heavy tree densities. This is the intermediate path loss scheme. Terrain C is suitable for flat terrains or rural with light vegetation, here path loss is minimum. The basic path loss expression of the SUI model with correction factors is presented as: PLSUI = A + 10ylog10 (d/d0) + Xf +Xh + s for d > d0 ISSN: 2231-5381 Terrain B 2.6 where, hr is the receiver antenna height in metres. D. Terrain A 4.6 -1 ahm = 1.11log10 (f-0.7)hr – ( 1.5log 10f – 0.8) 2.8 A = 20log 10 (4πd0/λ) and Y = a – bhb + (c/hb) 2.7 2.9 -10 log 10 ( hr / 2000) for terrain type A and B 2.10 X h= -20 log 10 ( hr / 2000) for terrain type C where, f is the operating frequency in MHz, and hr is the receiver antenna height in meter. For the above correction factors, this model is extensively used for the path loss prediction of all three types of terrain in rural, urban and suburban environments. E. Hata-Okumura extended model or ECC-33 Model One of the most extensively used empirical propagation models is the Hata-Okumura model [9], which is based on the Okumura model. This model is a well-established model for the Ultra High Frequency (UHF) band. Recently, through the ITU-R Recommendation P.529, the International Telecommunication Union (ITU) encouraged this model for further extension up to 3.5 GHz [13]. The original Okumura model does not provide any data greater than 3 GHz. Based on prior knowledge of Okumura model, an extrapolated method is applied to predict the model for higher frequency greater than 3 GHz. In this model path loss is given by [11]: http://www.ijettjournal.org Page 4 International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 PL HO = Afs + Abm - Gb - Gr 2.11 where Afs: Free space attenuation [dB], Abm: Basic median path loss [dB], Gb: Transmitter antenna height gain factor and Gr: Receiver antenna height gain factor. These factors can be separately described and given as: Afs = 9.24 + 20log10 (d) + 20 log10 (f) 2.12 Abm=20.41+9.83log10 (d)+7.894log10 (f)+9.56[log 10 (f)]2 2.13 G b = log10(hb/2000){13.958 + 5.8[log10(d)]2} TABLE IV SIMULATION PARAMETERS Parameters Values Base station transmitter power 43 dBm Mobile transmitter power 30 dBm Transmitter antenna height 30 m in urban and suburban 2.14 When dealing with gain for medium cities, the Gr will be expressed in [11]: 2.15 Gr = [42.57 + 13.7log10(f)][log10 (hr) – 0.585] For large city: 2.16 Gr = 0.759(hr) – 1.862 where, d: Distance between transmitter and receiver antenna [km], f: Frequency [GHz], hb: Transmitter antenna height [m] and hr: Receiver antenna height [m]. This model is the hierarchy of Okumura-Hata model. So the urban area is also subdivided into large city and medium sized city, as the model was formed in the Tokyo city having crowded and tallest buildings. F. IV. SIMULATION PARAMETERS 2.11 in the model are The simulation parameters applied presened in Table IV below: Ericsson Model This model is developed by Ericsson also stands on the modified Okumura-Hata model to allow room for changing in parameters according to the propagation environment. Path loss according to this model is given by [12]: and 20 m in rural area Receiver antenna height 6m Operating frequency 3.5 GHz Distance between Tx-Rx 5 km Building to building distance 50 m Average building height 15 m Street width 25 m Street orientation angle 300 in urban and 400 in suburban Correction for shadowing 8.2 dB in suburban and 10.6 dB in urban area V. RESULTS In this study 3 different environments i.e. urban, suburban and rural are taken. The height of receiver antenna is 6 m and transmitter antenna height is 30 m in urban and suburban and 20 m in rural area. The simulated results for different models in urban, suburban and rural environments are shown in the Figure II, III and IV respectively. 2.17 PLEM = a0 + a1.log10 (d) + a2 .log10(hb) + a3.log10(hb). log10(d) - 3.2(log1o(11.7hr)2) + g(f) and g(f) = 44.49log10(f) – 4.78(log10(f))2: 2.18 where parameters f: Frequency [MHz], hb: Transmission antenna height [m], hr: Receiver antenna height [m] and default values of these parameters (a0, a1, a2 and a3) for different terrain are given in Table III. TABLE IIII VALUES OF PARAMETERS FOR ERICSSON MODEL. a0 a1 a2 a3 Urban 36.2 30.2 12.0 0.1 Suburban 43.20 68.93 12.0 0.1 Rural 45.95 100.6 12.0 0.1 Environment ISSN: 2231-5381 FIGURE II: SIMULATED RESULTS IN URBAN ENVIRONMENT http://www.ijettjournal.org Page 5 International Journal of Engineering Trends and Technology (IJETT) – Volume 15 Number 1 – Sep 2014 get LOS signal, in that situation, the COST-Hata model showed the less propagation loss compare to SUI model and Ericsson model. Therefore, for the worst case scenario for deploying a coverage area, the maximum coverage can be served by using more transmission power, but it will increase the probability of interference with the adjacent area with the same frequency blocks. On the other hand, if the less propagation models are considered for deploying a cellular region, it may be inadequate to serve the whole coverage area. Some users may be out of signal in the operating cell especially during mobile condition. So, there needs to be a trade-off between transmission power and adjacent frequency blocks interference while choosing a propagation model for initial deployment. REFERENCES [1] FIGURE III: SIMULATED RESULTS IN SUBURBAN ENVIRONMENT [2] [3] [4] [5] [6] [7] [8] [9] [10] FIGURE IV: SIMULATED R ESULTS IN R URAL ENVIRONMENT [11] VI. CONCLUSION From the comparative analysis made in this paper, it is found that due to multipath and NLOS environment in urban area, all models experiences higher propagation losses compare to suburban and rural areas. From the results, it is observed that there is no single model that can be recommended for all environments. In urban area, the Ericsson model showed the lowest propagation loss as compared to other models. Alternatively, the ECC-33 model showed the heights propagation loss. In suburban area, the SUI model showed quite less propagation loss compared to other models. On the other hand, ECC-33 model showed highest propagation loss as showed in urban area. In rural area, if the area is flat enough with less vegetation, where the LOS signal probability is high, in that case, the LOS calculation may be considered. Alternatively, if there is less probability to ISSN: 2231-5381 [12] [13] C. 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