The global mobile communication is fast growing in industry. This paper recommends appropriate settings to evaluate the performance of wireless mobile system deploying third generation networks in an urban environment. To meet this aim, a case Study of Sulaimanyia city is considered for this study by establishing suitable radio channel models. The work presents a statistical channel model, where fixed and nomadic analysis services are considered in the simulated radio coverage scenario. The cartographic dataset had been collected, and Matlab Software was used for showing the analysis and simulation results. Statistical channel models are derived that combine standard parameters such as separation distance, operating frequency and terminal height with more advanced and innovative parameters such as distance dependent shadowing and LOS probability.
Third Generation Wireless Modeling in Urban Environment
1. International Journal of Electrical, Electronics and Computers (EEC Journal) [Vol-2, Issue-3, May-Jun 2017]
https://dx.doi.org/10.24001/eec.2.3.3 ISSN: 2456-2319
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Third Generation Wireless Modeling in Urban
Environment
Kusay F. Al-Tabatabaie
Computer Science Dep., Cihan University –Sulaimanyia Campus, Iraq
Abstract—The global mobile communication is fast
growing in industry. This paper recommends appropriate
settings to evaluate the performance of wireless mobile
system deploying third generation networks in an urban
environment. To meet this aim, a case Study of
Sulaimanyia city is considered for this study by
establishing suitable radio channel models. The work
presents a statistical channel model, where fixed and
nomadic analysis services are considered in the simulated
radio coverage scenario. The cartographic dataset had
been collected, and Matlab Software was used for
showing the analysis and simulation results. Statistical
channel models are derived that combine standard
parameters such as separation distance, operating
frequency and terminal height with more advanced and
innovative parameters such as distance dependent
shadowing and LOS probability.
Keywords— Mobile, 3G, Sulaimanyia City, propagation
Model, ICS telecom cartography.
I. INTRODUCTION
The rapid revolution of wireless technologies in the past
decade has led to the fast adoption of smart phones.
Consumers are expecting every device they have to be
connected to the network to record, transfer, view, or
monitor data [1]. Therefore, as wireless technologies are
evolving, so must radio planning methods. Many
researchers worked to progress cellular solutions such as
reducing transmit power, improving coverage, and
provide high capacity connectivity [2-5]. The need to
evaluate the performance of such systems in an urban
environment is required for proper study to set radio
channel model.
To determine the radio coverage is required to take into
account the network type (Fixed, nomadic, mobile…) and
target type (Major metropolitan areas or wireless
complement connection for rural areas). This call radio
signal path loss, which increases with increasing
frequency. The radio frequency (RF) power of radio
signals would be reduced when radio signals have
travelled over a considerable distance. Therefore, in most
cases, the systems with higher frequencies will not
operate reliably over the distances required for the
coverage areas with varied terrain characteristics [6]. For
clear line of sight (LOS) propagation, the range between
the transmitter and receiver is determined by the free
space path loss (PL) equation [7], can be derived from the
following expression (1)
d
PL
4
log20 10 dB (1)
where d and λ are the range and wavelength in meters,
respectively.
In Non-Line-of-Sight (NLOS) cases, the performance of
higher frequencies is worse with reliable distances
dropping even faster. Most paths are obstructed by
objects and buildings. When penetrating obstacles, radio
waves are decrease in amplitude. As the radio frequency
increases, the rate of attenuation increases. Fig. 1
illustrates the effect of higher frequencies having higher
attenuation on penetrating obstacles [8].
Fig.1: Higher frequencies have higher attenuation on
penetrating obstacles.
A radio beam can diffract when it hits the edge of an
object. The angle of diffraction is higher as the frequency
decreases. When a radio signal is reflected, some of the
RF power is absorbed by the obstacle, attenuating the
strength of the reflected signal. Fig. 2 show that higher
frequencies lose more signal strength on reflection [9].
Fig.2: Frequency dependence of signal strength on
reflection
2. International Journal of Electrical, Electronics and Computers (EEC Journal) [Vol-2, Issue-3, May-Jun 2017]
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Conversely, high frequency is required to provide
sufficient bandwidth. However, spectrum allocation
widths are normally proportional to the frequency of the
band and hence nominating the 3400-4200 MHz band for
IMT-Advanced would allow the spectrum users to operate
with more and wider channels [10]. The use of higher
available capacity can also support much higher data rates
than the lower spectrum. In addition, higher frequency
can reduce the financial cost of licensing. It is important
to notice that gain of antennas is a functional to the
frequency being received [11]. In free space propagation,
clear and unobstructed line-of-sight (LOS) path is
available and the first Fresnel zone is maintained between
base station and terminal. Free space path loss can be
obtained by using the logarithmic value of the ratio
between the receiving and transmitting power as
expressed in Equations 2, 3, 4 and 5. This simplified free
space path loss model for unity antenna gain is based on
[12]. Equations 3, 4 and 5 indicate that free space path
loss is frequency dependent and it increases with distance.
The increase of distance and frequency produce similar
effect on the path loss.
t
r
dB
P
P
PL 10log10 (2)
mHzdB dfPL 1010 log20log2056.147 (3)
KmMHzdB dfPL 1010 log20log2044.32 (4)
KmGHzdB dfPL 1010 log20log2044.92 (5)
Where f is frequency, d is distance; Pr and Pt are the
receiving and transmitting power in watts, respectively.
Fig. 3 shows simulation for free space path loss for the
frequencies 900 MHz, 2000 MHz, and 4000 MHz at
different transmitter - receiver distances.
Fig.3: Free space path loss at 900 MHz, 2000 MHz, and
4000 MHz
II. RADIO PROPAGATION MODEL
A radio propagation model is an empirical mathematical
formulation for the characterization of radio wave
propagation as a function of frequency, distance and other
characteristics. A single model is usually developed to
predict the behaviour of propagation for every similar link
under similar constraints. The essential aim of signal
propagation studies is to formalize how the signal can
propagate from one point to another. Only in such
situation can a typical model predict the path loss effect
on an area covered by a single or multi transmitter (s)
[13].
It is found that ITU-R P.452-14 [14] is the most suitable
propagation model for this study, because it can cover
from 0.7 MHz to 30 GHz frequency range. The
prediction of the line of sight LOS is a result of the signal
after being exposed to the path and clutter loss model
CEPT and ITU organizations have accepted a common
formula for wireless transmission assessment at a
microwave frequency level. This formula has
incorporated the clutter attenuation as well as
environmental effects, and is expressed as follows:
hGHzkm AfddL log20log2044.92)( (6)
Where d (km) is the distance between interferer and
victim FSS receiver, f is the carrier frequency in GHz and
Ah is loss due to protection from local clutter (i.e clutter
loss), and is given by:
33.0625.06tanh125.10
a
d
h
h
h
eA k
(7)
where dk (km) is the distance from nominal clutter point
to the antenna, h is the antenna height (m) above local
ground level and ha (m) is the nominal clutter height
above local ground level. In [14], clutter losses are
evaluated for different categories, such as trees, rural,
suburban, urban and dense urban. Increasing antenna
height up to the clutter height will result in a decrease in
clutter loss, as shown in Table 1 and Fig. 4.
Table.1: Nominal clutter heights and distances [14]
Clutter
Category
Clutter Height
ha (m)
Nominal
Distance dK (km)
Rural 4 0.1
Suburban 9 0.025
Urban 20 0.02
Dense urban 25 0.02
Where table 1 reveals that the value of nominal distance
is highest for rural and suburban areas, whereas for urban
3. International Journal of Electrical, Electronics and Computers (EEC Journal) [Vol-2, Issue-3, May-Jun 2017]
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and dense urban areas the separation distance decreases in
response to the clutter loss increment.
Fig.4: Clutter losses for rural, suburban, urban and
dense urban areas.
III. POINT-TO-MULTIPOINT (P-MP)
Similarly, a Point-to-Multipoint fixed service is one that
involves a base station and a number of remote stations as
shown in Fig. 5.
Fig.5: Point-to-Multipoint FWA Service.
In a P-MP service, the base station sends a broadcast to
the remote stations in the downstream direction and
receives transmissions from the remote stations in the
upstream direction. A sectored antenna [15, 16] is usually
employed within P-MP service as in LMDS and
Microwave Multipoint Distribution Service (MMDS)
services.
IV. BROADCASTING SERVICES
The broadcasting service consists of sound, video and
data broadcasting. Video broadcasting is a P-MP TV
transmission for public reception, typically from a fixed
emitter to fixed and portable receivers using the
horizontal frequency (line repetition frequency). The
channel bandwidth of the colour TV is 6 MHz in America
and Japan, 7-8 MHz in Europe. Digital television is
incompatible with analogue TV in terms of how the
broadcasted information is represented as a signal.
However, it must have RF spectrum compatibility. An
important factor in defining the digital standard is to
consider the channel bandwidth of existing analogue
standards (or smaller bandwidth). Countries currently
using Phase Alternation by Line (PAL) or Sequential
Colour with Memory (SECAM) with an 8 MHz UHF
bandwidth are likely to choose only a standard that can
handle such channels Digital Video Broadcasting–
Terrestrial (DVB-T). On the other hand, countries using
National Television System Committee (NTSC) or PAL
with 6 MHz bandwidth may choose any of the standards,
while maintaining the bandwidth compatibility [17].
V. SIMULATION RESULTS AND ANALYSIS
In order to influence the choice of the propagation model,
the urban radio planning had been performed for the
cartographic dataset. However, the most important thing
is the technology which applied to simulate the channel
model in this urban environment. This technology
depends on the technical characteristics and the type of
applied engineering methodology such as fixed-type,
mobile-type, using OFDM or not.
In this work, a wide range of wireless technologies for
urban areas were considered, a combination from both of
mature 3G and WLL technologies had been performed to
sketch the quality of service (QoS) as shown in fig. 6.
Fig.6: QoS to each sector in Sulaimanyia area
The overall (QoS) to each sector can be calculated
according to:
A service flow provisioning defined on a per
mobile unit basis.
The throughput available at each sector,
calculated according to the OFDMA permutation
4. International Journal of Electrical, Electronics and Computers (EEC Journal) [Vol-2, Issue-3, May-Jun 2017]
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and the number of data sub-carriers used, the
UL/DL duration ratio, the modulation…
A variation of the contention ratio according to
the hour of the day.
The indoor propagation loss due to building absorption
can be simulated by applying a diffusion coefficient per
building type. To activate set allocation, radio-planner
had been specify for each selected base station (BS), the
active sets each BS in prediction tool, ICS telecom tool
had been used as shown in fig. 7. where ICS Telecom is
able to model both Inter channel Interference (ICI) and
Inter Symbol Interference (ISI).
Fig.7: Coverage prediction for selected BS using ICS
telecom cartography.
High Resolution data provides all building outline and
heights. This type of simulation must be entirely
deterministic in order to represent the canyon effect. The
buildings here are physical obstacles to the standard
signal propagation in ICS Telecom.
Regarding the hand-over along a mobile path, If the radio
planner is more particularly interested into a mobile path,
a dedicated hand over analysis can be performed, in UL
or in DL. Display as shown in fig. 8.
Fig.8: Display of the FSBB hand-over of a mobile unit
anchored to active set 3
VI. CONCLUSION
The proposed channel propagation model had been
presented using using ICS telecom cartography, where
cartographic dataset type used to show streets, the
buildings locations and heights outlined. For coverage
calculations, the empirical or deterministic propagation
model had been chosen using High Resolution datasets.
This project novelty is to improves the accuracy of peer-
to-peer channel power prediction in urban environments
by using more advanced distance dependent shadowing,
LOS probability. And provides solution to the problem of
radio channel modelling in system level simulations that
incorporate multi-hop/ad-hoc and fixed relay network
elements in an urban environment in the 2-5 GHz range.
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