METTU UNIVERSITY

COLLEGE OF ENGINEERING AND TECHNOLOGY

DEPARTEMENT OF ELECTRICAL AND COMPUTER
ENGINEERING
COMMUNICATION STEARM
TITLE: CELLULAR NETWORK DESIGN
GROUP NAME ID NO
1.TOLU AYANA 0560
2.MITIKU GEREMU 0572
3.YOSEF DIRIBA 0584
4.YORDANOS BIRHANU 0538
5.TIGIST GETACHEW 0414

SUBMITTED TO: INST.MR.KEHALI.A

 Introduction
In present day technology, mobile world plays a high flying role in every individual day to day
life. There has been drastic change in the field of cellular technology since few decades. The
cellular concept was a major breakthrough in solving the problem of spectral congestion and user
capacity. It offered very high capacity in a limited spectrum allocation without any major
technological changes. Cellular systems, such as LTE, are designed assuming that devices connect
to a base station to communicate. In most cases this is an efficient approach as the server with the
content of interest is typically not in the vicinity of the device. However, if the device is interested
in communicating with a neighboring device, or just detecting whether there is a neighboring
device that is of interest, the network-centric communication may not be the best approach.
Similarly, for public safety, such as a first responder officer searching for people in need in a
disaster situation, there is typically a requirement that communication should also be possible in
the absence of network coverage.
Wireless communications are especially useful for mobile applications, so wireless systems are
often designed to cover large areas by splitting them into many smaller cells. This cellular approach
introduces many difficulties such as how to avoid interference, or how to hand-over from one cell
to another, while maintaining good service quality. Coverage, capacity, interference, and spectrum
reuse are important concerns of cellular systems; this chapter reviews these aspects as well as the
technologies, tools, and standards used to optimize them.
1. Basic Cellular Communications System Concepts
Cellular systems are widely used today and cellular technology needs to offer very efficient use of
the available frequency spectrum. With billions of mobile phones in use around the globe today,
it is necessary to re-use the available frequencies many times over without mutual interference of
one cell phone to another.
It is this concept of frequency re-use that is at the very heart of cellular technology. However the
infrastructure technology needed to support it is not simple, and it required a significant investment
to bring the first cellular networks on line. Early schemes for radio telephones schemes used a
single central transmitter to cover a wide area. These radio telephone systems suffered from the
limited number of channels that were available. Often the waiting lists for connection were many
times greater than the number of people that were actually connected.
Page | 1
In view of these limitations this form of radio communications technology did not take off in a big
way. Equipment was large and these radio communications systems were not convenient to use or
carry around.
1.1 Cell system for frequency re-use
The method that is employed is to enable the frequencies to be re-used. Any radio transmitter will
only have a certain coverage area. Beyond this the signal level will fall to a limited below which
it cannot be used and will not cause significant interference to users associated with a different
radio transmitter. This means that it is possible to re-use a channel once outside the range of the
radio transmitter. The same is also true in the reverse direction for the receiver, where it will only
be able to receive signals over a given range. In this way it is possible to arrange split up an area
into several smaller regions, each covered by a different transmitter / receiver station.
These regions are conveniently known as cells, and give rise to the name of a "cellular" technology
used today. Diagrammatically these cells are often shown as hexagonal shapes that conveniently
fit together. In reality this is not the case. They have irregular boundaries because of the terrain
over which they travel. Hills, buildings and other objects all cause the signal to be attenuated and
diminish differently in each direction.
It is also very difficult to define the exact edge of a cell. The signal strength gradually reduces and
towards the edge of the cell performance will fall. As the mobiles themselves will have different
levels of sensitivity, this adds a further greying of the edge of the cell. Therefore it is never possible
to have a sharp cut-off between cells. In some areas they may overlap, whereas in others there will
be a "hole" in coverage.
In the cellular concept, frequencies allocated to the service are re-used in a regular pattern of
areas, called 'cells', each covered by one base station. In mobile-telephone nets these cells are
usually hexagonal. In radio broadcasting, a similar concept has been developed based on
rhombic cells.
To ensure that the mutual interference between users remains below a harmful level, adjacent
cells use different frequencies. In fact, a set of C different frequencies {f1, ...,fC} are used for each
cluster of C adjacent cells.
Cluster patterns and the corresponding frequencies are re-used in a regular pattern over the entire
service area.

Page | 2
The total bandwidth for the system is C times the bandwidth occupied by a single cell

For hexagonal cells, i.e., with 'honeycomb' cell lay-outs commonly used in mobile
radio, possible cluster sizes are C = i2 + ij + j2, with integer i and j (C = 1, 3, 4, 7, 9, ..).
Integers i and j determine the relative location of co-channel cells.

Characterizing Frequency Reuse

 D = minimum distance between centers of cells that use the same band of frequencies
(called co-channels)

Page | 3
  R = radius of a cell

 d = distance between centers of adjacent cells (d = R√3)

 N = number of cells in repetitious pattern (Cluster) ¾ Reuse factor ¾ Each cell in pattern
uses unique band of frequencies

 Hexagonal cell pattern, following values of N possible ¾ N = I2 + J2 + (I x J), I, J = 0, 1,

2, 3…

 Possible values of N are 1, 3, 4, 7, 9, 12, 13, 16, 19, 21, …

1.2 Cell clusters

When devising the infrastructure technology of a cellular system, the interference between
adjacent channels is reduced by allocating different frequency bands or channels to adjacent cells
so that their coverage can overlap slightly without causing interference. In this way cells can be
grouped together in what is termed a cluster. Often these clusters contain seven cells, but other
configurations are also possible. Seven is a convenient number, but there are a number of
conflicting requirements that need to be balanced when choosing the number of cells in a cluster
for a cellular system:

 Limiting interference levels

 Number of channels that can be allocated to each cell site

Page | 4
1.3 Cell size
Even though the number of cells in a cluster in a cellular system can help govern the number of
users that can be accommodated, by making all the cells smaller it is possible to increase the overall
capacity of the cellular system. However a greater number of transmitter receiver or base stations
are required if cells are made smaller and this increases the cost to the operator. Accordingly in
areas where there are more users, small low power base stations are installed.
Features of Cellular Systems
Wireless Cellular Systems solves the problem of spectral congestion and increases user capacity.
The features of cellular systems are as follows −
 Offer very high capacity in a limited spectrum.
 Reuse of radio channel in different cells.
 Enable a fixed number of channels to serve an arbitrarily large number of users by
reusing the channel throughout the coverage region.
 Communication is always between mobile and base station (not directly between
mobiles).
 Each cellular base station is allocated a group of radio channels within a small
geographic area called a cell.
 Neighboring cells are assigned different channel groups.

Page | 5
  By limiting the coverage area to within the boundary of the cell, the channel groups
may be reused to cover different cells.
 Keep interference levels within tolerable limits.
 Frequency reuse or frequency planning.
 Organization of Wireless Cellular Network.
Cellular network is organized into multiple low power transmitters each 100w or less.

Page | 6
Cellular network designing using matlab code and using the following parameters
(APPENDIX A)
Radius= 500 m
Number of cluster = 7
Sector=120 degrees

Result

Figure: drawing of hexagonal cellular network using 7 clusters

Propagation Models
A common model approach is to assume the propagation model consists of a random component
and non-random (or deterministic) component. The deterministic component seeks to capture how
a signal decays or attenuates as it travels a medium such as air, which is done by introducing a
path-loss or attenuation function. A common choice for the path-loss function is a simple power-

Page | 7
law. For example, if a signal travels from point x to point y, then it decays by a factor given by the
path-loss function.
L(|x-y|) = |x-y|^a
Where; a = the path-loss exponent, α>2,
|x-y| = the distance between point y of the user and the signal source at point x.
Although this model suffers from a singularity (when x=y), its simple nature results in it often
being used due to the relatively tractable models it gives. Exponential functions are sometimes
used to model fast decaying signal.
From different types of propagation model we selected hata model for our work:-

Modified HATA Model

The actual HATA path loss model is not suitable for the present environment. So the HATA
model is modified as follows for each environment.
For urban environment,

𝑃𝐿,𝑢𝑟𝑏𝑎𝑛 (𝑑)𝑑𝐵 = 69.55 + 26.16 log10 (𝑓𝑐 ) − 13.82 log10 (ℎ𝑡 ) − 𝑎(ℎ𝑟 )
+ (44.9 − 6.55 log10 (ℎ𝑡 )) log10 (𝑑) + 𝐶𝑚,𝑢𝑟𝑏𝑎𝑛

For sub-urban environment

𝑃𝐿,𝑠𝑢𝑏𝑢𝑟𝑏𝑎𝑛(𝑑) 𝑑𝐵 = 𝑃𝐿,𝑢𝑟𝑏𝑎𝑛 (𝑑)𝑑𝐵 − 2(log10 (𝑓𝑐 ⁄28))2 − 5.4

For rural environment,

𝑃𝐿,𝑟𝑢𝑟𝑎𝑙 (𝑑)𝑑𝐵 = 𝑃𝐿,𝑢𝑟𝑏𝑎𝑛 (𝑑)𝑑𝐵 − 4.78(log10 𝑓𝑐 )2 + 18.33 log10 𝑓𝑐 − 𝐾 − 𝐶𝑚,𝑟𝑢𝑟𝑎𝑙

Where; 𝐶𝑚,𝑢𝑟𝑏𝑎𝑛 = correction factor for urban environment and taken as 12.

𝐶𝑚,𝑟𝑢𝑟𝑎𝑙 = Correction factor for rural environment and taken as 29.

Limitations
Though based on the Okumura model [4], the Hata model does not provide coverage to the whole
range of frequencies covered by Okumura model. Hata model does not go beyond 1500 MHz while
Okumura provides support for up to 1920 MHz

Page | 8
 COST-231 Model
Most future Personal Communications Services (PCS) systems are expected to operate in the 1800-
2000 MHz frequency band. It has been shown that path loss can be more dramatic at these
frequencies than those in the 900 MHz range. Some studies have suggested that the path loss
experienced at 1845 MHz is approximately 10 dB larger than those experienced at 955 MHz, all
other parameters being kept constant. The COST231-Hata model extends Hata's model for use in
the 1500-2000 MHz frequency range, where it is known to underestimate path loss.
This model is expressed in terms of the following parameters

Parameters Minimum Value Maximum Value

Frequency, MHz 1500 2000

BS, Antenna height, m 30 200

MS Antenna height, m 1 20
Ranges, km 1 20

Table 1. Validity range of COST231 path loss model.

The path loss formula for COST231is given as follows.

𝑃𝐿, (𝑑)𝑑𝐵 = 46.3 + 33.9 log10 (𝑓𝑐 ) − 13.82 log10 (ℎ𝑡 ) − 𝑎(ℎ𝑟 )
+ (44.9 − 6.55 log10 (ℎ𝑡 )) log10 (𝑑) + 𝐶

Where; C = 0 for medium city and sub-urban areas

C = 3 for metropolitan areas

Page | 9
 Result for COST231 for different base station. (Appendix b)

Figure: Result for COST231 for different base station

For COST 231 also starting by draw path-loss versus separation distance ( 0 to 20 Km ) at
carrier frequency 1200 MHZ and different base station height ( 35 ,125 ,150 m ) for different
environment .
From figure urban and sub- urban environment with carrier Frequency of 1200 MHZ the path
loss of the height base station (125 and 150 m) of urban and sub-urban base station (35 m) is
approximately closed to each other the path loss of rural environment is lower than sub-urban,
even if it have the same carrier frequency and base station height with urban and rural from our
result COST231 model we conclude that an increase of separation distance leads to increase path
loss. However an increase the base station height leads to reduce the path loss.

Page | 10
Appendix A
#code
clc
Clear all
r= 500;
a=100; % the x coordinate of the initial base station
b=100; % the y coordinate of the initial cell
Pause (1);
t=0: pi/3:2*pi;

x=a+ r*cos (t);

y=b+r*sin (t);
figure
pause(1);
plot(x,y,'r')
axis square
hold on
pause(1);
t=0:pi/3:2*pi;
x2=a+(r+(r/2));
y2=b+sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
plot(x3,y3,'c')
axis square
hold on;
pause(1);
x2=a+(r+(r/2));
y2=b-sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
plot(x3,y3,'b')
axis square
hold on;
pause(1);
x2=a;
y2=b-sqrt(3)*r;
x4=x2+r*cos(t);
y4=y2+r*sin(t);
plot(x4,y4,'y')
axis square

Page | 11
pause(1);
hold on;

x2=a;
y2=b+sqrt(3)*r;
x4=x2+r*cos(t);
y4=y2+r*sin(t);
plot(x4,y4,'k')
axis square
hold on;
pause(1);
t=0:pi/3:2*pi;
x2=a-(r+(r/2));
y2=b+sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
plot(x3,y3,'g')
axis square
hold on;
pause(1);
x2=a-(r+(r/2));
y2=b-sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
plot(x3,y3,'m')
axis square
hold on;
pause(1);
t=0:pi/3:2*pi;
x=a+r*cos(t);
y=b+r*sin(t);
fill(x,y,'r')
axis square
hold on
pause(1);
t=0:pi/3:2*pi;
x2=a+(r+(r/2));
y2=b+sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
fill(x3,y3,'c')
axis square
hold on;
pause(1);
x2=a+(r+(r/2));
y2=b-sqrt(3)*(r/2);

Page | 12
x3=x2+r*cos(t);
y3=y2+r*sin(t);

fill(x3,y3,'b')
axis square
hold on;
pause(1);
x2=a;
y2=b-sqrt(3)*r;
x4=x2+r*cos(t);
y4=y2+r*sin(t);
fill(x4,y4,'y')
axis square
pause(1);
hold on;
x2=a;
y2=b+sqrt(3)*r;
x4=x2+r*cos(t);
y4=y2+r*sin(t);
fill(x4,y4,'k')
axis square
hold on;
pause(1);
t=0:pi/3:2*pi;
x2=a-(r+(r/2));
y2=b+sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
fill(x3,y3,'g')
axis square
hold on;
pause(1);
x2=a-(r+(r/2));
y2=b-sqrt(3)*(r/2);
x3=x2+r*cos(t);
y3=y2+r*sin(t);
fill(x3,y3,'m')
axis square
hold on;
pause(1);

Page | 13
 Appendix B
MATLAB code for COST231

%COST231 Model 3
clc;
close all;
clear all;
d = 1:0.01:20;
hr = 5;
ht1 = 35;
ht2 = 125;
ht3 = 150;
fc = 2000;
% a. For Large Cities
% fc >= 1500MHz
ahr = 3.2*(log10(11.75*hr)).^2 - 4.97;
% A. Typical Urban
L50urban1 = 46.3 + 33.9*log10(fc) + (44.9 - 6.55*log10(ht1))*log10(d) -
13.82*log10(ht1) - ahr;
L50urban2 = 46.3 + 33.9*log10(fc) + (44.9 - 6.55*log10(ht2))*log10(d) -
13.82*log10(ht2) - ahr;
L50urban3 = 46.3 +33.9*log10(fc) + (44.9 - 6.55*log10(ht3))*log10(d) -
13.82*log10(ht3) - ahr;
% B. Typical Suburban
L50suburban1 = L50urban1 - 2*(log10(fc/28)).^2 - 5.4;
L50suburban2 = L50urban2 - 2*(log10(fc/28)).^2 - 5.4;
L50suburban3 = L50urban3 - 2*(log10(fc/28)).^2 - 5.4;
% C. Typical Rural
L50rural1 = L50urban1 - 4.78*(log10(fc)).^2 + 18.33*log10(fc) - 40.94;
L50rural2 = L50urban2 - 4.78*(log10(fc)).^2 + 18.33*log10(fc) - 40.94;
L50rural3 = L50urban3 - 4.78*(log10(fc)).^2 + 18.33*log10(fc) - 40.94;
figure(1);
plot(d, L50urban1, 'r',d, L50urban2, '--r', d, L50urban3,':r');
hold on;
plot(d, L50suburban1, 'b', d, L50suburban2, '--b', d, L50suburban3, ':b');
hold on;
plot(d, L50rural1, 'g', d, L50rural2, '--g', d, L50rural3, ':g');
hold on;
legend('urban ht1=35', ' urban ht2=125', ' urban ht3=150','suburban ht1=35',
'suburban ht2=125', 'suburban ht3=150', 'rural ht1=35','rural ht2=125','rural
ht3=150');
grid on;
xlabel('distance [km]');
ylabel('path Loss in [dB]');
title('COST231 Model for different base station antenna ht.');

Page | 14
Reference
[1 ] https://morse.colorado.edu/~tlen5510/text/classwebch2.html
[2] JPL's Wireless Communication Reference Website © 1993, 1995, 1997

Page | 15