LTE Network Dimensioning Tool Using Java

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Dec 12, 2013 (3 years and 7 months ago)

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ISSN:

2278


909X

International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3, Sep
tember

2012

1

A
ll Rights Reserved © 2012 IJARECE




Abstract


T
h
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L
o
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g

t
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m

e
v
ol
u
t
io
n

(
L
T
E
)
.
I
n

t
h
i
s
paper we have focused
on
one of basic steps in LTE network planning denoted by LTE
dimensioning process. This process includes two basic items;
coverage and capacity dimensioning for both uplink and
downlink. By the aid of computer software, LTE dimensioning
was executed and pr
ogram results, in form of tables and curves,
will be analyzed at the last subsection of the paper.


Index Terms



OFDM


LTE


Coverage


Capacity.


I.

I
NTRODUCTION


LTE is the standard for wireless communication specified
by the 3
rd

Generation Partnership P
roject (3GPP). LTE
concerns a wireless communication system optimized for
packet services and realizes high throughput, low latency and
highly efficient frequency utilization. The main benefits of
LTE technology when compared with previous mobile
generatio
n could be summarized as follows: [1]

(1) System optimized for LTE packet services is a wireless
communication system that handless voice calls, which
requires real
-

time processing, as IP packet data (Voice
over IP), in addition to Internet and e
-
mail.

(2
) Simplification of network architecture. With LTE,
eNodeB is required with a wireless access feature and
directly connected to a core network. With a reduced
number of layers of equipment that constitutes a wireless
access network, this system is simplif
ied as compared
with the existing third
-

generation mobile communication
systems. As a result, this system enables low latency for
data transfer and hand
-

over.


Manuscript received Aug

15
, 20
1
2
.

Nelly Muhammad Hussein
,
Communication and electronics department,
Modern Academy for Engineering and Technology, Cairo, Egypt.



Muhamma
d Nabil Saber
,
Communication and electronics department,
Modern Academy for Engineering and Technology, Cairo, Egypt.



Abd El
-
Rahman Ashraf
,
Communication and electronics d
epartment,
Modern Academy for Engineeri
ng and Technology, Cairo, Egypt
.


Amr Saeed Amen
,
Communication and electronics department, Modern
Academy for Engineering
and Technology, Cairo, Egypt.



(3) Wireless access technology robust in multi
-
path
environment. LTE uses orthogonal frequency

division
multiple access (OFDMA) for downlink and single
carrier
-

frequency division multiple access (SC
-

FDMA)
for uplinks. OFDMA incorporates a mechanism to
suppress delayed signal inference by using a cyclic prefix
(CP) in a transmission signal format.

This makes it robust
in a multi
-

path environment.

(4) Adaptive modulation according to communication
quality. In LTE system, three modulation schemes could
be used; quadrature phase shift keying (QPSK), 16
quadrature amplitude modulation (16QAM) and 64
quadrature amplitude modulation (64QAM). Adaptive
modulation and coding is achieved by combining them
with multiple error correction coding rates.

(5) Antenna technology to realize high throughput. LTE
adopts multiple input multiple output (MIMO) as the
a
ntenna technology. MIMO is a spatial multiplexing
transmission technology, in which multiple antennas are
used to transmit and receive data. For example 2 x 2
MIMO allows transmission with approximately twice as
much throughput.


To serve the massive growt
h in demand for mobile
broadband services, a high speed data access is required. A
lot of researches are made to improve high system capacities.
Among these researches, the multiple
-

input multiple
-

output
(MIMO) represents the most effective research resu
lts. The
researches based on MIMO technologies resulted in system
capacity improvement without additional bandwidth.
Multipath propagation causing selective frequency fading
may cause serious problems for mobile communication
system. Therefore, multicarrie
r modulation (MC), especially
Orthogonal Frequency Division Multiplexing (OFDM) is
recommended for solving such problems.


This kind of multicarrier modulation has been receiving
growing interest in recent years as a solution to combat the
effect of frequ
ency selectivity of wireless channels due to
simplified equalization in the frequency domain. MIMO is
associated with OFDM technique which has the ability of
converting frequency selective fading channel into flat fading
channel form. [2].


LTE system is
expected to be competitive for many years,
therefore, the requirements and targets set forth for this
system are quite stringent. In order to achieve such goals,
essential step should take place known by dimensioning of
LTE network. Dimensioning is the ini
tial phase of network
planning. It provides the first estimate of the network element





LTE Network Dimensioning Tool Using Java

Nelly M. Hussein, Muhammad Nabil, Abd El
-
Rahman Ashraf, and Amr Saeed

ISSN:

2278


909X

International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3
,
September

2012


2

A
ll Rights Reserved © 2012 IJARECE

count as well as the capacity of those elements.
Dimensioning process also includes detailed panning and
optimization of the wireless cellular network. In
dimensioning pr
ocess, relatively simpler models and
methods are used for modeling of the actual conditions for
network under consideration. On the other hand,
dimensioning tool should be accurate enough to provide
results with an acceptable level of accuracy, when loaded

with expected traffic and subscriber base.


Wireless cellular network dimensioning is directly related to
the quality and effectiveness of the network, and can deeply
affect its development. Wireless cellular network
dimensioning contains basics steps; Da
ta / Traffic Analysis,
Coverage Estimation, Capacity Evaluation, and Transport
Dimensioning to be explained in details in the coming
subsection. [3]



II.

COVERAGE DIMENSIONIN
G

The

process

for

calculating

LTE

coverage

and

capacity

can

be

made in

an arbitrary

w
ay,

but

adapted

to

the

dimensioning

project

input

demands

and the

expected

output.

The

process

begins

with

defining

quality

requirements expressed

as

bit

rates

on

the

cell

edge,

or

as

coverage

degrees

separately for

uplink

and

downlink,

with

the

desired

ou
tput of

cell

capacity

(uplink and
downlink)

and

site
-
to
-
site

distance.

Figure

(1)
illustrates main steps of dimensioning

process.




















The

quality

requirement

is

based

on

a

throughput

requirement

at

a

given coverage

probability

in

the

uplink

and

downlink.

The

prerequisites

must

be determined as

well.
Depending

on

the

quality

criteria,

the

coverage

can

be
calculated

in

terms of

path

loss,

site
-
to
-
site distance,

or

cell

range.

If

the

coverage does not

meet

the

requirements,

the

definition

of

ce
ll

edge

quality

or

some prerequisites

for

the

calculation

may

need

to

be reiterated.


The

coverage and

the

quality

constraints

at

the

cell

edge

are

used

to calculate

the

capacity
.
Calculating

capacity

includes

two

further

stages:




Uplink

coverage




Downli
nk

coverage

A.

Uplink Coverage

Most mobile telephony systems are frequently limited by the
uplink, so it is useful to start link budget calculations with the
uplink coverage requirements. The calculations are
performed according to the following stages: [5] ,

[6] , [7]



Bit rate requirement.



SINR requirement.



eNodeB receiver sensitivity.



Uplink noise rise (interference margin).



User equipment power per resource block.



Uplink link budget.


Dimensioning starts by defining the quality requirement.
Quality is expre
ssed as a certain bit rate R
req

that can be
provided to one individual user at the cell edge with a
certain probability. The bit rate requirement follows the
service for which the system is dimensioned. All
calculations are performed per resource block. Eq
uation 1
shows how to obtain the bit rate requirement per resource
block, R
req,/RB

defined as required bit rate R
req

divided by the
number of resource blocks (N
RB
).




. . . . (1)


In

a

real

system,

N
RB

for

each

user equipment (
UE) is

selected by

the

scheduler

on

a

1

ms Transmission

Time

Interval (TTI)

level,

based

on

the

throughput

and

power
requirements

at

each signaling interval.

In

a

dimensioning

exercise,

the

number can

be selected

freely,

guided

by

experience

and

understanding

of

the

system within

the

restrictions

of

total

deployed

bandwidth,

as

shown

in

Table

1.

[ 8]


Table 1 ”
Bandwidth and Resource Blocks S
pecified In
3GPP


Bandwidth

N
RB

1.4 MHz

6

3.0 MHz

15

5.0 MHz

25

10.0 MHz

50

15.0 MHz

75

20.0 MHz

100


The

bit

rate

req
uirement

should be

based

on

the

service

for

which

the

system

is dimensioned,

and

as

a

compromise

between

conflicting

needs

and

trends,

with the

following

considerations:

1.

With

a

small

N
RB
,

the

required

bit

rate

can

be
satisfied

with

a

minimum

of resources.

This

leaves

a

maximum

amount

of

space

in

the

time
-
frequency
resource

plane

for

other

users

to

maximize

capacity.

Coverage

Capacity

Done



MIMO



Tx Diversity



UE Power



UE Rx Power



Path loss at cell edge



Cell range



Site
-

to
-

sit
e distance




Uplink cell capacity



Downlink cell


capacity


If input requirements are
not met

Fig. (1) “LTE Dimensioning Process”

Quality at
cell edge



ISSN:

2278


909X

International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3, Sep
tember

2012

3

A
ll Rights Reserved © 2012 IJARECE


2.


At

a

large

N
RB
,

the

transmitted

blocks

are

spread

over

a

frequency

interval, with

less

power

used

per

resource

block.

A lower

modulation

schem
e

or

a
higher

coding rate

can

be

selected.

The

receiver

is

capable

of

decoding the

transmissions

at

lower

SINR,

to

give

a

higher

path

loss

leading to

an

increased

cell

range.

Additionally, the

user

equipment

can

reduce maximum

output

power

when using

large

N
RB
,

according

to

the

3GPP
document

User

Equipment

(UE)

radio

transmission

and

reception
,

3GPPTS

36.101., the

allowed power

reduction

is

not

assumed

to

be

used

at the

cell

edge.

3.

The

impact

from

noise

rise

on the

resulting

coverage

range

when

varying
N
RB

i
n

the

dimensioning

plays

a

comparatively

minor

role,

unless

the

noise rise

is

very

high.

4.

All

resource

blocks

must

be consecutive

in

the

uplink.

Large

N
RB

may

be less

probable

if

the

scheduler

operates

efficiently.


LTE

includes

a

variety

of

different

trans
port

formats

with

different

modulation and

coding

schemes.

Each

format

has

a

specified

bit

rate

R
.

The

SINR requirement

for

decoding

a

particular

transport

format

has

been

determined

by a

large

set

of

simulations.

The

simulation

results

in

a

set

of

tables

for

different channel

models

and

for

different

antenna

arrangements.

As

an

approximation, the

simulation

results

have

been

fitted

to

a

semi
-
empirical

parameterized
expression.



Receiver

sensitivity

in

eNodeB,

S
e
N
o
d
e
B
,

is

the

required

signal

power

at

the
system

reference

point

when

there

is

no

interference

contribution

from

other user

equipments.


The

following

relation

describes

receiver

sensitivity

per

resource

block:


S
eNodeB

= N
t

+ N
f

+10log(W
RB
) +
Ɣ


=N
RB,UL

+
Ɣ
[dBm] . . . (2)

Where:

N
t
: is thermal noise power density

N
f
: is the noise figure of eNodeB receiver.

W
RB

: is the bandwidth per resource block.

Ɣ
: is SINR requirement for the uplink traffic channel.


N
RB,UL
: is therm
al noise per resource block in uplink.


In

LTE

a

user

does

not

interfere

with

other

users

in

the

cell

because

they

are separated

in

the

frequency and time

domain.

The

noise

rise

in

the

uplink

depends only

on

interference

from

adjacent

cells.

In

the

link

bu
dget, an

interference margin

B
I
U

L

compensates

for

noise rise.

In

the

case

of

closed loop

power control

with

a

fixed

SINR

target,

the

interference

margin

is

(as

a

linear

ratio):



B
IUL

= 1 / (1


Ɣ
target

Q
UL

F) . . . . (3)


Where:


is the SINR for target of the uplink loop power
control is the average uplink system load.

Q
UL

: is the average uplink system load.

F

:
is

the

average

ratio

of

path

gains

for

interfering

cells

t
o
those

of

the

serving

cell.



All

allocated

resource

blocks

share

the

total

user

equipment

output power. Assuming

that

all

resource

blocks

are

allocated

an equal

amount

of

power,

the power

per

resource

block

P
U
E
,R
B

is

calculated

in

the

following

way:






P
UE,RB

=P
UE

/ N
RB

. . . . (4)

Where:

P
UE
: total user equipment power.


Finally,

the

uplink

link

budget

can

be calculated

as

follows:


L
pmax

= P
UE,RB

-
S
eNodeB



B
IUL



B
LNF

-

L
BL


L
cpl



L
BPL

+G
a

-
L
j



. . . (5)


Where:

L
pmax

: is the maximum path loss due to propagation in the
air [dB]

B
IUL
: is the interference margin expressed logarithmically
[dB]

B
LNF

: is the log
-

normal fading margin [dB].

L
BL

: is the body loss [dB].

L
cpL

: is the car penetr
ation loss [dB].

L
BPL

: is the building penetration loss [dB].

G
a

: is the sum of the maximum gain in the forward direction
of eNodeB antenna, and user equipment antenna gain
[dBi].


L
i

: is the tower mounted amplifier (TMA) insertion loss
[dB].


The

log
-
normal

(or

slow)

fading

margin

models

the

required

area coverage probability.

By

adding

this

margin,

a

probability

is

secured

for

setting up and maintaining

a

connection

at

a

given quality.


Table 2

shows

fading

margins

in

dB

for

varying

standard

deviatio
n “
σ”

of

the

log
-
normal

fading

process

and

different

coverage

probabilities:


Table

2:

“Fading

Margins

for

Varying

Standard

Deviation

of

Log
-
Normal

Fading”

Environment

σ
[dB]

Coverage Probability

98%

95%

90%

85%

Rural,
Suburban

6

5.5

2.9

0.5

-
1.2

Dense
urban
and Suburban
indoor

10

10.6

6.7

3.1

0.6

Urban indoor

12

13.1

8.4

4.2

1.3

Dense urban

14

15.3

9.9

5.1

1.8

ISSN:

2278


909X

International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3
,
September

2012


4

A
ll Rights Reserved © 2012 IJARECE


B.


Downlink Coverage:

The

downlink

link

budget

is

calculated

for

the

following

purposes:



To

determine

maximum allowed path loss.



To

determi
ne

the

bit

rate

that

can

be

supported

in

the

downlink

at

the uplink

cell

range

limit.


The

calculations

are

performed

based on some givens as
follows:



Maximum

air

path

loss

from

uplink.



Bit

rate

requirement.



Power

per

resource

block



Downlink

noise rise

(in
terference

margin)



Downlink

link

budget



Mobile unit sensitivity.



Bit

rate

at

the

cell

edge



Concluding

the

link

budget


L
p
m
a
x

from

the

uplink

link

budget

calculations is

the

starting

point

of

the downlink

calculations

and

is

used

to

obtain

a

downlink

noise

rise

estimate.

At the

end

of

the

link

budget

calculation

process,

if

the

downlink

L
pmax

is

less

than the

uplink

L
pmax
,

both

the

uplink

and

downlink

link

budgets

can

be

recalculated (including

the

noise rise)

using
the

new

L
pmax
.


As

with

the

uplink,

the

bi
t

rate requirement

is

expressed

per

resource

block

in

the

calculations.

However, unlike

the

uplink,

the

downlink

scheduler

can

allocate

resource

blocks

across the

entire

deployed

bandwidth

without

requiring

them

to

be

consecutive.

It can

be shown

that

it

i
s

always

favorable

to

spread

the

transmission

across

as many

resource

blocks

as

possible.

Assuming

this,

the

number of

allocated resource

blocks

N
RB

in

the

downlink

for

dimensioning

is

set

to

the

total

number of

resource

blocks

for

the

deployed

bandwidth.


In

this

process,

the

obtained

bit

rate

requirement

per

resource

block

is

not

used directly

to

calculate

power

per

resource

block,

but

to

compare

with

the

rate

that can

be

obtained

at

the

cell

edge

given

by

the

uplink

link

budget.

Alternatively,

it can

be

used

as

a

starting

point

for

link

budget

calculations.


The

power

in

LTE

is

shared

by

all

resource

blocks.

It

is

assumed

that

all resource

blocks

are

allocated

an

equal

amount

of

power.

An

individual

resource block

has

no

power

control.

Instead,

users

are

scheduled

with

high

rates

every
millisecond.


The

power

per

resource

block

is:


P
tx,,RB
= P
nom,ref
/ N
RB



. . . (5)

Where:

P
nom,
r
ef
:

is

the

sum

of

nominal

power

from

all

radio

units

in

the

cell

at

the reference

point

[Watt].


T
he

downlink

noise

rise

B
I
D
L

on

the

cell

edge

is

needed

for

the

link

budget

and is

calculated

using

the

following

expression

(all

quantities

linear):


B
IDL

=1 +( P
tx,RB
Q
DL

F
c

/(N
RB,DL
L
sa,max
)
) … (6)


Where:


Q
DL

: is the downlink system load.

F
c
: is the
average ratio between the received power from other
cells to that at the cell edge location.

N
RB,DL
:
is

the

thermal

noise

per

resource

block

in

the

downlink, defined

by

N
t

+

N
f

+

1
O
l
o
g

(W
RB

)

similar

to

Equation (2).

L
sa,max
:

is the signal attenuation in d
ownlink corresponding to
L
pmax

calculated by the following expression:


L
sa,max
=L
pmax

+ B
LNF

+ L
BL

+L
CPL

+ L
BPL



G
a

+L
j

[dB]


















. . . (7)


The

downlink

link

budget,

L
pmax

,

is

calculated

by

the

following

equation:


L
pmax

= P
tx,RB


S
UE


B
IDL


B
LNF


L
BL


L
CPL


L
BPL


+G
a

-
L
j

. . . (8)

Where:

P
tx,RB

:
is

the

transmitter

power

per

resource

block

at

the
system

reference

point

[dBm]

S
UE
:
is

the

user

equipment

sensitivity

in

dBm.


T
he

only

unknown

variable

in

Equation

7

is

the

user

equipment

sensitivity

S
U
E
. Analogous

to

Equation

2,

it

is

written as

follows:


S
UE

= N
t

+ N
f

+10log(W
RB
) +
Ɣ



=N
RB,UL

+
Ɣ
[dBm] . . . (9)


The

calculation

of

SINR

on

cell

edge

is

given

by

the

following

equation:


Ɣ

= P
tx,RB


L
pmax



N
RB,UL

S
UE


B
IDL


B
LNF


L
BL



L
CPL


L
BPL

+G
a

-
L
j

[dBm]


. . . . (10)


The

cell

edge

SINR

estimate

is

transformed

into

a

bit

rate

per

resource

block,
R
RB
,

by

the

same type

of

semi
-
empirical

relationship

as

for

the

uplink

SINR
requirement.


The

resulting

bit

rate

R
RB
is

multiplied

by

the

number

of

resource

blocks

N
RB

to obtain

the

maximum

b
it

rate

R

expected

on the

cell

edge.

If

the

uplink

is

really the

limiting

link,

as

in

an

initial

assumption,

R

should

be

larger

than

the

required bit

rate

R
r
e
q

.


III.

CAPACITY DIMENSIONIN
G

A.


Uplink Capacity:

Capacity

dimensioning

obtains

input

information

to

the

phases after

radio interface

dimensioning:

transmission

link

dimensioning

and

eNodeB dimensioning.

The

method

is

specified

for

a

certain

background

load,

known

as system

load.

The

dimensioning

method

finds

the

maximum

capacity

that

the target

cell

can

sustain

momentarily,

given

the

system



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Volume 1, Issue
3, Sep
tember

2012

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ll Rights Reserved © 2012 IJARECE


load

in

the

surrounding cells.

It

is

improbable

that

all

cells

in

a

system

are

fully

loaded

at

the

same

time, as

observed

in

real

networks

of

different

technologies. The

following

downlink

capacity

calculations

are

pe
rformed:



SINR.



Cell

throughput
.

The

operating

mode with

power

control

assumes

perfect

power

control

and infinite

power

dynamics.

User

equipment

is

received

at

the

SINR

identical

to

Ɣ
t
a
rg
e
t

as

obtained

from

previous subs
ection.

The

bit

rate

per

resource

blo
ck
R
R
B
,U

L

is

identical

to

the

bit

rate

corresponding

to

the

SINR

and

the

number

of allocated

resource

blocks
N
RB
.
The

average

user

bit

rate

R
R
B
,U
L

is

scaled

proportionately

with

the

number

of

resource

blocks

N
R
B

corresponding

to

the

deployed

bandwidth,

s
ee

Table

(1)
.


In

the

uplink,

one

or

more

resource

blocks

are

always

allocated

at

each

band edge

to

signal

users

in

idle

mode

on

the

channel

Physical Uplink

Control Channel

(PUCCH).

For

this

reason,

the

number

of

resource

blocks

in

uplink
available

for

cal
culating

capacity

are

always

reduced

by

a

number

N
P
U

C

C

H

. (
Note: recommended value for N
PUCCH

= 4).


In

a

similar

way,

resource

blocks

allocated

for

Physical Random

Access Channel

(PRACH),

N
P
R
AC
H
,

reduce

the

available

number

of

resource

blocks

in uplink
.

The

resulting

average

user

bit

rate

per

cell

is:


R
avr,UL
=R
RB,UL
(
N
RB



N
PUCCH



N
PRACH
)



…. (11)


The

cell

throughput

is

shown

in

the

following

equation:


T
cell,UL
= Q
UL

R
avg,UL

. . . (12)


B.


Downlink Capacity

The

following

down
link

capacity

calculations

are

performed:



SINR.



Cell throughput.

The

downlink

capacity

is

based

on the

SINR

at

the

average

location

within

a cell,

denoted

R
D
L,a
v
e

as

a

linear ratio.

The

average

SINR

is

expressed

in

the average

noise

rise.

This

is

similar

t
o

the

interference

margin,

but

the

SINR

is evaluated

at

an

average

location

instead

of

at

the

cell

edge
:


B
DL
-
noiserise
= 1 + (P
tx,RB
Q
DL

F) / (N
RB
,
DL

L
sa,max
)






. . . (13)


The

resulting

average

SINR,

R
D
L
,
a
v
e

is

shown

in

the

following

equation:


R
DL,ave
= P
tx,RB
/( B
DL
-
noise rise
N
RB,Dl
H L
sa,max
)





. . . . (14)


In

the

above
equation,

H

is

the

average

attenuation

factor.

It

is

the

ratio

between

the (linear)

average

signal

attenuation

in

the

cell

and

the

(linear)

signal

attenua
tion at

the

cell

range

distance

from

the

antenna.

H

depends

on the

site geometry,
antenna

pattern,

wave

propagation

exponent,

and

base

station

antenna

height.


The

cell

throughput

is

shown

in

the

following

equation:



T
cell,DL
= Q
DL

n
RB

R
RB,DL

. .
. .
(15)


IV.

WAVE PROPAGATION

In this paper, proposed propagation model is
Ericson Variant
Okumura
-

Hata Model

given as follows: [4]

L
p

= A


13.82 log h
b



a(h
m
)


+ (44.9


6.55 log h
b

) log R

. . . (16)


Where:

L
P

: is the air path loss.

A:
is the frequency
-

dependent fixed attenuation factor. See
table (3).

h
b

: is the base station height [m].

h
m

: is the height of the user equipment antenna [m].

R: is the distance between base station and mobile unit. [km]


Table

3 “
Fixed

Attenuation

A in

O
kumura
-
Hata

Propagation

Model


Environ.

Frequency [MHz]

850

900

1700

1800

1900

Urban

146.2

153.2

153.8

154.3

155.1

Suburba
n

127.0

127.5

133.6

134.1

134.6

Rural

127.0

133.6

134.1

134.6

135.3

Open

117.8

118.3

123.8

124.3

124.8


V.

SOFTWARE RESULTS AND

AN
ALYSIS

System Description:

Downlink cases simulated include the following:



Antenna

techniques:

Single

Input

Multiple

Output

(SIMO)

1x2,

TX

diversity 2x2,

Open

Loop

Spatial

Multiplexing

(OLSM)
2 x 2.



Modulation

schemes:

QPSK,

16
-
QAM,

64
-
QAM.



Channel

models:

EPA 5

Hz,

EVA 70 Hz,

ETU

300

Hz.


Downlink cases simulated include the following:



Antenna

techniques:

2
-
branch

RX

diversity.



Modulation

schemes:

QPSK,

16
-
QAM.



Channel

models:

EPA 5

Hz,

EVA 70 Hz,

ETU

300

Hz.


Figure (2) displays steps of capacity and cove
rage
dimensioning for both up link and downlink in flowchart
form. Some assumptions should be considered as follows:

1
. The tool is designed to carry out both coverage and
capacity estimations. It performs the required
calculations, providing the optimum s
ite count on the
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Volume 1, Issue
3
,
September

2012


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ll Rights Reserved © 2012 IJARECE

basis of user inputs, and also the provided capacity by
optimizing specific inputs.

2.

The tool is basically supposed to be user
-
friendly in a way
that it doesn’t require heavy training to manage it; also
inputs and outputs are placed on
separate main sequenced
panels so user can easily distinguish between them.

3.

The tool optimizes the output coverage and capacity
number of sites to the minimum number that satisfies and
enhances all the QOS (Quality of Service) attributes,
using a uniqu
e optimization algorithm in order to allow
the user to achieve the best possible QOS with the
minimum number of sites so that decrease the cost
needed.






























VI.




















LTE Dimensioning process was executed by the aid of
ja
va script. In order to facilitate system parameters
entering and output display, GUI was used. Figure (3)
shows forms obtained after program run. Figure (3
-
a) is
used for input and output arguments whereas, figure (3
-
b)
illustrates final distribution of eN
odeB over selected.

























VII.



VIII.







Let’s display an example for the sequence of arguments
(input and output) fed to dimensioning program during one
of its runs:

(
Note:

Dimensioning process was applied over selected areas
in Egypt).



Region Selection:

o

Region Name
→ Maadi
(user selected)

o

Scatter type → Urban
(program determined)

o

Total area → 9 km
2

(program determined)

(a)

(b)

Fig. (3) “Results obtained from LTE dimensioning Java
Program”:

(a)

GUI input form.

(b) Final distribution of base stations over map.

Fig. (2) “Overall dimensioning system

flowchart”

Start


User input
data

Coverage

Capacity

Pr
opagation
calculation

Uplink
calculation


Display
L
pmaxUL

Downlink
calculation

Display
Lpmax
DL

LpmaxuL
<Lpmax
DL


L
pmaxUL

Is limiting
link

Back
tracking
process

LpmaxuL
<Lpmax
DL


Downlink
calculation

Display
average
user bit
rate

Display cell
throu
ghput



Display average
user bit rate

D
isplay cell
throughput



Display
cell radius

Display
inter site
distance

Display
sites on

map

Yes

No

Yes

No

Uplink

calculation

LpmaxUL

Is limiting
link



ISSN:

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Volume 1, Issue
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tember

2012

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ll Rights Reserved © 2012 IJARECE


-115
-110
-105
-100
-95
-90
-85
-80
-75
80
85
90
95
100
105
110
115
120
125
User Equipement Senstivity (SUE) dBm
Lpmax (DL) dB


Double Tx antenna
Single Tx antenna
Trible Tx antenna

Main Dimensioning Input Parameters:

o

Frequency Band → 2600 MHz


(user determined)

o

Carrier Band Width → 20 MHz


(user determined)

o

Antenna Gain

→ 18.5 dBi

(user determined)

o

Uplink required bit rate → 500 kbps


(user determined)

o

Downlink required bit rate → 1000 kbps


(user determined)

o

Antenna Arrangement → SIMO 2x1

(user determined)

o

Uplink cell loading percentage → 30%

(user determined)

o

Downli
nk cell loading percentage → 50%

(user determined)


Uplink Coverage Parameters:

o

Power of user Equip. → 23 dBm

(user determined)

o

Number of resource block → 5

(user determined)

o

In or out car → Out
(user determined)

o

Car penetration loss → 0 dB



(program determined)

o

Building penetration loss → 18 dB



(user determined)

o

Transmitted data → VOIP



(user determined)

o

Body loss → 3 dB

(program determined)

o

SI
NR of most interfering service


cell edge


→ 4.9136 dB (
program determined)

o

Coverage prob. → 95%

(user determined)

o

Log
-

normal fading → 4.9 dB



(program determined)

o

Cable type → Fiber

(u
ser determined)

o

Base station height → 30 m



(user determined)

o

Uplink max. path loss → 123.2 dB



(program determined)


Downlink Coverage Parameters:

o


No. of antenna in Se
-
Node B



→ Single Antenna
(program determined)

o


Noise Figure → 7 dB
(program determined)

o


User equipment sensitivity →
-
115 dBm

(user determined)

o


Downlink max. path loss → 122.43 dB



(program determined)


The Capacity Parameters:

o

Bit ra
te per resource block (uplink)


→ 100 kbps
(program determined)

o

No. of resource blocks for control channel


→ 3
(user determined)

o

Average user bit rate per cell (uplink)


→ 9.7 Mbps
(program determined)

o

Cell throu
ghput (uplink) → 2.91 Mbps


(program determined)

o

Average downlink SINR → 6.98 dB


(program determined)

o

Average user bit rate per cell (downlink)


→ 28.756 Mbps
(program determined)

o

Cell throughput (downlink) → 14.378 Mbps


(program determined)


Propagation Model:

o

The cell radius → 382.2 m


(program determined)

o

Number of cells → 31
(program determined)

o

Min. distance bet
ween two base stations


→ 573.32 m
(program determined)



Form all system parameters displayed in the previous
example, there are specific parameters have remarkable
effect on system performance. In the coming set of curves,
we have selected

the most effective parameters and displayed
system performance with those parameters variation. The
first set of curves illustrates effect of mobile unit sensitivity
on maximum allowed downlink path loss. Figure (4) displays
maximum allowed path loss vers
us variation in mobile unit
sensitivity in three situations; using single, double, and triple
transmitting antenna in eNodeB.






















System parameters used to obtain the above set of curves are
as follows:

Scatter type is urban, frequency b
and = 2600 MHz,

carrier bandwidth = 20 MHz, antenna gain = 18.5 dBi, uplink
required bit rate = 500 kbps, downlink required bit rate =
1000 kbps, uplink cell loading percentage = 30%, downlink
cell loading percentage = 50%, power of user Equip. = 23
dBm, N
umber of resource block = 5, out car, building
penetration loss = 18 dB, transmitted data is VOIP, coverage
prob. = 95%,

cable type is fiber, base station height = 30 m
and number of resource blocks for control channel = 3.


Fig. (4) “Performance of maximum allowed downlink path
loss versus variation in user equipment sensitivity”

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2012


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30
35
40
45
50
55
60
300
400
500
600
700
800
900
1000
1100
Base Station Height [m]
Cell Radius [m]


Urban
Rural
Suburban
As shown in figure (4), maxim
um allowed path loss is
inversely proportional to user equipment sensitivity and this
relationship is logic. Receiver sensitivity represents
minimum detectable power. So smaller receiver sensitivity
means more allowance for channel conditions to be worse
a
nd it is well known that propagation path loss is the most
effective factor on transmitted signal attenuation. Therefore
receiving sensitivity is still the most important parameters at
any mobile hand set. The new observation obtained from
figure (4) is th
e effect of transmitting antennas number on the
maximum allowed path loss.


As seen from the above set of curves that by using two
transmitting antennas at eNodeB, larger level of allowed
maximum path loss could be obtained when compared to
single transmi
tting antenna case. The explanation for that is
the increment occurs in the SNR when the number of
transmitting antennas increases. But actually there is main
constrain for this benefit is the cost of transmission power.
Therefore, transmitted power is ret
urned to normal in case of
triple transmitting antennas.


The next set of curves shown in figure (5) displays effect of
base station height variation on the cell site radius in three
different regions; urban, suburban and rural.


System parameters used to

obtain set of curves shown in
figure (5) are as follows:

Frequency band = 2600 MHz, carrier bandwidth = 20 MHz,
antenna gain = 18.5 dBi, uplink required bit rate = 500 kbps,
downlink required bit rate = 1000 kbps, uplink cell loading
percentage = 30%, do
wnlink cell loading percentage = 50%,
power of user Equip. = 23 dBm, number of resource block =
5, out car, building penetration loss = 18 dB, transmitted data
is VOIP, coverage prob. = 95%,

number of transmitting
antennas in eNode B =1, cable type is fi
ber, base station
height = 30 m and number of resource blocks for control
channel = 3.
























The relationship between base station height and cell site
radius is direct proportionality. This arises from the radiation
ability of higher an
tenna system for larger distance
destination points. Another explanation for this relationship
is that higher base station means more resistivity against path
obstacles resulting in better channel fading conditions (i.e.
signal keeps its strength for longe
r distance). Actually there is
another factor affecting on cell site radius is the capacity of
subscribers defined over region of interest. Figure (5) tells us
base station located in rural region (low traffic or capacity
region) can cover larger cell size

when compared with
suburban and urban regions which have higher traffic
capacity.


Another observation obtained from figure (5) is that linear
proportionality between base station height and cell radius
has various slopes based on regions nature. In case

of rural
regions, any small change in base station height will cause
larger change in cell radius w.r.t. urban and suburban
regions.


Let’s display an example for cell radiuses obtained at base
station heights = 30 and 40 m displayed in table (4).


Table

(4): “Cell radiuses corresponding to 40 m base station
height”

Base
Station
Height
(m)

Cell Radius
(m)



Urban


Cell
Radius
(m)


Rural


Cell Radius
(m)


Suburban


30

370

810.886

513.14

40

405.7

905.69

567



Remember numerical example mentioned at the

beginning of
this subsection which included arguments resulted and
obtained from dimensioning program, in that example we
have seen that there is difference between required bit rate
and actual obtained bit rate when capacity dimensioning is
applied. The
last set of curves shown in figure (6), illustrates
comparison between actual bit rate obtained at four
situations; single, double, triple and four transmitting
antennas.


System parameters used to obtain set of curves shown in
figure (6) are as follows:

Scatter type is urban, frequency band = 2600 MHz, carrier
bandwidth = 20 MHz, antenna gain = 18.5 dBi, uplink
required bit rate = 500 kbps, downlink required bit rate =
1000 kbps, uplink cell loading percentage = 30%, downlink
cell loading percentage = 30
%, power of user Equip. = 23
dBm, number of resource block = 5, out car, building
penetration loss = 18 dB, transmitted data is VOIP, coverage
prob. = 95%,, cable type is fiber, base station height = 30 m
and number of resource blocks for control channel

= 3.

Fig. (5) “Performance of cell site radius versus variation in
扡獥⁳瑡瑩潮⁨敩g
ht”



ISSN:

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International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3, Sep
tember

2012

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ll Rights Reserved © 2012 IJARECE






As mentioned before, MIMO technology is essential need in
LTE technology. In traditional MIMO systems, the same data
symbol is emitted simultaneously from all transmitting
antennas. But in the modified MIMO technique applied in
LTE, data symb
ols are arranged over transmitting antennas at
each signaling interval. Therefore, transmission rate over
each antenna will be smaller than original data rate from
source. Which means original data rate could be increased
without fearing from fading bad co
nditions (especially
frequency selective fading distortion).


Figure (6) shows that the greater is the number of
transmitting antennas, higher bit rate could be allowed But
this direct relationship between number of transmitting
antennas and bit rate is on
ly considered in downlink situation
not uplink. The reason for this is the ability of inserting
multiple transmitting antennas in eNodeB whereas in mobile
unit antenna configuration is usually fixed. In the coming
table we display bit rate per cell conside
red for each case of
antenna configuration shown in figure (6)


Table (5): “Bit rate per cell for uplink and downlink for
different antenna configurations at eNodeB”


1 Tx
antenna

2 Tx
antenna

3 Tx
antenna

4 Tx
antenna

Uplink

5.9

Mbps

5.75
Mbps

5.9375
Mb
ps

5.9375
Mbps

Downlink

25.6
Mbps

31.87
Mbps

35.04
Mbps

36.97
Mbps










VI.

CONCLUSION

Long Term Evolution (LTE) technology has solved many
problems facing mobile communication systems in its last
generations previous to LTE system. LTE belongs to 3.9
mo
bile generation. And in order to gain all benefits of LTE
system, it has to be well designed. LTE dimensioning is
considered the main stage in planning process. In this paper
we have seen detailed LTE dimensioning tool using java
script. All used equations

and flowchart have been explained
in details through paper subsections. From all parameters
affecting on LTE system performance we have focused on
some parameters and displayed their effect on system
behavior such as; base station height, number of transm
itting
antennas, region capacity nature, and user equipment
sensitivity. But remember that all previous analysis is based
on
Okumura
-

Hata Model

that matches most regions in
Egypt.






REFERENCES


[1] Watanable a
nd Machida, “Outdoor LTE Infrastructure Equipment
(eNodeB), Fujistu Sd. Tech. J., Vol. 48, No. 1, January 2012.

[2] Khlifi and Bouallegue, “Hybrid LS
-

LMMSE Channel Estimation
technique for LTE Downlink Systems”, International Journal of Next
-

Generation
Networks (IJNGN) Vol. 3, No. 4, December 2011.

[3] Syed, “Dimensioning of LTE Network”, Helsinki University, Master of
Sciences thesis, Feb. 2009.

[4] Zhung, “Network Capacity, Coverage Estimation and Frequency
Planning of 3GPP Long term Evolution”, Mast
er of Sciences thesis,
Linkoping University, September, 2010.

[5] “Coverage and Capacity dimensioning Recommendation”, Ericson Jan.
2010.

[6] “LTE Radio Network Coverage Dimensioning”, HUAWEI, 2010.

[7] Mishra, “Advanced Cellular network Planning and Opti
mization”,
WILEy 2007.

[8] “Nokia Siemens Network LTE Radio Access Operating Documentation”,
Jun 2011.




Nelly Muhammad

Hussein,
Ph.D. from Faculty
of Engineering
-

Communication department,
Cairo University 2010. .
Lecturer
in Modern
Academy for
Engineer
ing and Technology,
Communication Dept.
Published 5 single author
papers mentioned as follows:

1.

“Applying Channel Equalization Techniques to
STBC OFDM


CDMA System in The
Pr
esence of Multi
-
Path Frequency Selective
Channel Fading” , Vol. 5, No. 4, April 2009.

2.


“Performance Enhancement of STBC OFDM
-

CDMA
System
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Downlink Bit Rate p
er Cell

Up
link Bit Rate p
er Cell

Fig. (6) “Bit rate per cell obtained from uplink and downlink
capacity dimensioning”

ISSN:

2278


909X

International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE)


Volume 1, Issue
3
,
September

2012


10

A
ll Rights Reserved © 2012 IJARECE


Muhammad Nabil Saber

B.Sc. from Modern
Academy for Engineering and Technology


Communication Dept. in May 2012
.

This work
is part of graduation project with the same title
of paper.







Abd El
-
Rahman Ashraf

B.Sc. from Modern
Academy for Engineering and Technology


Communication Dept. in May 2012. This work
is part of graduation project with the same title
of paper
.







Amr Saeed
Amen


B.Sc. from Modern
Academy for Engineering and Technology


Communication Dept. in May 2012. This work
is part of graduation project with the same title
of paper.