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
r
o
u
g
h
o
u
t
t
h
e
p
a
s
t
f
ew
y
e
a
r
s
,
t
h
e
r
e
h
as
b
e
e
n
a
maj
o
r
d
e
v
e
l
o
p
ment
i
n
t
h
e
c
o
mm
un
i
c
a
t
io
n
f
i
e
l
d
i
n
g
e
n
e
r
a
l
a
n
d
t
h
e
m
o
b
il
e
f
i
e
l
d
i
n
p
a
r
t
i
c
u
l
ar
as
i
t
i
s
t
h
e
e
a
s
i
e
s
t
w
ay
t
o
c
o
mm
un
i
c
a
t
e
w
i
t
h
s
o
me
on
e
a
n
y
w
h
e
r
e
i
n
t
h
e
w
o
r
l
d
.
T
h
e
d
e
v
e
l
o
p
ment
t
oo
k
p
l
ace
t
h
ro
u
g
h
a
nu
m
b
er
o
f
ph
a
s
es
b
e
g
i
nn
i
n
g
w
i
t
h
t
h
e
a
n
a
lo
g
c
o
m
m
un
i
c
a
t
i
o
n
t
h
en
m
o
v
i
n
g
t
o
t
h
e
d
i
g
i
t
a
l
o
n
e,
t
h
i
s
t
r
a
n
s
fu
s
io
n
i
m
p
li
e
d
ma
k
i
n
g
n
u
me
r
o
u
s
m
o
d
i
f
i
c
a
t
io
n
s
i
n
c
l
u
d
i
n
g
;
i
n
c
r
e
a
s
i
n
g
t
h
e
d
a
t
a
r
a
t
e
a
n
d
r
e
li
a
b
i
l
i
t
y
,
i
n
a
d
d
i
t
i
o
n
t
o
a
d
d
i
n
g
m
o
r
e
s
e
r
v
i
c
es
li
k
e
v
i
d
eo
b
ro
a
dc
a
s
t
i
n
g
,
m
u
l
t
i
-
med
i
a
s
e
r
v
i
c
e
s..
. e
t
c
.
N
o
w
a
d
a
y
s
o
n
e
o
f
t
h
e
m
o
s
t
i
m
p
or
t
a
n
t
ph
a
s
es
i
s
t
h
e
L
o
n
g
t
e
r
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
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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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2012
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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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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
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2012
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-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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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”
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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
Using Channel Coding Techniques over Multipath Fading
Channel” ,Vol. 5 No. 5, May 2009.
3.
“
LTE System Performance In Frequency Selective Fading Channel
with aid of STBC Technology”, UNIASCIT, Vol 1 (2), 2011,
54
-
62.
4.
“Wavelet Transform Effect on MIMO
-
OFDM System
Performance”, Cyber Journals: Multidisciplinary Journals in
Science and Technology, J
ournal of Selected Areas in
Telecommunications (JSAT), September Edition, 2011.
5.
“
Performance of OFDM
-
CDMA System using Modified Space
-
Shift Keying Technique”, International Journal of Information
and Communication Technology Research, Volume 2 No. 2,
F
ebruary 2012.
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.
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