Transcript of 02 RA2006-13A Coverage Planning
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Academy course:
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Module objectives
After completing this learning element, the participant will be
able to:
Theory:
Explain the elecromagnetic wave propagation characteristic in real
environment and why is necessary to create propagation models
List which propagation models are in use for planning and how to
apply most suitable
Explain how are created the basic propagation (Okumura Hata and
COST Hata) models and their usage
List alternative models e.g. Walfish Ikegami, Knife edge,
Ray-tracing and ray-launching model
Explain the link balance and the factors in UL/DL calculations for
loss calculations in GSM networks
List and explain the Link Budget Parameter (eg. the fading
factors)
List peak power values at antenna connector and antenna gains
Define the noise and interference taken in account for
planning
Explain how to calculate cell areas of different type of cells in
different environments
List the planning tools used by NSN
List the type of measurements used in the planning process
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Content: Coverage Planning
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Content: Radio Wave Propagation Modeling
Introduction to Radio Wave Propagation
Propagation characteristics
Exponential law
Original formulas
Modeling of Buildings and other Obstacles
Walfish Ikegami model
Knife edge models
Ray-tracing and ray-launching
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Content: Radio Wave Propagation Modeling
Introduction to Radio Wave Propagation
Propagation characteristics
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Propagation Characteristics (Overview)
Radio wave propagation described by solutions of the Maxwell
equations
energy spreading
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absorption at large obstacles depending on at small obstacles at
edges
medium density
In real environment appear unavoidable effects, which make usage of
Maxwell equations not practical
Dilution (free space propagation)
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Free-space propagation
Reflection
- phase f - f
- polarisation material dependant
- phase f random phase
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Absorption
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Linear
In field strength Reciprocal
In UL and DL channel same characteristics (if in same
frequency)
Dispersive
In spectrum (for a wideband channel)
Propagation Characteristics (Radio Channel Characteristics)
echoes
amplitude
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Radio signal propagates from A to B over multiple paths using
different propagation mechanisms
Multipath Propagation
Received signal is a sum of multipath signals fast fading
Different radio paths have different properties
Distance time delay
Direction angular dispersion
Receiver and transmitter movement Doppler shift of frequency
(Doppler spread can be neglected, but fast fading very frequency
selective)
Propagation Characteristics (Multipath)
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Inter symbol interference
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Viterbi equalization
Viterbi equalization generally applicable for signals that have
been reflected
from far away objects
26 bits designated for a "training sequence" included in each
transmitted
TDMA burst
Channel coding
For error detection and correction purposes
Gives the possibility to regenerate up to 12.5% of data loss
Interleaving
Data recovery possible even if one burst is lost
Propagation Characteristics (Compensation of Signal
Distortion)
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Fading describes the variation of the signal level when the
receiver
moves into the cell coverage area
Fading commonly categorised to two categories based on the
phenomena
causing it
Fast fading: Multipath propagation
Frequency-selective fading: long time delay
Space-selective fading: large angular dispersion
Propagation Characteristics (Fading)
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Exact solution of Maxwell equations not practical for real
environment
because of the complexity
On the other side full information provided by exact solution (e.g.
exact
polarization and phase besides the field strength) mostly not
needed
What is needed is the received power level
A propagation model predicts the path loss L(d) and thus power
level in
dependence on the distance d from the transmitting antenna.
Target: cell range estimation from prediction model:
Propagation model Max. allowed path loss Cell radius
Propagation Model Overview
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Propagation models provide a forecast for
Average signal
Variations around the average
Models must give a forecast as close as possible to real scenarios,
so that they can be used as reliable tools to plan cellular
networks
Propagation Medium
Path Loss
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Wave propagation described by rays travelling between transmitted
and receiving antenna and coming into reflections, scattering,
diffractions etc.
Optical ray techniques give very accurate descriptions of the wave
propagation but require a large computation time
Equation based on fit of extensive empirical measurements
Can be used only in environments similar to the examined one
Changes of the environment characteristic can cause enormous errors
in the prediction of wave propagation
Combination of empirical and deterministic models
e.g. empirical COST Hata can be combined with deterministic knife
edge model
Propagation Model Overview
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Empirical models
e.g. Log distance path loss, ITU model, Okumura Hata, COST
Hata
Usually empirical models are valid for a quasi flat surface only
(like all the models given
above)
Extension to hilly surface or even mountain area very difficult,
requires often ray-launching
Semi empirical models
e.g. Okumura Hata / COST Hata and knife edge, COST Walfisch
Ikegami
Semi empirical model combine deterministic models (e.g. knife edge
models) with
empirical models (e.g. Okumura Hata or COST Hata)
Combination of empirical and deterministic models requires usually
additional correction
terms
Such correction terms again have to be calibrated with
measurements
Deterministic models
Deterministic propagation models show a strong dependence on
geographical data base
resolution (resolution of at least 5 m required)
Propagation Model Overview
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Content: Radio Wave Propagation Modeling
Basic Propagation Models
Exponential law
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Log distance path loss model
To model real environment, instead of the exponent 2 a path loss
exponent n is used, which has to be determined together with c by
calibration measurements
PTx: Transmitted power
PRx: Received power
Power Law
On logarithmic scale this leads to
L = -10 log (c) - 10 n log (d) = A - log (d)
Free space propagation
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Received power level
on logarithmic scale
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Instead of the path loss exponent n now occurs the absorption
coefficient k, which is given in the unit 1 / km
Far from the BTS, the exponential law predicts a much lower
received power than the power law
On logarithmic scale the exponential law has the form: free space
loss + additional loss in dB / km
Losses in form dB / km often are applied to clutter
corrections
PTx: Transmitted power
PRx: Received power
k : absorption coefficient dependent on environment and
wavelength
In real environment, a exponential law often matches received power
measurement better than a power law
Exponential law
L = A - 20 log (d) + 10 log (e) * k * d
Free space
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Received power level
on logarithmic scale
Rural area
Dense urban area
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Content: Radio Wave Propagation Modeling
Okumura Hata and COST Hata Models
Original formulas
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L = path loss in dB
f = frequency in MHz (valid for 150-1500 MHz)
d = distance in km (valid for 1-20 km)
hBS = height base station in m (valid for 30-200 m)
hMS = height mobile station in m (valid for 1-10 m)
L = 69.55 + 26.16 log (f) - 13.82 log (hBS) - d (hMS) - c + [44.9 -
6.55 log (hBS)] log (d)
correction term c
Original Okumura Hata Model
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Example (f = 900 MHz, hBS= 30 m, hMS = 1.5 m)
Original Okumura Hata Model
c = 9.94
c = 0
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L = path loss in dB
f = frequency in MHz (valid for 1500-2000 MHz)
d = distance in km (valid for 1-20 km)
hBS = height base station in m (valid for 10-200 m)
hMS = height mobile station in m (valid for 1-10 m)
L = 46.3 + 33.9 log (f) - 13.82 log (hBS) - d (hMS) - c + [44.9 -
6.55 log (hBS)] log (d)
correction term c
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Example (f = 1800 MHz, hBS= 30 m, hMS = 1.5 m)
Original COST Hata Model
c = 11.9
c = - 3
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Okumura hata
L = 69.55 + 26.16 log (f) - 13.82 log (hBS) - d (hMS) - c + [44.9 -
6.55 log (hBS)] log (d)
COST Hata
L = 46.3 + 33.9 log (f) - 13.82 log (hBS) - d (hMS) - c + [44.9 -
6.55 log (hBS)] log (d)
Both formulas have the form
L = k1 + k2 log (d) + k3 log (hBS) + k4 log (hBS) log (d) + k5 hMS
+ k6 log (hMS)
k1 … k6 can be estimated by re-fit for any planning project
New coefficients for the operator’s environment and frequency
Extension to any Environment and Frequency
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Extension to Small Distances
Close to BTS
Less loss per km due to obstacles than far away
Received power goes down with lower slope than far away
Two slope model
Separate estimation of k1 and k2 close to the BTS and far
away
Coefficients which are valid for small distances as well
log d
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Extension to Mixed Clutter Types
In real environment mixture of clutters between BTS and MS, e.g.
small buildings, large buildings, trees, water surfaces…
Path loss given by basic model has to be corrected according
L = L (basic model) + L (clutter correction)
L (clutter correction)
Each clutter of type n gives a correction n in dB / km which has to
be determined by measurements
The total correction is given by the sum over all products n *
dn
dn is the path covered by the clutter of type n
100 m trees
200 m buildings
150 m trees
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Extension to Mixed Clutter Types
Example
Basic model
Large scatter and too optimistic far away from BTS because of too
small k
Mean difference predictions – measurements = 7 dB
Scatter = 15 dB
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Extension to Mixed Clutter Types
Same k, but additionally clutter correction due to buildings and
trees
Much lower scatter and better agreement between predictions and
measurements
Mean difference predictions – measurements = -1 dB
Scatter = 7 dB
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Content: Radio Wave Propagation Modeling
Modeling of buildings and other obstacles
Walfish Ikegami model
Knife edge models
Ray-tracing and ray-launching
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Besides modeling buildings by clutter correction, the following
techniques exist
Walfish Ikegami (Manhattan grid model)
Treat city as regular arrangement of buildings of identical size
and height
Knife edge
Ray-tracing and ray-launching
Estimate loss introduced by buildings by modeling reflection and
diffraction in detail
Modeling of Buildings and Other Obstacles
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Walfish-Ikegami Model
: Mean angle between propagation path and street in °
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Model distinguishes between line of sight (LOS) and non line of
sight (NLOS) situation
LOS
Path loss described by quasi free space propagation with path loss
exponent n = 2.6
NLOS
free space propagation with path loss exponent n = 2.0
multi screen diffraction loss (diffraction from roof top to roof
top)
roof top to street diffraction and scatter loss (diffraction from
last roof top down to MS in the
street)
Walfish-Ikegami Model
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Applicable for configurations with a large obstacle in the
propagation path, i.e.
Obstacle must be far away from transmitter and receiver, i.e.
Obstacle represented by ideal conducting half plane (knife
edge)
Reliable results for obstacles which are thin in comparison to the
distance from transmitter
and receiver (e.g. buildings)
Not applicable for hills or mountains
Path loss introduced by knife edge estimated on basis of Huygens
principle
Sum over all wavelets starting in the half plane above the obstacle
taken into account
phase differences (constructive and destructive interference)
hMS
hBS
d1
h
d2
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Ray tracing
For each point of reception, look for the most important rays by
starting from the transmitters
Unfortunately many transmitted rays are not important
Very accurate methods, but due to the complexity of the algorithms
computer power consuming
Digital maps with a high accuracy (at least 5 m) are required
Ray Tracing and Ray Launching
Ray launching
Send from the transmitters rays into all directions (to all 3D
pixels of the planning area)
Follow each ray and sum over all of them arriving at a certain
point of reception
Rx
Tx
Tx
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Following a ray, several events occur
Quasi free propagation (modeled by power law with path loss
exponent of about 2.5)
Reflection
Each event introduces a loss in dependence on the wavelength,
material and the angle of incidence
L = k0 + k1 + k2 2
reflection
diffraction
Event k0 k1 k2
Reflection 15..20 -1.0..0.5 -0.005..0.010
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Content: Coverage Planning
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Content: Link Budget Calculation
Antenna gain
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Content: Link Budget Calculation
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Link Budget Parameter
Duplexer losses [dB]
Receiver sensitivity [dBm]
Path loss [dB]
Interference margin [dB]
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Before dimensioning the radio network, the link budget for
different environments (indoor, outdoor, in-car) must be
considered
From the link budget, the maximum allowed path loss Lmax can be
derived
Lmax can be used to calculate the cell range R
Body Loss
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Parameter Example value
Antenna gain + 17 dB
Body loss - 0 dB
DL Link Budget – Transmitter Side
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DL Link Budget – Receiver Side + Environment
Parameter Example value
MS sensitivity -104 dBm
Slow fading margin + 12 dB ( = 7 dB, 99 % cell area
probability)
Fast fading margin + 3 dB
Interference margin + 2 dB
Body loss + 3 dB
Frequency hopping gain - 3 dB
Antenna gain - 0 dB
MHA gain - 0 dB
----------------------------------------------------------------
Lmax = effective isotropic radiated power – received isotropic
power
Lmax = 56 dBm - (-69) dBm = 125 dB
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Parameter Example value
Antenna gain + 0 dB
Body loss - 3 dB
UL Link Budget – Transmitter Side
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UL Link Budget – Receiver Side + Environment
Parameter Example value
BTS sensitivity -107 dBm
Slow fading margin + 12 dB ( = 7 dB, 99 % cell area
probability)
Fast fading margin + 3 dB
Interference margin + 2 dB
Body loss + 0 dB
Frequency hopping gain - 3 dB
Antenna gain -17 dB
MHA gain -3 dB
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Lmax = effective isotropic radiated power – received isotropic
power
Lmax = 30 dBm - (-94) dBm = 124 dB
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Link Budget (Power Budget) – Practical Example
with LB-Tool
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Link Budget Parameters on both Sides
Body loss
Typically 3-5 dB in dependence on
- Frequency
Feeder, jumper and connector loss
In case of DL on transmitter side
In case of UL on receiver side
Jumper and connector loss rather low (< 1 dB)
Feeder loss some dB in dependence on
- Frequency
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Receiver Specific Link Budget Parameters
MHA gain
- Feeder loss 3 dB full or even slight overcompensation
- Otherwise partial compensation only
Gain typically 2-4 dB in dependence on
Number of diversity paths
4 paths (space and polarization diversity)
Rx antenna separation (space diversity)
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Content: Link Budget Calculation
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Fast Fading
Rice fading
Raleigh fading
Gain depends on number of carriers over which is hopped
Typically 3-6 dB for hopping over 2-10 carriers
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Rice fading
: received electrical field strength from the dominant signal
: modified Bessel-Function of the first kind and zero order
other noise sources:
other noise sources like man made noise
For the Rice distribution can be approximated by a Gaussian
distribution
Fast Fading
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Rayleigh fading
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Actual amplitude / averaged amplitude in dB
Integrated probability for the actual signal amplitude to be below
a given
fading margin = actual amplitude / average amplitude
for a Rayleigh distribution
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Variation of the local mean signal strength on longer time
scale
Mostly due to shadowing when a mobile moves around (e.g. in a
city)
Variation of the mean receive level usually follows a normal
distribution on log scale log normal fading
The fading can be parameterized by adding a zero mean Gaussian
distributed random variable
= standard deviation (has to be determined by measurements)
= average receive level
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Service probability
Let Pmin be a minimal receive level
What is the probability p that the receive level P (d) at a given
distance d from the BTS is higher than the minimal receive
level
To compute the probability that the receive level exceeds a certain
margin the Gaussian distribution has to be integrated
This leads to the Q function
Slow Fading
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Example
Standard deviation = 10 dB
Slow Fading
Sufficient coverage
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Table for the Q function
Slow Fading
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The standard deviation for the average receive level in a certain
environment follows from measurements
Typical measurement values (outdoor, indoor) are given in the
following table
Slow Fading
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Cell edge probability = probability to have coverage at the border
of the cell
To achieve a certain cell edge probability, the average receive
level must exceed the sensitivity level by a certain margin
To calculate the required margin, the standard deviation must be
multiplied with a factor given in the following table
Slow Fading
Margin = • factor
50 55 60 65 70 75 80 85 90 95 96 97 98 99
0.000 0.126 0.253 0.385 0.524 0.674 0.842 1.036 1.282 1.645 1.751
1.881 2.054 2.326
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Cell area probability = probability to have coverage in the whole
area of a cell with radius R
Can be derived from the cell edge probability by Jake’s formula
which is based on the log distance path loss model
Slow Fading
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Results for cell area probability based on Jake‘s formula
These are independent from the standard deviation
Slow Fading
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Typical cell edge probabilities for
Very good coverage 95%
Very good coverage 99%
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Content: Link Budget Calculation
Antenna gain
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Maximum output power for MS of different power classes
In real networks dominate class 4 MS for GSM 900 and class 1 MS for
GSM 1800
Peak Power at Antenna Connector
Power Class
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Maximum output power per carrier (before combiner input) for macro
cell BTS of different power classes
Usually for GSM 900 the power classes 5-6 and for GSM 1800 the
power classes 1-2 are taken
Peak Power at Antenna Connector
TRX Power Class
GSM 900 BTS
GSM 1800 BTS
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Maximum output power per carrier (after all stages of combining)
for micro cell BTS of different power classes
Peak Power at Antenna Connector
TRX power class
GSM 900 micro-BTS
GSM 1800 micro-BTS
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Related to horizontal and vertical beam width
Narrow beams can be achieved with antenna of large size, especially
at high frequency
The usage of antennas with a specific beam width depends mainly on
the cell type
Omni cells
Seldom realized today for macro cells, but frequently for micro
cells and always for pico cells
No horizontal, but vertical energy concentration only
Small gain of about 5-10 dB in dependence on vertical beam
width
Sector cells
Realized for most macro cells, seldom for micro cells and never for
pico cells
3 sector site
Dominating type
Horizontal half power beam width of about 600-800, considerable
gain of about 13-18 dB
6 sector site
Seldom realized
Horizontal half power beam width of about 300, high gain of about
16-21 dB
Antenna Gain
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Antenna Gain and losses due to feeder/MHA
BSC
BTS
RxLEV PrxTotal = PrxTotal_ANT = Prx_Total_BTS + L_feeder –
G_mha
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Content: Link Budget Calculation
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Minimum signal level at the receiver so that the service can be
offered with the desired QoS
Receiver Sensitivity = Thermal Noise Power + Receiver Noise Figure
+ required S/N
Receiver Sensitivity
Received power
Thermal noise
k Boltzmann constant
B bandwidth (e.g. 200 KHz)
Nth = -121 dBm
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Carrier / noise (S/N) margin
Depends on BER requirements in dependence on service and fading
profile
The reference sensitivity performance is defined by GSM 05.05 for
the GSM 900 (and also the GSM 1800) system for different channel
types and different propagation conditions
Receiver Sensitivity
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The receiver sensitivity levels to be fulfilled on UL and DL are
defined in GSM 05.05
These depend on the power class of the equipment and the cell
type
Receiver Sensitivity
BTS requirements
MS requirements
- DCS 1800 MS class 3 MS -102 dBm
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To achieve coverage in an area, the received signal strength in UL
and DL must exceed the actual receiver sensitivity level
The actual receiver sensitivity level can be higher than the
reference sensitivity level due to interference
Coverage RX_LEV > (actual) receiver sensitivity level
No Coverage RX_LEV < (actual) receiver sensitivity level
Receiver Sensitivity
Received power
Thermal noise
Noise Figure
Required S/N
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S/N Check – Depending on Connection Type
Soft blocking limits
Parameters define the minimum acceptable carrier/noise ratio (S/N)
that must be met for the respective connection type
The different S/N requirements for different type of connection
have an impact on the coverage area probability for different
services
Connection Type
S/N target
14 dB
7 dB
12 dB
For full rate and EFR speech connections, and for circuit switched
data connections up to 9.6 kbit/s.
12 dB
14 dB
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To estimate the impact of an amplifier on the system noise, the
concept of the noise temperature Tnoise is used
Noise temperature is compared with a reference temperature of 290
K
Noise factor = noise temperature / 290°K + 1
The noise figure is the value of the noise factor given in dB
Noise figure = 10 * log (noise factor)
Amplifier Noise
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Tin = noise temperature of input signal
Tnoise = noise temperature of amplifier
G = gain of amplifier
MHA used for compensation of feeder loss
Improves level of received signal, but not S/N (downgrades even
S/N)
Amplifies not only useful input signal, but also its noise
Add own noise, which is amplified as well
Amplifier Noise
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Cascade of amplifiers
G = G1 * G2 total gain
Friis formula
Amplifier Noise
= G1 * G2 * (Tin + Tn1 + Tn2/G1)
= G * (Tin + Tnoise)
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Frequency reuse in the network produces interference
That has to be taken into account especially for the busy
hour
Often overall recommendations are given only, e,g. ETSI suggests a
margin of 3 dB
A more accurate approach is achieved by considering the fractional
load within the network
Fractional load = hardware load / re-use factor
Hardware load = Erlang / number of time slots
Example
Re-use factor = 6
Interference Margin
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The interference margin I needed to compensate the fractional load
follows from the load curve I / dB = -10 log (1 - )
Example
= 0.11
Interference Margin
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Content: Link Budget Calculation
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Link Balance
Coverage range in UL should be the same as in DL, i.e. radio link
should be balanced
Maximum allowed path loss in UL = Maximum allowed path loss in
DL
Due to the low MS power often the UL is the bottleneck, i.e. the
maximum allowed path loss is smaller than on the DL in spite
of
Better BTS receiver sensitivity in comparison to that of the
MS
Receive diversity applied by the BTS
Practically link balance can be verified by checking the carrier /
interference ratio C/I at cell edge
Need C/I on UL = C/I on DL
Received power
Thermal noise
Noise Figure
Required S/N
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Content: Coverage Planning
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Content: Coverage Calculation
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Omni and Sector Cells
Antenna gain
3 sector site gain about 13-18 dB
Difference 8 dB
Lmax (3 sector site) – Lmax (omni cell) 8 dB (both on UL and
DL)
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Macro and Micro Cells
BTS power
Difference 13 dB
BTS receiver sensitivity
Macro cell about -115 dBm (Flexi BTS, 2 Rx diversity)
Micro cell about -106 dBm (Metro site, no Rx diversity)
Difference 9 dB
Lmax (macro cell) – Lmax (micro cell) 13 dB (on DL)
Lmax (macro cell) – Lmax (micro cell) 9 dB (on UL)
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Rural and Urban Cells
Rural cell about 8 dB
Dense urban cell about 13 dB
Difference 5 dB
Building penetration loss
Dense urban cell about 20 dB
Difference 10 dB
Lmax (rural cell) – Lmax (dense urban cell) 15 dB (both on UL and
DL)
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Summary Cell Types
Maximum allowed path losses relative to rural sector macro cell
(type of highest coverage)
Cell type Lmax / dB
Rural sector macro 0
Rural sector micro (very seldom) -13 / -9 (DL / UL)
Rural omni micro (very seldom) -21 / -17 (DL / UL)
Dense urban sector macro -15
Dense urban omni macro (very seldom) -23
Dense urban sector micro -28 / -24 (DL / UL)
Dense urban omni micro -36 / -32 (DL / UL)
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Summary Cell Types
Cell radius relative to rural sector macro cell (type of highest
coverage)
Original Okumura Hata model with previous example values
Clutter correction Rural cell 28.5 dB
Dense urban cell 0 dB
Cell type R / Rrural sector macro
Rural sector macro 1
Rural omni macro 0.593
Dense urban sector macro 0.058
Dense urban omni macro 0.034
Dense urban sector micro 0.025 / 0.032 (DL / UL)
Dense urban omni micro 0.015 / 0.019 (DL / UL)
In dense urban environment macro BTS required to realize even small
cells
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Number
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Summary Cell Types
dBm
-104.0
-102.0
A
TRANSMITTING END:
W
2.0
17.825018762674937
dBm
33.01029995663981
42.51029995663981
K
22.79296875
19.79296875
17.79296875
13.79296875
13.79296875
Cell Range (km):
Cell Range (km):
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Coverage Calculation – Practical Example with LB Tool
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When cell radius is known, the cell area can be calculated
Often traditional hexagon model is considered
R
Omni
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Time Dependent Conditions
Humidity
Due to water absorption, coverage strongly affected by fog and
especially rain
Receive level goes down with increasing distance from the BTS
according exponential law
Absorption coefficient increases when going towards higher
frequency, especially for GSM 1800 often outage during (strong)
rain
Foliation of trees
Affects strongly coverage, again due to water absorption
Has to be taken into account in form of a clutter correction (see
next slide)
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Time Dependent Conditions
(-49 dBm against -81 dBm measured)
Additional clutter trees
(-69 dBm against -81 dBm measured)
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Content: Coverage Planning
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Content: Coverage Planning Tools
Examples for knife edge models
Other Tools
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Content: Coverage Planning Tools
Example for knife edge model
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Reporter
Administrator
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WCDMA
Integrated
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2G and 2.5G Radio Planning
Coverage
Interference
Traffic
Neighbours
Frequencies
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Field Measurement Analysis
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Project Tracking and Site Acquisition
Forms
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Example for COST Hata Prediction
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Example for COST Hata Prediction with knife edge correction
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Content: Coverage Planning Tools
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Example for pure Exponential Model
Receive level / dBm
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Example for Exponential Model with Clutter Correction
Receive level / dBm
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Example for Ray-Launching
Receive level / dBm
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Content: Coverage Planning
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Content: Coverage Measurements
Receive Level Statistics
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Number
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Receive Level Statistics
RxQual value
Example
UL RxLev q0 q1 q2 q3 q4 q5 q6 q7 total
-100 1 0 0 0 1 1 1 2 6
-95 5 1 1 1 1 1 0 1 11
-90 9 1 1 1 1 1 0 1 16
-80 29 1 0 0 0 0 0 1 31
-70 27 0 0 0 0 0 0 0 27
-37 11 0 0 0 0 0 0 0 11
Total 81 3 2 2 3 3 1 5
Low coverage
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Receive Level Statistics
Example
DL RxLev q0 q1 q2 q3 q4 q5 q6 q7 total
-100 1 0 0 0 0 0 1 0 2
-95 2 0 0 0 0 0 0 0 2
-90 6 0 0 0 0 0 0 0 6
-80 28 1 1 1 1 1 0 0 33
-70 24 1 1 1 0 0 0 0 27
-37 26 0 0 0 0 0 0 0 26
Total 87 2 2 2 1 1 1 0
Low coverage
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Drive Tests
Precise location of problems (e.g. coverage holes) possible
Measurement reports used for statistics give distance with
resolution of 550 m only and
not any information about the azimuth
On the other side small region can be examined per time only
Time dependent problems can escape detection
Measurement reports allow to monitor all cells of a BSC area
simultaneously, so that the
interaction of the cells with each other (e.g. interference) can be
evaluated
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Selection of Measurements used for Model Calibration
At cell edge often lack of coverage
Signals suffering strongly from fading dips often not detected any
more
At intermediate distance sometimes lack of coverage
Signals suffering strongly from fading dips sometimes not detected
any more
Close to BTS never lack of coverage
Even signals suffering strongly from fading dips completely
recognized
Not detected
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Selection of Measurements used for Model Calibration
At cell edge
Cannot be used for calibration
At intermediate distance
Close to BTS
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