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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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ï
î
ï
í
ì
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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ï
î
ï
í
ì
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
----------------------------------------------------------------
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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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)
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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Time Dependent Conditions
(-49 dBm against -81 dBm measured)
Additional clutter trees
(-69 dBm against -81 dBm measured)
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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Content: Coverage Planning
For public use – IPR applies
Content: Coverage Planning Tools
Examples for knife edge models
Other Tools
For public use – IPR applies
Content: Coverage Planning Tools
Example for knife edge model
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
For public use – IPR applies
Reporter
Administrator
For public use – IPR applies
WCDMA
Integrated
For public use – IPR applies
2G and 2.5G Radio Planning
Coverage
Interference
Traffic
Neighbours
Frequencies
For public use – IPR applies
Field Measurement Analysis
For public use – IPR applies
Project Tracking and Site Acquisition
Forms
For public use – IPR applies
Example for COST Hata Prediction
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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Example for COST Hata Prediction with knife edge correction
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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Content: Coverage Planning Tools
For public use – IPR applies
Example for pure Exponential Model
Receive level / dBm
For public use – IPR applies
Example for Exponential Model with Clutter Correction
Receive level / dBm
For public use – IPR applies
Example for Ray-Launching
Receive level / dBm
For public use – IPR applies
Content: Coverage Planning
For public use – IPR applies
Content: Coverage Measurements
Receive Level Statistics
* © Nokia Siemens Networks Presentation / Author / Date / Document 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
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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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
For public use – IPR applies
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
* © Nokia Siemens Networks Presentation / Author / Date / Document Number
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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
For public use – IPR applies
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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