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8/13/2019 23 RF Invironment and Propagation Model
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CDMA RF Planning Unit 3
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Main Content
The Transmission Loss In RF Environment
Why There Is Loss?
How To Predict Loss----Propagation Models
Propagation Models Calibration
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Some Key Points In
Coverage Planning
The major considerations are:• Coverage - distribute RF energy over a
given area
• Quality - keep FER manageable even if
power is sufficient• Capacity - be able to support all offered
traffic
• Control - Prevent unwanted pollution andcontrol amount of Soft Handoff
Interference & power management!
All this need good quality of radio signal!
But radio environment is very serious, radio signal is
easy to be affected!
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Fading Phenomena
Large scale fading (slow-fading):• occurs over distances of 100‟s – 1000‟s m
• observed as an average signal power attenuation
(path loss vs. distance)
• signal power losses of 20 to 40 dB/decade or
6dB to 12dB/Octave (Path Loss Exponent 2 to
4)
• caused by spreading loss, log-normal shadowing• characterized by various propagation models.
(Refer to the “Propagation models” section for
further details.)
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Fading Relationship
• 20dB/Decade = 1/r 2 = 20LOG D1/D2
— 20LOG 1/10 = -20dB
— 20LOG 1/20 = -26dB
• 30dB/Decade = 1/r 3 = 30LOG D1/D2
— 30LOG 1/10 = -30dB
— 30LOG 1/20 = -39dB
• 40dB/Decade = 1/r 4 = 40LOG D1/D2
— 40LOG 1/10 = -40dB
— 40LOG 1/20 = -52dB
Useful when the Power Level at
one location is known
6dB
9dB
12dB
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Fading Phenomena
Student Exercise
Use graph paper to compare the decay of signal level in dBm at the following
distances, given the signal level of -40 dBm at 1 mile from the source, using
20dB, 30dB and 40dB per decade
110
100 1000
Distance in miles
-40
-50
-60
-70
-80
-90
-100
-110
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Fading Phenomena (Con.)
Small scale fading (fast-fading):
• occurs over distances on the order of thewavelength of EM wave
• can experience instantaneous fades oftypically 10 to 30 dB
• characterized by statistical distributions such as Rayleigh or Rician
It may not be obvious at this point, but you can‟tfix these problems with “more power.” Whynot?
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Main Content
The Transmission Loss In RF Environment
Why There Is Loss?
How To Predict Loss----Propagation Models
Propagation Models Calibration
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Propagation Physics
Four basic mechanisms:
• spreading loss (free-space)
• reflection
• diffraction
• scattering
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Propagation Mechanisms
Spreading Loss
A B C D
Spherical Wave front
propagating away from source
Pwr @ A (Reference)
Pwr @ B < A
Pwr @ C < B
Pwr @ D < C
Spreading Loss
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Non Line-of-sight Propagation
• Non-LOS propagation is a very important
property in wireless communications.
• It allows the signal to reach many areas not
directly covered by LOS
-20 dBm
-30 dBm
-40 dBm
-50 dBm
-60 dBm
-70 dBm
-80 dBm
-90 dBm
-100 dBm
-110 dBm
-120 dBm
Signal
Level
Legend
Area View
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Application to Mobile Environment
How can we apply an understanding of
this phenomena to the wireless
environment?
Consider some relatively simple cases:
• Free-space propagation
• 2-ray reflection
• Knife-edge diffraction
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Free-space Propagation
When does free-space apply? – When there is only one signal path (no reflections) and,
– the path is unobstructed.
• Technically speaking, the first Fresnel zone is not penetrated
by obstacles.1stFr esnelzoneBAdD
1stFr esnelzoneBAdD
d = 0.5 . ( . D)
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2-ray Reflection
Consider two incoming rays:
• one is direct, the other reflected (almost 180o)
• partial cancellation
• signal decay twice that of free space
Heights Exaggeratedfor Clarity
HB
Hm
D
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Knife-edge Diffraction
• A single well-defined obstruction blocks the path
• Can estimate the effects of individual obstructions,
and extend to multiple
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Real-world Propagation
• Complex RF propagation situations that are verydifficult to quantify
• Each case always includes the unique effects of
combining different mechanisms
• The situations that affect us most in the cellularenvironment are:
– multipath propagation
– RF clutter, shadowing, diffraction – building and vehicle penetration
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Real-world Propagation
Propagation Building Blocks
Spreading Loss
Reflection
Diffraction
Scattering and
AbsorptionAbsorption
Losses
This is why we need
empirical-based Models
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Multipath
• Generalization of the two-ray reflection mechanism.
• Dozens or even hundreds of signal components arrive at
random amplitudes and phases, not just a simple phase
inversion.
• This is a fast fading mechanism
– deep fades, sometimes as much as three or four orders
of magnitude
– occur over distances a fraction of a wavelength.
• Referred to as Rayleigh or Rician fading
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Multipath (Rayleigh fading)
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Multipath (Rayleigh fading)
Student Exercise
1. Given that multipath fades occur at a /2 separation, calculate the
distance between fades at Freq = 800MHz and Freq = 1900 MHz. For
your convenience, use metric or English units.
Remember, v = freq(Hz) x
v = 300,000,000 m/s or 186,409 miles/s
( will be in whatever velocity unit you use)
2. At 800 MHz, if you are driving at 30 MPH (or 48 KPH), how much
time does it take to move from one fade to another?
3. Given that CDMA power control of the Mobile can be made 800 times
a second; how many power control adjustments can be made
between fades?
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RF clutter/Shadowing
• Slow variations in path loss due to large objects and
terrain features.
• Variation is described by a log-normal distribution.
– It is the result of forward scattering over a
number of objects, leading to a random
variation of the signal.
• We will address this phenomena, and make some
calculations, in the link budget section. Being alarge-scale phenomena, it is accounted for by
adding a fade margin in the link budget.
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Building & Vehicle Penetration
• To make sure sufficient signal strength reachesthe mobile, we need to account for the loss
incurred in penetrating these objects.
• We want to know the average power that is lost
for the signal to penetrate the object.
• Predicting signal levels in buildings is complex.
A building is a detailed collection of obstructions
and absorbing elements.
• Again, we will look at this further in the link
budget calculations.
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Signal Decay Rates
•Free-space – 20 dB per decade of distance
– 6 dB per octave of distance
• Reflection cancellation – 40 dB per decade of distance
– 12 dB per octave of distance
• Real-life wireless propagation – decay rates fall typically between 30 and 40 dB per
decade of distance, although 20 dB is common problem in CDMA systems
This is an important consideration in system planning.
Why?
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Main Content
The Transmission Loss In RF Environment
Why There Is Loss?
How To Predict Loss----Propagation Models
Propagation Models Calibration
S di L D t
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Spreading Loss Due to
Spherical Wavefront
4pR 2
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Free-space Propagation
• Free-space propagation serves as a reference point for just about all path loss models.
• Propagation loss is a function of Tx-Rx
separation distance and carrier frequency:
L free-space (dB) = 32.44 + 20 Log f + 20 Log d
where
f = carrier frequency, in MHz
d = separation distance, in km
or ( 36.5 + 20 Log f + 20 Log d miles )
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Free-space Propagation
Student Exercise
A 1900MHz BTS is transmitting a signal power of 2.4 watts out of a 0dBi gain
antenna. A transmission path across a large body of water experiences
properties close to free-space attenuation.
1. Using the given formula, calculate the receive signal level of the
transmission at a distance of 10 kilometers or 6 miles. Give the result
in dBm.
2. What would the receive signal be if the path loss exponent increasedfrom 2 (20Logd) to 3.5 (35Logd) and would the signal be seen by a receiver
with a -104dBm sensitivity?
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Propagation Models
• An important objective is to predict the
actual path loss experienced by the
communications link.
• There are no theoretical models that
capture all of the variations experienced inthe field.
• We can however, try to reproduce major
trends, and apply these „models‟ to
consistent environments.
“There is
noth in g as
practi cal as a
good theory”
L. Bol tzmann
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Why Propagation Models?
• Using the physics of propagation, even our bestcalculations can’t give us all the answers we need
• We can’t compute every reflected path and every
obstruction
• We even want general answers without knowing
specific paths
• We make measurements
But we can’t measure every location we want
• So, we must take measurements and use both
physics and statistics to reach general conclusions
• We formalize our calculation processes and call
them models
Stat ist ics c an help us ef fect ively extend what we
know f rom phys ics, and w hat we see in
measurements, to predict the sig nal levels in places
we canno t measure.
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Area Models - Okumura’s model
• Not really a “model,” as much as a set of curves.Corrections to free-space.
• Describes the attenuation and variation of fieldstrength, for varied terrain.
• Systematic accounting of terrain irregularitiesand environmental clutter :
– Quasi-smooth terrain
– Irregular terrain
– Open area
– Suburban area
– Urban area
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Okumura (prediction curves)
FromOkumura et.al., 1968
Remember, this is additional
loss to the free-space ‘model’
Urban Area
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Okumura (prediction curves)
Student Exercise
1. Use the given Okumura nomograph to predict the signal level from a
1900MHz (use 2000MHz) BTS that is transmitting an EIRP of +50 dBm,
at 3 km and 30 kms, assuming the given BTS and MS antenna heights in
an urban environment.
2. Roughly, how many dB/decade is this slope or decay?
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Okumura (prediction curves)
Okumura Area Model
You still have to
look up the additional
attenuation value in the
tables
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What Is Good Model?
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Area Models - Hata
• Empirical model derived from Okumura‟soriginal report.
• The Hata model captures the graphical pathloss information from Okumura into a setof equations.
• Range of applicability:
– frequency - 150 to 1,500 MHz
– base station antenna height - 30 to 200 m – mobile antenna height - 1 to 10 m
– separation distance - 1 to 20 km
– terrain is semi-smooth
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Area Models - HataFinally, something
we can use in Excel!
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COST-231 model is developed by European COoperative for Scientific and TechnicalResearch committee
COST-231 model extends the Hata model to 2 GHz frequency band
COST-231 model is applicable for frequency range 1500-2000 MHz, distances
1-20 km, BS antenna heights 30-200 m, MS antenna heights 1-10 m
Parameters and variables are:
f is carrier frequency, in MHz
hb and hm are BS and MS antenna heights, in m
d is BS and MS separation, in km
A(hm) is MS antenna height correction factor (same as in Hata model)
Cm is city size correction factor: Cm=0 dB for suburbs and Cm=3 dB for metropolitancenters
Area Models - COST 231 HATA
Area Models –
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Area Models –
COST 231 Walfish-Ikegami
• Developed by the European researchcommittee COST 231
• Estimates path loss in an urban
environment, for microcells (< 1 km).• COST 231 model has three basic
components: – free space loss (L fs)
– roof-to-street diffraction and scatter loss(L rts)
COST 231 Walfish Ikegami
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COST 231 Walfish-Ikegami
(applicability)
• Confined to RF paths in urban areas
within the following ranges of validity:
– frequency (f c) - 800MHz to 2000MHz
– base station antenna height (h b) - 4m to 50m
– mobile antenna height (h m) - 1m to 3m
– separation distance (d) - 0.02km (20 meters)to 5km
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COST 231 (geometry)
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Area Models - Walfisch-Betroni / Walfisch-Ikegami Models
Ordinary Okumura-type models do work in this environment, but the
Walfisch models attempt to improve accuracy by exploiting the actual
propagation mechanisms involved
Path Loss = LFS + LRT + LMS
LFS = free space path loss (Friis formula)LRT = rooftop diffraction loss
LMS = multiscreen reflection loss
Propagation in built-up portions of cities is dominated by ray diffraction
over the tops of buildings and by ray “channeling” through multiple
reflections down the street canyons
The Walfisch-Betroni model is being considered by the ITU-R (International
Telecommunications Union) for deployment in the upcoming IMT-2000
(International Mobile Telecommunications 2000) standard which will
integrate paging, cordless, cellular, and LEO wireless telephone systems.
COST 231 Walfish-Ikegami
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Main Content
The transmission loss in RF environment
Why there is loss?
How to predict loss----Propagation Models
Propagation Models Calibration
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Calibration of Propagation Models
• Drive Tests
–
Field testing CW Measurements
CW
Receiver
PC
GPS
Receiver
CW TestTransmitter
Test Antenna
CalibratedEIRP
Test RX Antenna
We just do test, theCalibration will be
Finished by computer.
Comparison of Field Measured Data and
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Comparison of Field Measured Data and
Propagation Model
-40
-110
-100
-90
-80
-70
-60
-50
0 4 8 12 16 20 24 28 32
Distance from Cell Site, kmmeasured signal
Okumura-Hata model
This would be nice,for every radial fromthe site; but isimpractical!
Prediction Results
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Prediction Results
with Propagation Model
site
-100dBm or less
-90 to -99 dBm
-80 to -89 dBm
-70 to -79 dBm
-69dBm or more
Prediction Signal Levels
Selected (available)
Roads for Drive Testing
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Drive Test Results
site
-100dBm or less
-90 to -99 dBm
-80 to -89 dBm
-70 to -79 dBm
-69dBm or more
Drive Test Signal Levels
Prediction and Drive Test
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Prediction and Drive Test
Results Comparison
sitesite
-100dBm or less
-90 to -99 dBm
-80 to -89 dBm
-70 to -79 dBm
-69dBm or more
Drive Test Signal Levels
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Model Optimization
– What can we change? Well, not the Measured Data!For that particular environment it’s REAL. We needto improve the chosen model so that it can be appliedmore widely
• We can change the type of Model• Okumura-HATA
• COST231
• Walfisch-Ikegami
• etc
• Within the model, change the K Factors
• Massage the General Model to better fit Measured Data
Calibration of Propagation Models
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10 milesEIRP = +30 dBm
Model : Use Free Space
36.5 + 20Log(F) + 20Log(D)
F in MHz, D in Miles
• Example of model test and optimization
Calibration of Propagation Models
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• Example of Model Optimization
Model Free Space 36.5+20LOG(F)+20LOG(D)
Freq 1900 MHz
EIRP 30 dBm
D(miles) Ploss(dB) RX Level(dBm)
1 102.08 -72.08
2 108.10 -78.10
3 111.62 -81.62
4 114.12 -84.125 116.05 -86.05
6 117.64 -87.64
7 118.98 -88.98
8 120.14 -90.14
9 121.16 -91.16
10 122.08 -92.08
-120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
1 2 3 4 5 6 7 8 9 10
D(miles)
RX Level(dBm)
Calibration of Propagation Models
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• Example of Model Optimization
– Drive Test Data Points
EIRP = +30 dBm 1 2 4 5 8 10
Drive TestRoutes
Calibration of Propagation Models
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• Prediction and Drive Test Data Points
Model Free Space 36.5+20LOG(F)+20LOG(D)
Freq 1900 MHz
EIRP 30 dBm
D(miles) Ploss(dB) RX Level(dBm)
1 102.08 -72.08
2 108.10 -78.10
3 111.62 -81.62
4 114.12 -84.125 116.05 -86.05
6 117.64 -87.64
7 118.98 -88.98
8 120.14 -90.14
9 121.16 -91.16
10 122.08 -92.08
-120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
1 2 3 4 5 6 7 8 9 10
D(miles)
RX Level(dBm)
Calibration of Propagation Models
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Model 56.5+20LOG(F)+20LOG(D)
Freq 1900 MHz
EIRP 30 dBm
D(miles) Ploss(dB) RX Level(dBm)
1 122.08 -92.08
2 128.10 -98.10
3 131.62 -101.62
4 134.12 -104.12
5 136.05 -106.05
6 137.64 -107.64
7 138.98 -108.98
8 140.14 -110.14
9 141.16 -111.16
10 142.08 -112.08
-120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
1 2 3 4 5 6 7 8 9 10
D(miles)
RX Level(dBm)
Factor Increasedby +20
Predicted Signal Levelfrom Modified Model
• Prediction Modified
Calibration of Propagation Models
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• Prediction ModifiedModel 56.5+20LOG(F)+30LOG(D)
Freq 1900 MHz
EIRP 30 dBm
D(miles) Ploss(dB) RX Level(dBm)
1 122.08 -92.08
2 131.11 -101.11
3 136.39 -106.39
4 140.14 -110.14
5 143.04 -113.04
6 145.42 -115.42
7 147.43 -117.43
8 149.17 -119.17
9 150.70 -120.70
10 152.08 -122.08
-120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
1 2 3 4 5 6 7 8 9 10
D(miles)
RX Level(dBm)
Factor Increasedby 10
Calibration of Propagation Models
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Model 40+20LOG(F)+33LOG(D)
Freq 1900 MHzEIRP 30 dBm
D(miles) Ploss(dB) RX Level(dBm)
1 105.58 -75.58
2 115.51 -85.51
3 121.32 -91.32
4 125.44 -95.44
5 128.64 -98.64
6 131.25 -101.25
7 133.46 -103.46
8 135.38 -105.38
9 137.07 -107.07
10 138.58 -108.58
-120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
1 2 3 4 5 6 7 8 9 10
D(miles)
RX Level(dBm)
Calibration of Propagation Models
Now it’s OK
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