23 RF Invironment and Propagation Model

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CDMA RF Planning Unit 3




Main Content

The Transmission Loss In RF Environment

Why There Is Loss?

How To Predict Loss----Propagation Models

Propagation Models Calibration




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!




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.)




Fading Relationship

• 20dB/Decade = 1/r 2 = 20LOG D1/D2

— 20LOG 1/10 = -20dB

— 20LOG 1/20 = -26dB


— 30LOG 1/10 = -30dB

— 30LOG 1/20 = -39dB


— 40LOG 1/10 = -40dB

— 40LOG 1/20 = -52dB

Useful when the Power Level at

one location is known

6dB

9dB

12dB






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




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?




Main Content


Why There Is Loss?






Propagation Physics

Four basic mechanisms:

• spreading loss (free-space)

• reflection

• diffraction

• scattering




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




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




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




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)




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




Knife-edge Diffraction

• A single well-defined obstruction blocks the path

• Can estimate the effects of individual obstructions,

and extend to multiple




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




Real-world Propagation

Propagation Building Blocks

Spreading Loss

Reflection

Diffraction

Scattering and

AbsorptionAbsorption

Losses

This is why we need

empirical-based Models




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




Multipath (Rayleigh fading)




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?




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.




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.




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?




Main Content


Why There Is Loss?



S di L D t




Spreading Loss Due to

Spherical Wavefront

4pR 2





• 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 )





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?




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




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.




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




Okumura (prediction curves)

FromOkumura et.al., 1968

Remember, this is additional

loss to the free-space ‘model’

Urban Area





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?





Okumura Area Model

You still have to

look up the additional

attenuation value in the

tables




What Is Good Model?




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




Area Models - HataFinally, something

we can use in Excel!




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 –




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





(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




COST 231 (geometry)




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.





Main Content

The transmission loss in RF environment

Why there is loss?

How to predict loss----Propagation Models





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




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




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




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




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




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





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





• 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)





• Example of Model Optimization

– Drive Test Data Points

EIRP = +30 dBm 1 2 4 5 8 10

Drive TestRoutes





• Prediction and Drive Test Data Points

Model Free Space 36.5+20LOG(F)+20LOG(D)

Freq 1900 MHz

EIRP 30 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)





Model 56.5+20LOG(F)+20LOG(D)

Freq 1900 MHz

EIRP 30 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





• Prediction ModifiedModel 56.5+20LOG(F)+30LOG(D)

Freq 1900 MHz

EIRP 30 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





Model 40+20LOG(F)+33LOG(D)

Freq 1900 MHzEIRP 30 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)


Now it’s OK



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23 RF Invironment and Propagation Model