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CDMA NETWORK PLAN AND OPTIMIZE
Propagation Analysis
Link Budget
Transmitter Power
+44
+22
Feedline Loss
-3
Antenna Gain
+12
0
Various Allowances
-15
-14
0
More Allowances
-8
-8
Traffic Factors
+20
0
Antenna Gain
0
+12
Feedline Loss
0
-3
Receiver Sensitivity
-116
-121
Link Budget
135.4
140.2
Cell Planning
Traffic Estimation
Antenna Selection
and Application
Land Use
Databases
Schedule
CDMA NETWORK PLAN AND OPTIMIZE
• RF Propagation
– underlying mechanisms
– modeling and prediction
• Antenna Principles and Applications
– basic physics and operation
– application issues
– commercial products
• Traffic Engineering
– dimensioning
– backhaul and NETWORKworking considerations
• Technology-Specific Subjects
– Application principles, rules, limits, guidelines
– Hardware Architecture and Capabilities
CDMA NETWORK PLAN AND OPTIMIZE
-40
-50
-60
-70
RSSI,
dBm -80
-90
,
dB
-100
-110
0
4
8
12 16 20 24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
CDMA NETWORK PLAN AND OPTIMIZE
 Section A: Propagation Basics
• Radio Links: Types, key elements, configurations
• Frequency and Wavelength; the RF spectrum
 Section B: Overview of Propagation Mechanisms
• Free-Space, Reflection/Cancellation, Knife-Edge Diffraction
• Additional modes and real-life complications, multipath
• Techniques for combating multipath fading
 Section C: Propagation Models
• Okumura-Hata, COST-231, Walfisch Ikegami
• Confidence factors and statistical distribution
• Link Budgets
 Section D: Overview of Measurement Tools &
Methods
 Section E: Overview of Propagation Prediction Tools
CDMA NETWORK PLAN AND OPTIMIZE
Section A Objectives
•
•
•
•
•
Recognize the basic principles of RF propagation
Identify key elements in radio links
Recognize the possible configurations for radio links
Understand the role of frequency in propagation
Remember the wavelength of the signals of your own
communications system
• Mathematic tools
• Total considerations
Propagation:
Basic Elements of a Radio Link
Antenna 1
Transmission
Line
Information
Transmitter
Antenna 2
ElectromagNET
WORKic
Fields
Transmission
Line
Receiver
current
Propagation
Information
current
• Propagation is the science of how radio signals travel (propagate from
one transmitting antenna to another receiving antenna
• Propagation is an unavoidable part of every radio link
• To successfully design just one radio link, or a whole wireless system, one
must understand how propagation occurs
– basic mechanics of the propagation process
– appropriate models/techniques for propagation prediction
– characteristics of the other components of the overall radio link
Elements and Parameters of a
Radio Link
Transmitter
Trans.
Line
Antenna




power output
modulation type
spectral density
coding, if any
•
 line loss
 gain, bandwidth
 beamwidth
 polarization
•
 path loss
Antenna
Trans.
Line
Receiver
 gain, bandwidth
 beamwidth
 polarization
 line loss





sensitivity
selectivity
spreading gain
coding gain
dynamic range
•
Transmitter
– Generates RF energy on a desired
frequency
– Modulates the RF energy to convey
information
Antennas
– Convert RF energy into
electromagnetic fields, vice versa
– Focus the energy into desired
directions (gain)
Receiver
– filters out and ignores signals on
undesired frequencies
– Amplifies the weak received signal
sufficiently to allow processing
– De-modulates the signal to recover
the information
Radio Link Configurations
for useful communications
• Simplex
– Uses only one channel in broadcasting mode
– Only one talker speaks; listener can not interrupt
– Example: AM, FM broadcasting
• Half Duplex
– One channel, Bi-directional, but one-way-at-a-time
– Only one talker speaks at a time; can not be interrupted
– Example: CB, Land Mobile Radio
• Duplex
– Two channels are used
– Both talkers can speak anytime & interrupt
– Requires two totally independent links
– Examples: Telephone, Cellular, PCS
The Role of Frequency in Propagation
Frequency = number of cycles
in one second
•
•
1 second
/2
The Frequency of a Radio signal
determines many of its propagation
characteristics
– units: 1 Hertz = 1 cycle per second
Frequency and wavelength are inversely
related.
– antenna elements are typically in the
order of 1/4 to 1/2 wavelength in size
– objects bigger than roughly a
wavelength can reflect or obstruct RF
energy
– RF energy can penetrate into an
enclosure (building, vehicle, etc..) if it
has holes or apertures roughly a
wavelength in size, or larger
The Relationship between
Frequency and Wavelength
F total
waves
3x108 M
1 second
Cell

Examples:
AMPS cell site
speed
=C
f = 870 mHz.
 0.345 m = 13.6 inches
PCS-1900 site
f = 1960 mHz.
 0.153 m = 6.0 inches
• Radio signals travel through empty space
at the speed of light (C)
– C = 186,000 miles/second
(300,000,000 meters/second)
• Frequency (F) is the number of waves
per second (unit: Hertz)
• Wavelength  (length of one wave) is
calculated:
– (distance traveled in one second)
/(waves in one second)
C / F
The Radio Spectrum: Frequencies
used by various Radio Systems
1000
500
300
150
AM
0.3
100
0.4
0.5
75
0.6
50
LORAN
0.7 0.8 0.9 1.0
40
100 Meters
1.2
30
Marine
1.4 1.6 1.8 2.0
2.4
20
15
10 Meters
Short Wave -- International Broadcast -- Amateur
3
4
5
10
40
9
VHF TV 2-6
0.4
0.1
60
70
80 90 100
UHF TV 14-69
0.5
0/6
12
5
Broadcasting
7
8
9
14 16 18 20 22 24 26 28 30 MHz
30,000,000 i.e., 3x107 Hz
2
120 140 160 180 200
240
300 MHz
300,000,000 i.e., 3x108 Hz
0.3
0.2
GPS
10
1 Meter
VHF VHF TV 7-13
1.2
0.03
6
CB
<Cellular
0.7 0.8 0.9 1.0
0.06
4
10
FM
0.6
UHF
3
8
3
50
1
0.3
7
6
VHF LOW Band
30
6
3.0 MHz
3,000,000 i.e., 3x106 Hz
0.1 Meter
DCS,PCS
1.4 1.6 1.8 2.0
2.4
3.0 GHz
3,000,000,000 i.e., 3x109 Hz
0.02
12
0.15
0.015
0.01 Meter
14 16 18 20 22 24 26 28 30 GHz
30,000,000,000 i.e., 3x1010 Hz
Land-Mobile
Aeronautical Mobile Telephony
Terrestrial Microwave Satellite
Mathematics concept review
 Understand basic terms of the probability theory
 Understand and apply the Poisson, Log-Normal, Gaussian and
Rayleigh signal statistical distributions
 Understand concept and application of decibel unit
 Determine the relationship between dB, dBm, and dBuv
 Apply the logarithm and exponent functions to RF path calculations
 Understand and apply the slope and intercept parameters
 Understand the concept and the use of polar coordinates for plotting
antenna radiation patterns
Exponential and Logarithm Functions
y
10^x
2^x
log2 a
lg a
a
x
Exponential Functions
•
•
•
•
Logarirthm Functions
Exponential and logarithm functions play important role in RF coverage and interference
prediction and modeling
Exponential function has the form of a = b^x and is said to have base b as a positive value
Three base values are more often used in system engineering: b = 2, b = 10, and b = e (e is
an irrational number between 2.71 and 2.72)
Because math concentrates on base e, the function e^x is often referred to as the
exponential function written exp x
Exponential and Logarithm Functions, continued
•
•
•
Logarithm function is inversed to exponential function and has the forms:
– x = logb a for any b
– x = lg a
for b = 10 (decimal logarithm)
– x = ln a
for b=e (natural logarithm)
Basic laws of logarithms:
– log (a x c) = log a + log c
– log (a / c) = log a - log c
– log (1 / a) = - log a
– log a^n = n x log a
Basic properties of logarithms:
– logb 1 = 0, lg 1 = 0, ln 1 = 0
– logb b = 1, lg 10 = 1, ln e = 1
– logb a is defined only for a > 0 and doesn,t make sense if a < = 0
– logb a is negative if 0 < a < 1 and positive if a > 1
Concepts of Slope, Intercept, and Line
y
Intercept Points
Positive Slope Line
x1,y1
Negative Slope Line
b
A
a
x2,y2
x
A
Zero Slope Line
No Slope Line
• The slope and intercept are basic characteristics used for RF path loss modeling
• The slope of straight line in orthogonal coordinates is defined as:
Slope = (y2 - y1) / (x2 - x1) = tg A
Concepts of Slope, Intercept, and Line, continued
•
•
•
•
•
A line with positive slope rises to the right, a line with negative slope falls to the left
Horizontal line has slope 0 , vertical line has no slope
Angle A that a line makes with the horizontal is called an angle of inclination
Intercept is referred to the point at which a line crosses either x-axis (denoted a) or yaxis (denoted b)
The straight line equation with slope m and intercept b is as follows
Y=mxX+b
•
RF Engineering Example.
– Path loss in suburban cell is presented by 1-mile intercept of - 60 dBm and slope of 38 dB/decade. Calculate Receive Signal Strength at 10 mile distance
– Solution.
RSS[dBm} = - 60 dBm + ( -38 dB/decade ) = - 98 dBm
Polar Coordinates Concept
M
rm
Am
An
rn
N
Polar Graph
•
•
•
•
In RF engineering, the polar coordinates(zuobiao) are used for plotting of antenna
radiation patterns
Polar coordinate system locates points using two coordinates named radius r (always
positive) and angle A
Positive A represents counterclockwise rotation while a negative A represents
clockwise rotation
Polar coordinate graph paper contains a collection of circles and rays with different r
Concept of Probability
•
•
•
•
•
Probabilities are numbers assigned to events satisfying the following rules:
– Each outcome is assigned a positive number such that the sum of all n probabilities
is 1
– If P(A) denotes the probability of event A, then P (A) = sum of the probabilities of
the outcomes in the event A
The probability of sure event is 1. The probability of impossible event is 0. The converses
are not necessarily true.
Probabilities of other events are always between 0 and 1
Inclusive OR rule for two events A and B:
P (A or
B) = P (A) +P (B) - P (A and B)
Independent events are unrelated that is one of the events does not affect the likelihood of
the other
P (A and B) = P (A) x
P (B)
The Poisson Distribution
e^()^k
PXk 
k!





•
•
•
•
•
•





k - is a variable number of successes (k = 0,1,2,...); lambda- is an average
Poisson distribution is an approximate of binomial distribution
Poisson distribution has only one parameter- lambda.
Discrete random variable is generally meant as a numerical result of an experiment. In
radio mobile communications, a sample of receive signal strength (RSS) may be
considered as continuos random variable with a certain probability density.
Expectation or Mean is defined as weighted average of random values, where each value
x is weighted by probability of its occurrence P(x)
– E(X) = SUM [(x) x P(x)]
If a random variable X follows the Poisson distribution, then
– E(X) = lambda
Variance and Standard Deviation
• An average value of RSS across cell site does not tell much about RF coverage
in any particular cell site spot.
• The Variance is used to measure the RSS spread around the average RSS
• Variance of a random variable X is defined as
Var X = E [(x - u)^2],
where u - is the mean
• If Var X is large, then it is likely that x will be far from the mean
• Standard deviation Sigma is widely used in RF coverage and interference
prediction
• The standard deviation of random variable X is defined as
Sigma = SQR ( Var X )
or Var X = (Sigma)^2
Probability Density and Distribution Functions - Concepts
Probability density function f(x)
a
b
P(a<=x<=b)
f(x)
F(x) area
x
x-axis
 RF coverage and interference may appear to
be random and unpredictable in nature. Since
there are many variables involved, several
average properties are used
 The probability density and distribution
functions become useful for RF engineers
 Most often used statistical distributions are:
Binomial, Poisson, Gaussian, Log-Normal,
Rayleigh and Ricean
 Cumulative distribution functions (cdf)
specifically important because they allow RF
engineer to predict probability that RSS will be
below or above a specified level.
 This is used for setting RSS thresholds and
determining the quality of service and extent of
coverage within a cellular system.
Probability Density and Distribution Functions Concepts, continued
•
•
Probability density is applied to continuous random variables, such as time, distance, and
signal strength (RSS)
If X is a continuous random variable, the probability density function f(x) on interval
a,b is defined by formula
b
P (a< = x < = b) = af (x) x dx
•
•
Every random variable has a cumulative distribution function (cdf) which gives the
amount of probability that has been accumulated so far
The probability density function f(x) and cumulative distribution function F(x) are
related by formula
x
F (x) = P (X< = x) =
•
f (x) x dx
For continuous random variables, F(x) is non-decreasing and no-jump function because
it collects cumulative probability starting from 0 and rising to a height of 1
The Normal or Gaussian Distribution
Smaller Sigma
• The normal distribution has a density function
defined by formula
Mean
Larger Sigma
• Special case of normal distribution with u=0
and (sigma)^2 = 1 is called standard normal
distribution
Mean
Standard normal
distribution
-3 -2 -1
(x)^2
f(x)
exp
 2
2^2
1
1
2
3
Confidence Interval and Confidence Level
f(x)
Bell-shaped•pdfValues
•
Area=
F(x1)
•
x1
x
x2
of RSS at any distance over RF path are concentrated
close to the mean and have bell-shaped distribution
The confidence interval may be meant as a prespecified
RSS range in dB within which the signal strength
measurements fall
For standard normal distribution, the confidence interval is
defined as
RSS - k x (sigma) < = RSS < = RSS +k x (sigma)
RSS - is any measurement reading
K- is a positive number between 0 and 2
RSS- is a local mean of the received signal strength
F(x)
1
•
cdf
•
F(x1)
x1
x
Confidence level indicates the degree of awareness, that the
predicted RSS will fall in confidence interval
Confidence interval and confidence level are coupled with
the local mean m by the following expression
P(mxm)
m

m
(xm)^2
exp
d
 2
2^2
1
Mobile Signal Strength - Log-Normal and Rayleigh
Distributions
Signal strength, dBm
m(t)- local mean
r(t)
Mobile signal fading
•
•
Time
A mobile radio signal r(t) can be presented by two components as
m (t) x r0 (t)
The component m(t) varies due to terrain elevation and has different names
– local mean or
– long-term fading or
– long-normal fading
r (t) =
Mobile Signal Strength - Long-Normal and Rayleigh
Distribution, continued
•
•
•
•
•
The component r0(t) varies due to wave reflection
from buildings and has also different names
– multipath fading or
– short-term fading or
– Rayleigh fading
The time interval for averaging r(t) has been
determined as 20 to 40 wavelengths
Using 36 to 50 samples per interval of 40 wavelengths
is a good rule for obtaining the local means
The component m(t) follows a log-normal distribution
due to the affect of terrain contour
The component r0(t) follows Rayleigh distribution
because of prevalence of reflected waves over direct
waves in urban mobile environment
Mobile Signal Strength - Log-Normal and Rayleigh
Distributions, continued
• Log-normal distribution means normal distribution in dB units
• Log-normal distribution (or shadowing) implies that measured signals in dB at
specified TX-RX separation have a Gaussian distribution about the variable
distant-dependant mean
• Another implication is that the standard deviation sigma of Gaussian distribution
should also be expressed in dB units
• Multipath propagation produces signals with different amplitudes and phases
which arrive at MS. The resulting signals follow the Rayleigh distribution
• The Rayleigh probability density function (pdf) is defined as follows
p(r) 



 





r exp
r^2 


^2

2x^2 
0
r - signal strength (RSS)
 - standard deviation
if r  o
if r< 0
where
Mobile Signal Strength - Log-Normal and Rayleigh
Distributions, continued
•
The Rayleigh distribution function (cdf) is defined as follows
R^2 

2^2 
R- specified level of RSS




P(r  R) 1exp 
p(r) pdf
Ricean
A=0
where
•
The effect of a dominant line-of-sight signal arriving at MS with
many weaker multipath signals gives rise to the Ricean distribution
• The Ricean distribution degenerates to a Rayleigh distribution when
the dominant component fades away
• The Ricean probability density function (pdf) is defined as follows
r


Ar 
r
r^2A^2
P(r) 
exp
 where
 I 

^2


^2
2^2 
A-denotes the amplitude of the direct signal
I -modified Bessel fuction
00
0
Mobile Signal Strength - Log-Normal and Rayleigh
Distributions, continued
•
The Ricean distribution is often described in terms of parameter K which is
defined as the ratio of deterministic signal power to the variance of multipath
KdB10log
•
A^2
2^2
The parameter K is known as the Ricean factor and completely specifies the
Ricean distribution. If A=0 then we have Rayleigh distribution. For K>>1,
the Ricean probability density function is approximately Gaussian about the
mean.
Decibel Concept
P1
P2
G1
•
•
P3
G2
P4
L1
The dB (decibel) unit was introduced to describe the transfer characteristics of
NETWORKworks, so when working in dB, gains can be added instead of
multiplied
When two powers P2 and P1 are expressed in the same units (kilowatts, watts)
then their ratio can be defined as
P
where
P
log denotes the logarithm function to the base 10
 2 


 1 
dB10log
•
If an amplifier has G gain,then its output
power in watts is defined as


P2 W P1WG
Decibel Concept, continued
•
This relationship could also be expressed in dB as:
P 2dBm P1dBmGdB
If an attenuation has L loss, then its output power in watts and dBm is defined as
P 4W
P3W
L
P 4dBm P3dBm L dB
Using gains and losses in dB, the output power P4 can be
expressed as follows
P 4 dBm P1dBm G1dB G2 dB LdB
Decibel Concept, continued
•
•
•
•
•
•
•
•
Voltage or field strength at a receiving end is measured in dBu. This notation is
a simplification of decibels above 1uV/m which has been accepted by the
Institute of Radio Engineers
Relationship between voltage in dBu and the power associated with it in dBm
assuming 50 ohms terminal impedance is as follows:
1dBu = -107dBm
Relationship between a field strength in dBu and its received power in dBm
assuming half-wave dipole probe, 50 ohms terminal impedance, and frequency
of 850 MHz as follows:
1dbu = -132 dBm
39 dbu = -93 dBm
32 dbu = -100 dBm
At another frequency or using another kind of probe,
Cellular Performance Snapshot - Survey of
Cellular Users
Versus
Cellular Application
2-way Partable Radio
 Users distribution:
• public safety, government and low enforcement agencies - 66%
• business and industrial - 17%
• service providers and dealers - 10%
 Cellular phones are preferred for:
• security of conversation
• mobility
 Portable radios are preferred for:
• voice quality
• reliability
Cellular Performance Snapshot - Survey of
Cellular Users, continued
 DISTRIBUTION OF USERS OPINIONS
 What are the cellular problems?
• dead spots in service area - 38%
• poor signal quality - 31%
• dropped calls - 24%
• interference or crosstalk - 19%
 Which aspects of cellular service are most important?
• reliability of service - 69%
• portability - 40%
• roaming - 31%
 How much time mobile phone is in use?
• 5 to 15 minutes per day - 80%
• 15 to 30 minutes - 10%
 How often mobile phone is used?
• less than 5 calls per day - 61%
• 5-10 calls per day - 32%
Cell Site Planning - An Essential Task of Wireless
System Development
Millions of users
300
250
200
150
100
50
1984
•
•
1988
1992
1996
2000
2004
Years
The estimation of projected cellular market in the US is based on the current growth
rate
The deployment of wireless networks is still characterized by consistent
underestimation of subscriber demand and capital investment required
Cell Site Planning - An Essential Task of Wireless
System Development, continued
•
•
•
•
Proper planning of wireless system should be two years ahead of the implementation which is
dictated by normal lead times on hardware and sites
– zoning approval and site acquisition - 6-12 months
– Base Station electronics equipment delivery - 3 months
– antennas, chargers, rectifiers, and back-up batteries - 4 months
Badly planned wireless network demonstrates the following inefficiencies
– poor performance in frequency reuse (noise and interference)
– poor RF coverage (dead spots)
– increased rate of dropped calls (poor hand off engineering)
– excessive call blocking (poor system resource engineering)
RF engineers should do cell sites planning properly rather than just quickly
When the project manager is driven by idea to get coming up and running in much shorter time
frames, the consequences of built-in compromises could be
– less than optimal Base Station location
– the site may not be suitable for future expansions
– future frequency reuse may be limited
– equipment may not be compatible with the rest of the network
Cell Site Selection Concept
Power line
Joint site
•
•
•
•
Cell site selection is the process of selecting good base station sites
The selection of the best sites is essential for both good coverage and extensive frequency
reuse
From the customer point of view, the most vital feature of a cellular system is good
coverage within the defined service area
The RF cell planning objective is to cover the service area without discontinuities, with
specified GOS and interference, and providing for cell growth and future frequency reuse
Cell Site Selection Concept, continued
•
•
•
•
•
•
A cell cluster with N=4,7, or 12 is chosen on the basis of long-term subscriber density
distribution
The cell site needs access to commercial power (about 400 W per radio) including airconditioning and emergency power plant
The availability of a cell site depends on zoning codes, property owner limitations and
neighborhood environmental concerns such as
– radio interference with TV reception
– safety of the antenna tower
– effect of EM emission on health support devices
The FCC has specified a field strength of 39 dBuV/m average as the boundary of a cell;
this figure is a compromise because in a real cell signal strength fluctuates with time,
mobile speed and position
The real objective is to obtain a signal-to-noise ratio (S/N) comparable to a land-line
telephone service which is usually accepted as 30 dB
Good handheld coverage can be defined as a signal level yielding a comfortable voice in
buildings from the ground floor up, excluding elevators and their vicinity
Cell Site Boundary Determination - Carey Contours
60 dBuV/m
Zone of quality coverage
39 dBuV/m
32 dBuV/m
BS
Zone of marginal coverage
•
•
•
The FCC has used R. Carey empirical (jingyande) study of TV field strength of 25
dBuV/m for 50 % of locations and 50 % of time
For cellular service planning, FCC made a 14-dB adjustment to Carey curves to make up
a contour of 39 dBuV/m reliable for 90 % of locations and 90 % of time
Wireless operators making service applications in the US are required by the FCC to
submit service areas based on 39 dBuV/m
Cell Site Boundary Determination - Carey
Contours, continued
• In 1992 the FCC proposed a new cell boundary criteria defined by 32
dBuV/m and so far the dispute had not been settled
• The 32 dBuV/m contour defines an area where a 3-watts mobile unit will
perform with a reasonable reliability (around 90 %/) while a handheld will
have an irregular reception in suburban and urban areas
• Generally for suburban areas, 39-40 dBuV/m will provide cell boundary with
quality coverage while 32-39 dBuV/m will provide marginal coverage
• The FCC has proposed an approximate formula to calculate the 32 dBuV/m
contour as a function of antenna height and transmit power
d [km] = 2.5 x h^0.34 x P^0.17 where
– d is the distance from BS in km
– h is antenna height in m
– P is transmit power in W
• Field signal measurements are recommended to adjust the contour by
accounting for local terrain elevation and obstructions
Coverage In Noise-Limited System - Ways For
Improving
Cellular System
Start-up configuration
•
•
Mature configuration
In planning cell coverage, RF engineer should consider two different stages of
cellular system expansion
– start-up configuration (also referred to as noise-limited system)
– mature configuration (also referred to as interference-limited system)
The noise-limited system is defined as a system with no cochannel or adjacent
channel interference; two cases are possible:
– no cochannel and adjacent channels are used in the start-up configuration
– cochannel cells distanced far away and antennas are low so interference is
negligible
Coverage In Noise-Limited System - Ways For
Improving, continued
•
The following approaches are considered by RF engineer in order to increase cell
coverage (area of reliable RSS reception)
– increasing transmitted power: doubling of transmit power (3 dB increase) results in
extending covered cell area by 40 percent
– increasing BS antenna height: doubling of antenna height generally results in gain
increase of 6 dB in a flat terrain
– using a directional high-gain antennas extends the sectors of reliable RSS reception
– lowering the threshold level of RSS: drop of 6 dB can double the cell area
– using low-noise receivers increases the carrier-to-noise ratio which in turn extends
the area of reliable RSS reception
– using diversity receivers reduces multipath fading in particular directions
– selecting BS high-site locations
– engineering the antenna patterns
Interference In Interference-Limited Systems - Ways
For Reducing
Cellular System
Start-up configuration
Mature configuration
• The interference-limited system is defined as a system
with clusters of large and small cells and extensive
frequency reuse
Interference In Interference-Limited Systems - Ways
For Reducing, continued
•
The following methods are generally considered by RF engineer in order to reduce the
interference across the cell area (providing desirable voice quality)
– choosing cell site location by use of RF propagation prediction models
– reducing the antenna height
– reducing the transmitted power
– tilting the antenna patterns
– selecting directive antenna patterns
– proper assignment of idle, noisy, and vulnerable to interference channels
– good frequency reuse planning
Section B. Overview of
Propagation Mechanisms and Principles
-40
-50
-60
-70
RSSI,
dBm -80
-90
,
dB
-100
-110
0
4
8
12 16 20 24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
Section B Objectives
• Identify the main propagation modes which exist in the
mobile environment at cellular and PCS frequencies, and
recognize the type and magnitude of signal attenuation
they cause
• Recognize the special fading characteristics of signals in
the mobile environment and understand their causes
• Identify methods of combating fast fading in the mobile
environment
• Recognize the variable nature of signal penetration into
buildings and vehicles
Basic Mobile Propagation Models
Free Space
d
A
D
B
Reflection
with partial cancellation
Knife-edge
Diffraction
• Free Space
– no reflections, no obstructions
– signal decays 20 dB/decade
• Reflection
– reflected wave 180out of phase
– reflected wave not attenuated much
– signal decays 30-40 dB/decade
• Knife-Edge Diffraction
– direct path is blocked by obstruction
– additional loss is introduced
– formulae available for simple cases
Free-Space Propagation
•
r
Free Space
spreading Loss
energy intercepted
by the red square is
proportional to 1/r2
•
1st Fresnel Zone
d
A
D
The simplest propagation mode
– Imagine a transmitting antenna at the center of an
empty sphere. Each little square of surface intercepts
its share of the radiated energy
– Path Loss, dB (between two isotropic antennas)
=
36.58 +20*Log10(FMHZ)+20Log10(DistMILES )
– Path Loss, dB (between two dipole antennas)
= 32.26 +20*Log10(FMHZ)+20Log10(DistMILES )
– Notice the rate of signal decay:
– 6 dB per octave of distance change, which is
20 dB per decade of distance change
When does free-space propagation apply
– there is only one signal path (no reflections)
– the path is unobstructed (first Fresnel zone is not
peNETWORKrated by obstacles)
B
First Fresnel Zone =
{Points P where AP + PB - AB < }
Fresnel Zone radius d = 1/2 (D)^(1/2)
Reflection with Partial Cancellation
Direct
ray
Reflected
Ray
Point of
reflection
This reflection is at frazing incidence
The reflection is virtually 100%
efficient, and the phase of the
reflected signal flips 180 degrees.
• Assumptions:
– path distance is substantially longer
than height of either antenna
– there are no other obstructions and
the reflected ray is not blocked
If these assumptions are true, then:
– The point of reflection will be very
close to the car -- at most, a few
hundred feet away.
– the difference in path lengths is
influenced most strongly by the car
antenna height above ground or by
slight ground height variations
• The reflected ray tends to cancel the
direct ray, dramatically reducing the
received signal level
Reflection with Partial Cancellation
Heights Exaggerated
for Clarity
HTFT
HTFT
DMILES
•
Analysis:
– physics of the reflection cancellation
predicts signal decay approx. 40 dB
per decade of distance
• twice as rapid as in free-space!
– observed values in real systems range
from 30 to 40 dB/decade
Path Loss, dB =
172 + 34 x Log10 (DMILES )
- 20 x Log10 (Base Ant. HtFEET)
- 10 x Log10 (Mobile Ant. HtFEET)
Heights to Scale
Comparison of Free-Space and Reflection Propagation Modes
Assumptions: Flat earth, TX ERP = 50 dBm, @ 1950 MHz. Base Ht = 200 ft, Mobile Ht = 5 ft.
DistanceMILES
1
2
4
6
8
10
15
20
FS using Free-SpaceDBM
-52.4
-58.4
-64.4
-67.9
-70.4
-72.4
-75.9
-78.4
FS using ReflectionDBM
-69.0
-79.2
-89.5
-95.4
-99.7
-103.0
-109.0
-113.2
Knife-Edge Diffraction
•
H
R1
= -H
R2
2

 
1
R1
1
 R2
•
•
•
0
-5
atten -10
dB -15
-20
-25
•
-5 -4 -3 -2 -1 0 1 2 3

Sometimes a single well-defined obstruction
blocks the path. This case is fairly easy to
analyze and can be used as a manual tool to
estimate the effects of individual obstructions.
First calculate Fresnel zone diffraction
parameter  from path geometry
Next consult the table to obtain the
obstruction loss in dB
Add this loss to the otherwise-determined path
loss to obtain the total path loss.
Other losses such as reflection cancellation
still apply, but computed independently for the
path sections before and after the obstruction.
Recognize Typical Signal Fading Rates
Signal Level vs. Distance
0
-10
-20
-30
-40
1
2
3.16
5 6 7 8
Distance, Miles
One Decade
One Octave
of distance (2x)
of distance (10x)
10
We have seen how the signal fades with
distance in two simplified modes of
propagation:
• 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 fading
rates fall typically between 30 and 40 dB
per decade of distance
Additional Propagation Modes
Refraction
by atmospheric layers
Ducting
by atmospheric layers
>100 mi.
• Refraction: common problem near water
– wavefront can be sent when encountering
atmospheric layers of different density
– signal (or interference) can be delivered
far beyond normal line-of-sight path
– infrequent, but commonly occurs near
large bodies of water and flat deserts
• Ducting: an atmospheric freak
– waves wrapped between well-defined
atmospheric layers and/or earth surface
– signal can propagate hundreds of miles
– infrequent but can be relatively stable for
hours under unusual weather conditions
Real-Life Complications
Obstruction by Clutter
•
RFD
Multi-Path
Propagation
Building Penetration
Vehicle Penetration
•
•
Obstruction by Cluttered Environment
– this is the common mode in cities
– random absorption, additional loss
– random reflection causes delay spread
Multi-Path Propagation
– common in the mobile environment
– dozens or even hundreds of signal
components arrive at random amplitudes
and phases
– substantial delay spread
Building/Vehicle Penetration
– diffraction, absorption cause extra loss
– highly statistical and difficult to predict
– must be addressed for reliable service
Multi-path Propagation Effects
Small-Scale/Short-term Phenomena
•
•
•
Signal levels vary as user moves
Slow variations come from blockage and
shadowing by large objects such as hills
and buildings
Rapid Fading comes as signals received
from many paths drift into and out of
phase
– phase cancellation occurs, causing
rapid fades that are occasionally deep
– the fades are roughly /2 apart:
7 inches apart at 800 MHz.
3 inches apart at 1900 MHz
– called Rayleigh fading, after the
statistical model that describes it
Multi-path Propagation
Rayleigh Fading
A

10-15 dB
t
Space Diversity
A Method for Combating Rayleigh Fading
D
•
•
•
Signal received
by Antenna 1
•
Signal received
by Antenna 2
Combined
Signal
Fortunately, Rayleigh fades are very
short and last a small percentage of the
time
Two antennas separated by several
wavelengths will not generally
experience fades at the same time
space Diversity can be obtained by using
two receiving antennas and switching
instant-by-instant to whichever is best
Required separation D for good decorrelation is 10-20
– 12-24 ft. @ 800 MHz.
– 5-10 ft. @ 1900 MHz.
Space Diversity
Application Limitations
D
•
•
Signal received
by Antenna 1
Signal received
by Antenna 2
Combined
Signal
•
Space Diversity can be applied only on
the receiving end of a link.
Transmitting on two antennas would:
– fail to produce diversity, since the
two signals combine to produce only
one value of signal level at a given
point -- no diversity results.
– produce objectionable nulls in the
radiation at some angles
Therefore, space diversity is applied only
on the uplink i.e., reverse path
– there is not room for two sufficiently
separated antennas on a mobile or
handheld
Using Polarization Diversity
where Space Diversity is not convenient
V+H
or
\+/
A B
A B
Antenna A
Antenna B
Combined
• Sometimes zoning considerations or
aesthetics preclude using separate diversity
receive antennas
• Dual-polarized antenna pairs within a single
radome are becoming popular
– environmental clutter scatters RF energy
into all possible polarizations
– differently polarized antennas receive
signals which fade independently
– in urban environments, this is almost as
good as separate space diversity
• Antenna pair within one radome can be V-H
polarized, or diagonally polarized
– each individual array has its own
independent feedline
– feedlines connected to BTS diversity inputs
in the conventional way; TX duplexing OK
Building Penetration
Calculation Attempts using Physics
Building Penetration
Vehicle Penetration
•
•
?
?
•
?
Typical Penetration Losses
compared to outdoor street level
All metal attenuation
26 dB
Foil insulation
3.9 dB
Concrete block wall
13-20 dB
Ceiling Duct
1-8 dB
Metal Stairs
5 dB
•
Main Mechanism: Diffraction
A highly variable situation!
– variable geometry
– variable materials
– variable contents
– variable angle of RF penetration
Calculation attempts based on
– indoor geometry/ray tracing
– floor-by-floor coupling delta factors
– windows, doors, stairs, etc.
– types of construction materials
• concrete, insulation, etc.
Calculation methods are not very effective
or reliable; instead, statistical models are
used
The Reciprocity Principle
Does it apply to Wireless ?
-148.21 dB
@ 1871.25 MHz
-148.21 dB
@ 1871.25 MHz
-151.86 dB
@ 1951.25 MHz
The Reciprocity Principle:
Between two antennas, on the same exact
frequency, path loss is the same in both
directions.
• But things are not exactly the same in
wireless -– transmit and receive 45 or 80 MHz.
apart
– antenna: gain/frequency slope
– different Rayleigh fades up/downlink
– often, different TX & RX antennas
– RX diversity
• Notice also the noise/interference
environment may be substantially different
at the two ends
• So, reciprocity holds only in a general sense
for cellular
Section C. Propagation Models
-40
-50
-60
-70
RSSI,
dBm -80
-90
,
dB
-100
-110
0
4
8
12 16 20 24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
Section C Objectives
• Recognize the need for propagation models, and their roles in system
design
• Identify available types of models and their appropriate uses
• Survey the most popular available propagation models and become
familiar with their basic inputs, processes, and outputs
• Understand application of statistical methods to develop confidence
levels for system coverage
• Recognize the purpose and structure of link budgets
• Understand the parameters typically included in Link Budgets, and
recognize typical ranges for their values
Propagation Models
Why do we need propagation models?
•
•
•
•
Using the physics of propagation, even
our best calculations can not give us all
the answers we need
– we can not compute every reflected
path, every obstruction
– we even want general answers
without knowing specific paths
We can make measurements
– but we can not 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
RF
,
dB
Types of Propagation Models and their Uses
Examples of Various Model Types
•
•
•
•
Simple Analytical models
– used for understanding and
predicting individual paths and
specific obstruction cases
General Area models
– primary drivers: statistical
– used for early system dimensioning
(cell counts, etc.)
Point-to-Point models
– primary drivers: analytical
– used for detailed coverage analysis
and cell planning
Local Variability models
– primary drivers: statistical
– characterizes microscopic level
fluctuations in a given locale,
confidence-of-service probability
 Simple Analytical
• free space (Friis)
• reflection cancellation
• knife-edge diffraction
 Area
• Okumura-Hata
• Euro/Cost-231
• Walfisch-Betroni/Ikegami
 Point-to-Point
• Ray Tracing
- Lee- Method, others
• Tech-Note 101
• Longley-Rice, Biby-C
 Local Variability
• Rayleigh Distribution
• Normal Distribution
• Joint probability Techniques
General Principles of Area Models
-50
+90
-60
+80
-70
+70
-80
+60 Field
Strength,
+50
dBuV/m
RSSI,
-90
dBm
-100
+40
-110
+30
-120
0
3
6
9 12 15 18 21 24 27 30 33
•
•
•
+20
Distance from Cell Site, km
•
Area models mimic an average
path in a defined area
Based on measured data alone,
with no consideration of
individual path features or
physical mechanisms
Typical inputs used by model:
– Frequency
– Distance from transmitter to
receiver
– Actual or Effective Base
Station & mobile Heights
– Average Terrain Elevation
– Topography correction loss
(Urban, Suburban, Rural, etc.)
Results may be quite different
than observed on individual paths
in the area
The Okumura Model:
Parent of Hata and Euro/Cost-231 Models
Path Loss, dB = LFS + Amu(f,d) - G(Ht) - G(Hr) - Garea
LFS = 32.26 + 20Log10(dMILES) + 20Log10 (fMHZ)
free space path loss (friis formula)
Amu(f,d) = additional median attenuation
expressed by Okumura in curves
G(Ht) = gain due to base station antenna height
= 20Log10 (Ht / 200) for Ht = 10m to 1000m
G(Hr) = gain due to mobile station antenna height
= 10Log10 (Hr / 3) for Hr = less than 3m
Garea = gain due to topography of area (arbitrary)
• The Okumura model is the basic template from which the popular
Okumura-Hata and Euro/Cost-231 PCS area models are derived from.
Okumura-Hata Model
A (dB) = 69.55 + 26.16 log (F) -13.82 log(H) + (44. 9 -6.55 log(H) )*log (D) + C
Where: A
F
D
H
C
=
=
=
=
=
Path loss
Frequency in mHz (800-900 mHz)
Distance between base station and terminal in km
Effective height of base station antenna in m
Environment correction factor
C = 0 dB
- 5 dB
- 10 dB
- 17 dB
=
=
=
=
Dense Urban
Urban
Suburban
Rural
Euro/COST-231-HATA Model
A (dB) = 46.3 + 33.9*logF -13.82*logH + (44.9 -6.55*logH)*log D + C
Where:
A = Path loss
F = Frequency in MHz (between 1700 and 2000 MHz)
D = Distance between base station and terminal in km
H = Effective height of base station antenna in m
C = Environment correction factor
C =
for dense urban environment: high buildings, medium and
wide streets
for medium urban environment: modern cities with small
parks
for dense suburban environment, high residential buildings.
wide streets
for medium suburban environment. industrial area and small
homes
for rural with dense forests and quasi no hills
Statistical Propagation Models
Typical Results including Environmental Correction
COST-231/Hata
f =1900 mHz.
Tower
Height
(meters)
EIRP
(watts)
Dense Urban
Urban
Suburban
Rural
30
30
30
50
200
200
200
200
f = 870 mHz.
Tower
Height
(meters)
EIRP
(watts)
Dense Urban
Urban
Suburban
Rural
30
30
30
50
200
200
200
200
Okumura/Hata
C, Range,
dB
km
0
-5
-10
-17
2.52
3.50
4.8
10.3
C, Range,
dB
km
-2
-5
-10
-26
4.0
4.9
6.7
26.8
Walfisch-Betroni/Walfisch-Ikegami Models
• Propagation in built-up portions of cities is
dominated by ray diffraction over the tops
of buildings and by ray
•
through multiple reflections down the street
canyons
• Ordinary Okumura-type models do work in
this environment, but the Walfisch models
attempt to improve accuracy by exploiting
the actual propagation mechanisms
involved
Area View
Signal
Level
Legend
-20 dBm
-30 dBm
-40 dBm
-50 dBm
-60 dBm
-70 dBm
-80 dBm
-90 dBm
-100 dBm
-110 dBm
-120 dBm
Path Loss = LFS + LRT + LMS
LFS = free space path loss (Friis formula)
LRT = rooftop diffraction loss
LMS = multiscreen reflection loss
Urban Out-of-Sight Propagation Model
W1
Receiving
Antenna
W2
d1

Receiving
Antenna

Transmitting
Antenna
• Out-of-sight mode is typical for PCS when
mobile on street can not be seen by BS antenna
• This model is based on geometry of buildings
reflection and RSSI measurements in NY-city
• Model is applicable for 1956 MHz SS signal,
BS antenna height 6.5 m, MS antenna height
1.5 m, buildings height about 30 m, building
block length 75 m, main street width 30 m, side
street width 20 m
Parameters Included:
LOOS = out-of-sight path loss
LFS = Free space loss
A
= corner inflicted attenuation
B
= slope in out-of-sight street
d1 = BS and street corner separation
d2 = MS and street corner separation
Statistical Techniques
Distribution Statistics Concept
Signal Strength Predicted vs. Observed
•
An area model predicts signal strength vs.
distance over an area
– this is the median or most probable
RSSI,
signal strength at every distance from dBm
the cell
– the real signal strength at any real
location is determined by physics, and
will be higher or lower
– it is feasible to determine median signal
strength M and standard deviation 
– it is feasible to apply M and  to find
probability of receiving an arbitrary
signal level at a given distance
Signal Strength predicted
by area model
Observed
Signal Strength
Distance
Occurrences
Normal
Distribution
RSSI
Median
Signal
Strength
,
dB
Statistical Techniques
Practical Application of Distribution Statistics
•
•
Percentage of Locations where
Observed RSSI exceeds Predicted RSSI
Technique:
– use a model to predict RSSI
– compare measurements with model
• obtain median signal strength M
RSSI,
dBm
• obtain standard deviation 
• now apply correction factor to obtain
field strength required for desired
probability of service
Applications: Given
– a desired outdoor signal level
– the observed standard deviation  from
signal strength measurements
– a desired percentage of locations which
must receive that signal level
– compute a fluctuation dB which will give us
that % coverage confidence
10% of locations
exceed this RSSI
50%
90%
Distance
Occurrences
Median
Signal
Strength
Normal
Distribution
RSSI
,
dB
Area Availability
and Probability of Service at Cell Edge
•
Statistical View of
Cell Coverage
75%
90%
Area Availability:
90% overall within area
75%at edge of area
•
Overall probability of service is best close to
the BTS, and decreases with increasing
distance away from BTS
For overall 90% location probability within
cell coverage area, probability will be 75% at
cell edge
– result derived theoretically, confirmed in
modeling with propagation tools, and
observed from measurements
– true if path loss variations are lognormally distributed around predicted
median values, as in mobile environment
– 90%/75% is a commonly-used wireless
numerical coverage objective
Statistical Techniques
Example of Application of Distribution Statistics
Cumulative Normal Distribution
•
100%
90%
80%
•
75%
70%
60%
50%
•
40%
30%
0.675
20%
10%
0%
-3 -2.5 -2 -1.5 -1 -0.5 0
0.5 1
1.5 2
2.5 3
Standard Deviations from
Median (Average) Signal Strength
Let us design a cell to deliver at
least -95 dBm to at least 75% of
the locations at the cell edge. (This
will be 90% of total locations within
the cell.)
Measurements you are made show a
10 dB. standard deviation  above
and below the median signal
strength
On the chart:
– to serve 75% of locations at
the cell edge , we must deliver
a median signal strength (.675
times  ) stronger than -95
dBm
– -95 + ( .675 x 10 ) = -88 dBm
– So, design for a median signal
strength of -88 dBm!
Statistical Techniques
Normal Distribution Graph & Table for Convenient
Reference
Cumulative Normal Distribution
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
-3
-2.5 -2
-1.5 -1
-0.5
0
0.5
1
1.5
2
Standard Deviations from Mean Signal Strength
2.5
3
Standard
Deviation
-3.09
-2.32
-1.65
-1.28
-0.84
-0.52
0
0.52
0.675
0.84
1.28
1.65
2.35
3.09
3.72
4.27
Cumulative
Probability
0.1%
1%
5%
10%
20%
30%
50%
70%
75%
80%
90%
95%
99%
99.9%
99.99%
99.999%
Building Penetration
Statistical Characterization
Building Penetration
Vehicle Penetration
•
•
Typical penetration Losses, dB
compared to outdoor street level
Environment
Type
Median Std.
Loss, Dev.
dB
, dB
Dense Urban Bldg.
20
8
Urban Bldg.
15
8
Suburban Bldg.
10
8
Rural Bldg.
10
8
Typical Vehicle
8
4
•
Difficult to characterize analytically,
statistical techniques are more effective
– many analytical parameters, all
highly variable and complex
Usually modeled as additional
penetration loss plus existing outdoor
path loss
– median value estimated/sampled,
statistical distribution determined
– standard deviation estimated or
measured
– additional margin allowed in link
budget to offset assumed loss
Typical values in the table at left
Composite Probability of Service
with Multiple Attenuating Mechanisms
Building
COMPOSITE = ((OUTDOOR)2+(PENETRATION)2)1/2
Outdoor Loss + Penetration Loss
RSSICOMPOSITE = RSSIOUTDOOR+RSSIPENETRATION
• For an in-building user, the actual signal level includes regular outdoor
path attenuation plus building penetration loss
• Both outdoor and penetration losses have their own variabilities with their
own standard deviations
• The user’s overall composite probability of service must include
composite median and standard deviation factors
Composite Probability of Service
Calculating Fade Margin for Link Budget
• Example Case: Outdoor  is 8 dB., and penetration loss  is 8 dB.
Desired probability of service is 75% at the cell edge.
• What is the composite ? How much fade margin is required?
COMPOSITE = ((OUTDOOR)2+(PENETRATION)2)1/2
= ((8)2+(8)2)1/2 =(64+64)1/2 =(128)1/2 = 11.31 dB
Cumulative Normal Distribution
On cumulative normal distribution curve, 75%
probability is 0.675  above median.
Fade Margin required =
(11.31) (0.675) = 7.63 dB.
100%
90%
Composite Probability of Service
80%
Calculating Required Fade Margin
Building
OutComposite
Penetration Door
Total
Environment
Type
Median Std.
Std.
Area
Fade
Loss, Dev.
Dev.
Availability
Margin
dB
, dB , dB
Target, %
dB
Dense Urban Bldg. 20
8
8
90%/75% @edge
7.6
Urban Bldg.
15
8
8
90%/75% @edge
7.6
Suburban Bldg.
10
8
8
90%/75% @edge
7.6
Rural Bldg.
10
8
8
90%/75% @edge
7.6
Typical Vehicle
8
4
8
90%/75% @edge
6.0
75%
70%
60%
50%
40%
30%
20%
10%
0%
.675
-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1
1.5 2 2.5 3
Standard Deviations from
Median (Average) Signal Strength
Link Budget Models
•
•
•
Transmitter
Link Budgets trace power expenditures along path
from transmitter to receiver
– identify maximum allowable path loss
– determine maximum feasible cell radius
Two distinct cases: Uplink, Downlink
– No advantage if link range in one direction
exceeds the other
– adjust cell power to achieve uplink/downlink
balance
– set power on both links as low as feasible, to
reduce interference
Link budget model can include appropriate
assumptions for propagation, geography, other
factors
Trans.
Line
Antenna
Antenna
Trans.
Line
+43
dBm TX output
-3
= +40
dB line efficiency
dBm to antenna
+13
= +53
dB antenna gain
dBm ERP
-158
= -105
dB path attenuation
dBm dipole antenna
+13
= -92
dB antenna gain
dBm into line
-3
= -95
dB line efficiency
dBm to receiver
Receiver
Downlink
Uplink
CDMA Reverse Link Budget Model Example
Term or Factor
MS TX power (dBm)
MS TX power (watts)
MS antenna gain and body loss (dBi)
MS EIRP (dBm)
MS EIRP (watts)
Fade Margin (dB)
Soft Handoff Gain (dB)
Receiver Interference Margin (dB)
Building Penetration Loss (dB)
BTS RX antenna gain (dBi)
BTS cable loss (dB)
kTB (dBm/14.4 kHz)
BTS noise figure (dB)
Eb/Nt (dB)
BTS RX Sensitivity
Uplink Path Loss (dB)
Given
23.0 dBm
0.2 W
Budget
Formula
23.0 dBm
0.2 W
-7.6 dB
4.0 dB
-3.0 dB
-20.0 dB
A
0.0 dBi
17.0 dBi
-3.0 dB
-132.4
6.4 dB
6.2 dB
-119.8 dB
130.2 dB
B
C
D
E
F
G
H
I
J
H+I+J
A+B+C+D+E+F+G
-(H+I+J)
CDMA Forward Link Budget Model Example
Term or Factor
BTS TX power (dBm)
BTS
% Power for traffic channels
No. of traffic channels in use (chs.)
BTS cable loss (dB)
BTS TX antenna gain (dBi)
BTS EIRP/traffic channel (dBm)
BTS EIRP/traffic channel (watts)
Fade margin (dB)
Receiver interference margin (dB)
Building Penetration Loss
MS antenna gain and body loss (dBi)
MS RX sensitivity
(NF 10.5 dB, Eb/No 5 dB)
Downlink Path Loss (dB)
Given
44.0 dBm
25.67 W
Budget
Formula
44.0 dBm
25.1 W
-7.6 dB
A
B
-3.0 dB
-20.0 dB
0.0 dBi
-116.8 dBm
C
D
E
F
130.2 dB
A+B+C+D+E-F
74%
19
-3.0 dB
17.0 dBi
CDMA Link Budget Conclusions
Reverse (Uplink)
Term or Factor
MS TX power (dBm)
MS TX power (watts)
MS antenna gain and body loss (dBi)
Given
0.2 W
0.0 dBi
23.0 dBm
MS EIRP (watts)
0.2 W
Fade Margin (dB)
-7.6 dB
Soft Handoff Gain (dB)
4.0 dB
Receiver Interference Margin (dB)
-3.0 dB
Building PeNETWORKration Loss (dB)
-20.0 dB
BTS RX antenna gain (dBi)
17.0 dBi
BTS cable loss (dB)
-3.0 dB
kTB (dBm/14.4 kHz)
-132.4
BTS noise figure (dB)
6.4 dB
Eb/Nt (dB)
6.2 dB
BTS RX Sensitivity
Uplink Path Loss (dB)
•
Budget
23.0 dBm
MS EIRP (dBm)
•
Forward (Downlink)
-119.8 dB
130.2 dB
Term or Factor
BTS TX power (dBm)
BTS
% Power for traffic channels
No. of traffic channels in use (chs.)
BTS cable loss (dB)
BTS TX antenna gain (dBi)
BTS EIRP/traffic channel (dBm)
BTS EIRP/traffic channel (watts)
Fade margin (dB)
Receiver interference margin (dB)
Building PeNETWORKration Loss
MS antenna gain and body loss (dBi)
MS RX sensitivity
(NF 10.5 dB, Eb/No 5 dB)
Downlink Path Loss (dB)
Given
44.0 dBm
25.67 W
74%
Budget
19
-3.0 dB
17.0 dBi
44.0 dBm
25.1 W
-7.6 dB
-3.0 dB
-20.0 dB
0.0 dBi
-116.8 dBm
130.2 dB
Forward and reverse links should be in gain balance. Excess gain on just one
link is no advantage during two-way communication.
– link balance adjustments are made by differential wilting or blossoming of
the BTS using BSM commands
The reverse link is usually the more difficult link due to interference and power
control issues of mobiles
Section D. Overview of Propagation
Measurement Tools and Methods
-40
-50
-60
-70
RSSI,
dBm -80
-90
,
dB
-100
-110
0
4
8
12 16 20 24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
Section D Objectives
• Survey commercially-available general
measurement tools, recognizing their basic
functions and structure
• Recognize important considerations for
drive-test modeling to characterize
morphological areas
1900 MHz. PCS Data Collection Topics
• Current practice: Drive tests for
– early set of sites for propagation modeling
– substantial fraction of actual sites for cell planning evaluation
• Tools Considerations:
– CW Testing
• wide variety of equipment available and in fair quantities
• does not provide data on delay spread, multipath issues
– CDMA Spread-Spectrum Signals, or GSM Channel Sounders
• limited products available, very expensive, small quantities
• provide delay spread & multipath insights
Obtaining Measurement Data
Practical Considerations & Tools
• Measurement data can be collected
manually, but it is simply too tedious
to obtain statistically useful
quantities by hand.
• There are many commercial data
collection systems available to
automate the collection process
• Most modern propagation prediction
software packages have the
capability to import measurement
data, compare it with predicted
values, and generate statistical
outputs (mean error, standard
deviation, etc.).
Commercial Measurement Systems
•Grayson Electronics:
•CDMA tool, CellScope
•MLJ
•CW test transmitters, receivers
•Qualcomm
•Mobile Diagnostic Monitor,
1900
QCP-
•SAFCO
•SmartSAM , SmartSAM Plus*,
PROMAS*, CDMA OPAS32
•COMARCO
•NAS-150, NAS-250, NAS-350
•LCC
•Cellumate*, RSAT; 揥alkabout?
RSAT 2000 w/expansion chassis*
TDMA/AMPS, GPS
•ZKSAM
•Rohde & Schwarz: GSM Tools
Field Data Collection
Elements of Typical Systems
Major Features:
• Field Strength Measurement
– accurate collection in real-time
– multi-channel, averaging capability
• Location Data Collection Methods:
– Global Positioning System (GPS)
– dead reckoning on digitized map database
using on-board compass and wheel
revolutions counter
– a combination of both methods is
recommended for the best results
• Ideally, system should be calibrated in true
field strength units (dBuV/m)
– not just raw RSSI dBm values
– normalized antenna gain, line loss
Cellular
Receiver
PC or
Collector
GPS
Receiver
Dead
Reckoning
Section E. Overview of Propagation Prediction
Tools
-40
-50
-60
-70
RSSI,
dBm -80
-90
,
dB
-100
-110
0
4
8
12 16 20 24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
Section E Objectives
• Survey commercially-available general
propagation prediction tools, recognizing
their basic functions and structure
• Recognize formats of terrain databases and
other inputs for cell planning propagation
prediction models
Point-to-Point Path-driven
Propagation Prediction Models
•
•
Based on deterministic methods
– use of terrain data for construction of path profile
– path analysis (ray tracing) for obstruction, reflection analysis
– appropriate algorithms applied for best emulation of underlying physics
– may include some statistical techniques
– automated point-to-point analysis for enough points to appear to provide large
area coverage on raster or radial grid
Commonly-used Resources:
– Terrain databases
– Morphological Databases
– Databases of existing and proposed sites
– Antenna characteristics databases
– Unique user-defined propagation models
Data Structure of Path-Driven
Area Propagation Prediction Tools
Geographic overlay Format:
• Output Map(s) on screen or plotter
– Coverage
• field strengths @ probability
• probabilities @ field strength
– Best-Server
– C/I (Adjacent Channel & Co-Channel)
• Cell Locations, Cell Grid
• Terrain Elevation Data
– USGS & Commercial databases
– Satellite or aerial photography
• Clutter Data
– Roads, Rivers, Railroads, etc.
– State, County, MTA, BTA boundaries
• Traffic Density Overlay
• Land Use Overlay
Survey of Available Tools
• A wide variety of software tools
are available for propagation
prediction and system design.
• Some tools are implemented on
PC/DOS/Windows platforms,
others on more powerful UNIX
platforms
• Capabilities and user interfaces
vary greatly
• Several of the better-known
tools for cellular engineering are
shown in the table at right.
Commercial Prediction Systems
•Qualcomm
•QEDesign CDMA Tool
(Unix)
•MSI
•PlaNETWORK (Unix)
•LCC
•CellCad
•ANETWORK
(Unix)
(DOS PC)
•CNETWORK
•Wings
•Solutions
(Unix)
(mainframe)
•ComSearch
•MCAP
(Unix)
•AT&T
•PACE
(DOS PC)
•Motorola
•proprietary
(Unix)
•TEC Cellular:
Wizard (DOS)
•Elebra: CONDOR, CELTEC
Examples of MSI Planet Output Screens
• Best-Server plot for handoff analysis
• Composite Coverage Plots (not shown: C/I, other capabilities)
Examples of QEDesign Output Screens
• Handoff cursor tool for analyzing and optimizing cell design to best
exploit soft handoff characteristics of CDMA
• Required Mobile ERP tool shows system-coverage-perspective view,
allows pinpointing areas where excess path loss exists
QEDesign Output Screens
(continued)
• Microcell tool for dense urban clutter
environment
• Antenna editor allows pattern
visualization and editing
QEDesign Output Screens
(continued)
• Measurement integration & data
profile features automate analysis and
correlation of drive-measured data
with model predictions
Structured Survey of Tool Features
Universal Basic Features
• Automatically calculates signal strength at
many points over a geographic area
– use databases of terrain data, environmental
conditions, land use, building clutter
estimated geographic traffic distribution, etc.
– user-definable 3-dimensional antenna
patterns
– Automatically analyzes paths, selects
appropriate algorithms based on path
geometry
– produces plots of coverage, C/I, etc.
• Used for analysis of sites, interference,
frequency planning, C/I evaluation, etc.
• Drawback: requires significant computation
power, time
Signal
Level
Legend
C/I
Legend
>20 dB
<20 dB
<17 dB
<14 dB
-20 dBm
-30 dBm
-40 dBm
-50 dBm
-60 dBm
-70 dBm
-80 dBm
-90 dBm
-100 dBm
-110 dBm
-120 dBm
Structured Survey of Tool Features
(continued)
Popular Advanced Features
• Accepts measurement input, can automatically
A A AA
A
A
A
A
generate predicted-vs-measured statistics and map
A A
displays
• Automatic hexagon-manipulation grid utility
• Maintains cell sites in relational database
– easy manipulation, import, export
• Flexible user interface allows multi-tasking
• Allows multiple user-defined propagation models
• Three dimensional terrain view
• Roads, boundaries, coastline easily overlaid onto
any display
A
A
A
A
Pred. Meas
Mean
-76 -72
Std. Dv
9
12
Samples 545 545
Area Name: DALLAS
Date: Initial Service
Subs: 100,000
Site Name Site # LatitudeLongitudeType Capacity
SITE - 1
SITE - 2
SITE - 3
SITE - 4
SITE - 5
A1
A2
A3
A4
A5
33/17/4696/08/33
33/20/0896/11/49
33/16/5096/12/14
33/10/2896/11/51
33/25/2196/03/53
Number of Sites
5
S322
S211
S332
S11
01
77
37
91
8
8
Total Capacity (Erlangs)221
7
9
6
1
3
1
3
4
8
2
2
7
1
8
9
6
7
9
5
10
3
11
2
8
4
6
Structured Survey of Tool Features
(continued)
Popular Advanced Features
• Produces plots of serving boundaries, C/I plots,
handoff boundaries, etc.
• allows interactive change of antenna number,
type, orientation, power and tilt
• Using growth-scaleable traffic input mask, can
predict traffic carried by each site, # channels
required
– Can automatically highlight cells not
meeting specified grade of service
• Algorithms for automatic frequency planning
and optimization
• user can define or mask cells to be changed or
unchanged during automatic optimization
CELL
14
22
26X
26Y
26Z
2
3
7
1
6
4
5
ERL Channels
8.3
17
2.1
5
1.7
4
23
31
14
20
2
3
7
1
6
4
5
Structured Survey of Tool Features
(continued)
Popular Advanced Features
• Identification of server and interferor
signal levels in live cursor mode upon
graphical coverage display
• Generates bin C/I & coverage statistics
for system evaluation
• Predicted Handoff Analysis
– statistical analysis of most likely
handoff candidates
– automatic generation of neighbor cell
lists
– percentage probability of handover
• Runs on powerful workstations to
minimize computation time
Cell 51 -82 dBm
Cell 76 -97 dBm
C/I +15 dB
C/I Pct. of Area
>20 dB 93.0%
<20 dB
7.0%
<17 dB
2.2%
Cell 18
Cell 24 48%
Cell 16 22%
Cell 17 18%
Cell 05 8%
Cell 22 4%
Propagation Farewell:
A Final Reminder about Cell Size
A Picture to Remember
-40
-50
-60
-70
RSSI,
dBm -80
-90
-100
-110
0
4
8
12
16 20
24 28 32
Distance from Cell Site, km
measured signal
Okumura-Hata model
Cell size varies logarithmically as a function
of RF power
We have accustomed to thinking linearly:
$1000 is twice of $500. But in propagation,
things work logarithmically.
• to multiply coverage distance by 10
requires a power increase of between 30 dB
and 40 dB
(that is 1000-10,000 times!)
• to decrease coverage distance by half
requires a power decrease of roughly 10 dB.
(that is 10 times)
• individual path obstructions and high spots
also can easily cause changes of +/- 20 dB.
or more in signal level at any spot
The end !