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CDMA NETWORK PLAN AND OPTIMIZE

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Propagation Analysis. Link Budget. Transmitter Power. +44. +22. Feedline Loss. -3. 0. Antenna Gain. +12. 0. Various Allowances. -15. -14. More Allowances. -8. -8. Traffic Factors. +20. 0. Antenna Gain. 0. +12. Cell Planning. Feedline Loss. 0. -3. Receiver Sensitivity. - PowerPoint PPT Presentation
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CDMA NETWORK PLAN AND OPTIMIZE Land Use Databases Traffic Estimation Antenna Selection and Application Cell Planning Propagation Analysis Transmitter Power Link Budget Feedline Loss Antenna Gain Various Allowances More Allowances Traffic Factors Antenna Gain Feedline Loss Receiver Sensitivity Link Budget +44 -3 +12 -15 -8 +20 0 0 -116 135.4 +22 0 0 -14 -8 0 +12 -3 -121 140.2 Schedule
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Page 1: CDMA NETWORK PLAN AND OPTIMIZE

CDMA NETWORK PLAN AND OPTIMIZE

Land UseDatabases

Traffic Estimation

Antenna Selectionand Application

Cell Planning

Propagation Analysis

Transmitter Power

Link Budget

Feedline Loss

Antenna Gain

Various Allowances

More Allowances

Traffic Factors

Antenna Gain

Feedline Loss

Receiver Sensitivity

Link Budget

+44

-3

+12

-15

-8

+20

0

0

-116

135.4

+22

0

0

-14

-8

0

+12

-3

-121

140.2

Schedule

Page 2: 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

Page 3: CDMA NETWORK PLAN AND OPTIMIZE

,dB

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

CDMA NETWORK PLAN AND OPTIMIZE

Page 4: 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

Page 5: 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

CDMA NETWORK PLAN AND OPTIMIZE

Page 6: CDMA NETWORK PLAN AND OPTIMIZE

Propagation: Basic Elements of a Radio Link

• 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

Trans-mitter

TransmissionLine

TransmissionLine

ElectromagNETWORKicFields

current current

Antenna 1 Antenna 2

ReceiverInformation Information

Propagation

Page 7: CDMA NETWORK PLAN AND OPTIMIZE

Elements and Parameters of a Radio Link

• 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 informationReceiver

Antenna

Antenna

Trans.Line

Transmitter

Trans.Line

power output modulation type spectral density coding, if any

line loss gain, bandwidth beamwidth polarization

path loss

gain, bandwidth beamwidth polarization

line loss sensitivity selectivity spreading gain coding gain dynamic range

Page 8: CDMA NETWORK PLAN AND OPTIMIZE

Radio Link Configurationsfor 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

Page 9: CDMA NETWORK PLAN AND OPTIMIZE

The Role of Frequency in Propagation• 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

/2

1 second

Frequency = number of cycles in one second

Page 10: CDMA NETWORK PLAN AND OPTIMIZE

The Relationship betweenFrequency and Wavelength

• 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 / FAMPS cell site f = 870 mHz.

0.345 m = 13.6 inches

PCS-1900 site f = 1960 mHz.

0.153 m = 6.0 inches

Examples:

Cell

speed = C

3x108 M1 second

F totalwaves

Page 11: CDMA NETWORK PLAN AND OPTIMIZE

The Radio Spectrum: Frequenciesused by various Radio Systems

Broadcasting Land-Mobile Aeronautical Mobile TelephonyTerrestrial Microwave Satellite

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.2 1.4 1.6 1.8 2.0 2.4 3.0 MHz3,000,000 i.e., 3x106 Hz

AM LORAN Marine1000 500 300 150 100 Meters

3 4 5 6 7 8 9 10 12 14 16 18 20 22 24 26 28 30 MHz30,000,000 i.e., 3x107 Hz

Short Wave -- International Broadcast -- Amateur CB 100 75 50 40 30 20 15 10 Meters

30 40 50 60 70 80 90 100 120 140 160 180 200 240 300 MHz300,000,000 i.e., 3x108 Hz

FM VHF TV 7-13VHF LOW Band VHFVHF TV 2-610 6 3 2 1 Meter

0.3 0.4 0.5 0/6 0.7 0.8 0.9 1.0 1.2 1.4 1.6 1.8 2.0 2.4 3.0 GHz3,000,000,000 i.e., 3x109 Hz

UHF TV 14-69UHF GPS DCS,PCS<Cellular1 0.6 0.3 0.2 0.15 0.1 Meter

3 4 5 6 7 8 9 10 12 14 16 18 20 22 24 26 28 30 GHz30,000,000,000 i.e., 3x1010 Hz

0.1 0.06 0.03 0.02 0.015 0.01 Meter

Page 12: CDMA NETWORK PLAN AND OPTIMIZE

Mathematics concept reviewMathematics concept review

Understand basic terms of the probability theory Understand and apply the Poisson, Log-Normal, Gaussian and Raylei

gh 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 a

ntenna radiation patterns

Understand basic terms of the probability theory Understand and apply the Poisson, Log-Normal, Gaussian and Raylei

gh 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 a

ntenna radiation patterns

Page 13: CDMA NETWORK PLAN AND OPTIMIZE

Exponential and Logarithm 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 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

10^x

x

y2^x

lg a

log2 a

a

Exponential Functions Logarirthm Functions

Page 14: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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

Page 15: CDMA NETWORK PLAN AND OPTIMIZE

Concepts of Slope, Intercept, and 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:

• The slope and intercept are basic characteristics used for RF path loss modeling

• The slope of straight line in orthogonal coordinates is defined as:

y

x

x1,y1

x2,y2

aA

A

Negative Slope LinePositive Slope Line

Zero Slope Line

No Slope Line

Intercept Points

b

Slope = (y2 - y1) / (x2 - x1) = tg A

Page 16: CDMA NETWORK PLAN AND OPTIMIZE

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 y-axis (denoted b)

• The straight line equation with slope m and intercept b is as follows

• 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.

• 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 y-axis (denoted b)

• The straight line equation with slope m and intercept b is as follows

• 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.

Y = m x X + b

RSS[dBm} = - 60 dBm + ( -38 dB/decade ) = - 98 dBm

Page 17: CDMA NETWORK PLAN AND OPTIMIZE

Polar Coordinates Concept

• 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

• 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

M

N

rm

rn

AmAn

Polar Graph

Page 18: CDMA NETWORK PLAN AND OPTIMIZE

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)

• 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)

Page 19: CDMA NETWORK PLAN AND OPTIMIZE

The Poisson Distribution

• 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

• 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

PXk

e ( ) k

k!PXk

e ( ) k

k!

Page 20: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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

• 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

• 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

Var X = E [(x - u)^2], where u - is the mean

Sigma = SQR ( Var X ) or Var X = (Sigma)^2

Page 21: CDMA NETWORK PLAN AND OPTIMIZE

Probability Density and Distribution Functions - Concepts

Probability density function f(x)

a bP(a<=x<=b)

F(x) area

f(x)

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.

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.

-

Page 22: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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

• 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

• 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

• 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

• 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

P (a< = x < = b) =a

b

f (x) x dx

F (x) = P (X< = x) = f (x) x dxx

Page 23: CDMA NETWORK PLAN AND OPTIMIZE

The Normal or Gaussian Distribution

• The normal distribution has a density function defined by formula

• Special case of normal distribution with u=0 and (sigma)^2 = 1 is called standard normal distribution

• The normal distribution has a density function defined by formula

• Special case of normal distribution with u=0 and (sigma)^2 = 1 is called standard normal distribution

Smaller Sigma

Mean

Larger Sigma

Mean

Standard normaldistribution

1 2 3-3 -2 -1

f(x)1

2exp

(x )^2

2^2

Page 24: CDMA NETWORK PLAN AND OPTIMIZE

Confidence Interval and Confidence Level

• Values 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

• 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

• Values 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

• 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

f(x)

Area=F(x1)

x1 x2 x

Bell-shaped pdf

F(x)1

cdf

x1

F(x1)

x

RSS - k x (sigma) < = RSS < = RSS +k x (sigma)RSS - is any measurement reading K- is a positive number between 0 and 2RSS- is a local mean of the received signal strength

P(m xm)1

2exp

(x m)^22^2m

m dx

Page 25: CDMA NETWORK PLAN AND OPTIMIZE

Mobile Signal Strength - Log-Normal and Rayleigh Distributions

• A mobile radio signal r(t) can be presented by two components as r (t) = 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

• A mobile radio signal r(t) can be presented by two components as r (t) = 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

Signal strength, dBm

TimeMobile signal fading

m(t)- local mean

r(t)

Page 26: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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

Page 27: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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^2

exp r^22x 2

if r o

0 if r < 0 where

r - signal strength (RSS) - standard deviation

Page 28: CDMA NETWORK PLAN AND OPTIMIZE

Mobile Signal Strength - Log-Normal and Rayleigh Distributions, continued

• The Rayleigh distribution function (cdf) is defined as follows

• 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

• The Rayleigh distribution function (cdf) is defined as follows

• 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

P(r R)1 exp R^2

2^2

where

R- specified level of RSS

P(r) r

^2exp r 2A^2

2^2

I00

A r 2

where

A-denotes the amplitude of the direct signalI0-modified Bessel fuction

p(r)

A=0

r

Ricean pdf

Page 29: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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.

• 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

• 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.

K dB

10 log A^2

2^2

Page 30: CDMA NETWORK PLAN AND OPTIMIZE

Decibel Concept

• 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

• If an amplifier has G gain, then its output power in watts is defined as

• 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

• If an amplifier has G gain, then its output power in watts is defined as

dB10 log P2

P1

where

log denotes the logarithm function to the base 10

P2 W

P1 W

G

P1 P2 P3 P4

G1 G2 L1

Page 31: CDMA NETWORK PLAN AND OPTIMIZE

Decibel Concept, continued

• This relationship could also be expressed in dB as:• This relationship could also be expressed in dB as:

P2 dBm

P1 dBm

G dB

P4 W P3 W

LP4 dBm P3 dBm

L dB

P4 dBm

P1 dBm

G1 dB

G2 dB

L dB

Using gains and losses in dB, the output power P4 can be expressed as follows

If an attenuation has L loss, then its output power in watts and dBm is defined as

Page 32: CDMA NETWORK PLAN AND OPTIMIZE

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,

• 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,

Page 33: CDMA NETWORK PLAN AND OPTIMIZE

Cellular Performance Snapshot - Survey of Cellular Performance Snapshot - Survey of Cellular UsersCellular Users

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

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

Versus

Cellular Application

2-way Partable Radio

Page 34: CDMA NETWORK PLAN AND OPTIMIZE

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%

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%

Cellular Performance Snapshot - Survey of Cellular Performance Snapshot - Survey of Cellular Users, continuedCellular Users, continued

Page 35: CDMA NETWORK PLAN AND OPTIMIZE

Cell Site Planning - An Essential Task of Wireless System Development

• 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

• 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

19881984 1992 1996 2000 2004

50

100

150

200

250

300Millions of users

Years

Page 36: CDMA NETWORK PLAN AND OPTIMIZE

• 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

• 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 Planning - An Essential Task of Wireless Cell Site Planning - An Essential Task of Wireless System Development, continuedSystem Development, continued

Page 37: CDMA NETWORK PLAN AND OPTIMIZE

Cell Site Selection Concept

• 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 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

Power line

Joint site

Page 38: CDMA NETWORK PLAN AND OPTIMIZE

• 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 air-conditioning 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

• 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 air-conditioning 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 Selection Concept, continuedCell Site Selection Concept, continued

Page 39: CDMA NETWORK PLAN AND OPTIMIZE

Cell Site Boundary Determination - Carey Contours

• 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

• 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

BS

60 dBuV/m

39 dBuV/m

32 dBuV/m

Zone of quality coverage

Zone of marginal coverage

Page 40: CDMA NETWORK PLAN AND OPTIMIZE

• 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

• 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

Cell Site Boundary Determination - Carey Cell Site Boundary Determination - Carey Contours, continuedContours, continued

Page 41: CDMA NETWORK PLAN AND OPTIMIZE

Coverage In Noise-Limited System - Ways For Improving

• 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

• 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

Cellular System

Start-up configuration Mature configuration

Page 42: CDMA NETWORK PLAN AND OPTIMIZE

• 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

• 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

Coverage In Noise-Limited System - Ways For Coverage In Noise-Limited System - Ways For Improving, continuedImproving, continued

Page 43: CDMA NETWORK PLAN AND OPTIMIZE

Interference In Interference-Limited Systems - Ways For Reducing

• The interference-limited system is defined as a system with clusters of large and small cells and extensive frequency reuse

• The interference-limited system is defined as a system with clusters of large and small cells and extensive frequency reuse

Cellular System

Start-up configuration Mature configuration

Page 44: CDMA NETWORK PLAN AND OPTIMIZE

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

• 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

Page 45: CDMA NETWORK PLAN AND OPTIMIZE

Section B. Overview of Propagation Mechanisms and Principles

,dB

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

Page 46: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 47: CDMA NETWORK PLAN AND OPTIMIZE

Basic Mobile Propagation Models

• Free Space

– no reflections, no obstructions

– signal decays 20 dB/decade

• Reflection

– reflected wave 180out 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

Knife-edge Diffraction

B

A

d

D

Free Space

Reflection with partial cancellation

Page 48: CDMA NETWORK PLAN AND OPTIMIZE

Free-Space Propagation

• The simplest propagation mode– Imagine a transmitting antenna at the center of an empt

y 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 d

B 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 peNE

TWORKrated by obstacles)First Fresnel Zone ={Points P where AP + PB - AB < }Fresnel Zone radius d = 1/2 (D)^(1/2)

1st Fresnel Zone

B

A

d

D

Free Space spreading Loss energy intercepted by the red square is proportional to 1/r2

r

Page 49: CDMA NETWORK PLAN AND OPTIMIZE

Reflection with Partial Cancellation • 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

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.

Page 50: CDMA NETWORK PLAN AND OPTIMIZE

Reflection with Partial Cancellation • 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 f

rom 30 to 40 dB/decadePath Loss, dB =

172 + 34 x Log10 (DMILES )- 20 x Log10 (Base Ant. HtFEET)

- 10 x Log10 (Mobile Ant. HtFEET)

Heights Exaggerated for Clarity

HTFT HTFT

DMILES

Comparison of Free-Space and Reflection Propagation ModesAssumptions: Flat earth, TX ERP = 50 dBm, @ 1950 MHz. Base Ht = 200 ft, Mobile Ht = 5 ft.

FS using Free-SpaceDBM

FS using ReflectionDBM

DistanceMILES

-52.4

-69.0

1

-58.4

-79.2

2

-64.4

-89.5

4

-67.9

-95.4

6

-70.4

-99.7

8

-72.4

-103.0

10

-75.9

-109.0

15

-78.4

-113.2

20

Heights to Scale

Page 51: CDMA NETWORK PLAN AND OPTIMIZE

Knife-Edge Diffraction

• 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.

H

R1 R2

attendB

0

-5

-10

-15

-20

-25

-4 -3 -2 -1 0 1 2 3-5

= -H2

1 1

R1 R2

Page 52: CDMA NETWORK PLAN AND OPTIMIZE

Recognize Typical Signal Fading Rates

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

Signal Level vs. Distance

-40

-30

-20

-10

0

Distance, Miles1 3.16 102 5 7 86

One Octave of distance (2x)

One Decadeof distance (10x)

Page 53: CDMA NETWORK PLAN AND OPTIMIZE

Additional Propagation Modes

• 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

Refraction by atmospheric layers

Ducting by atmospheric layers

>100 mi.

Page 54: CDMA NETWORK PLAN AND OPTIMIZE

Real-Life Complications

• 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

Building PenetrationVehicle Penetration

Obstruction by Clutter

RFD

Multi-Path Propagation

Page 55: CDMA NETWORK PLAN AND OPTIMIZE

Multi-path Propagation EffectsSmall-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

A

t

10-15 dB

Rayleigh Fading

Multi-path Propagation

Page 56: CDMA NETWORK PLAN AND OPTIMIZE

Space DiversityA Method for Combating Rayleigh Fading

• 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 de-correlation is 10-20– 12-24 ft. @ 800 MHz.

– 5-10 ft. @ 1900 MHz.

Signal received by Antenna 1

Signal received by Antenna 2

Combined Signal

D

Page 57: CDMA NETWORK PLAN AND OPTIMIZE

Space DiversityApplication Limitations

• 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

Signal received by Antenna 1

Signal received by Antenna 2

Combined Signal

D

Page 58: CDMA NETWORK PLAN AND OPTIMIZE

Using Polarization Diversitywhere Space Diversity is not convenient

• 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 a

ll 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 p

olarized, or diagonally polarized– each individual array has its own independent

feedline– feedlines connected to BTS diversity inputs in

the conventional way; TX duplexing OK

Antenna A

Antenna B

Combined

A B A B

V+Hor\+/

Page 59: CDMA NETWORK PLAN AND OPTIMIZE

Building PenetrationCalculation Attempts using Physics

• 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

Building PenetrationVehicle Penetration

?

?

?

Typical Penetration Lossescompared to outdoor street level

All metal attenuation

Foil insulation

Concrete block wall

Ceiling Duct

26 dB

3.9 dB

13-20 dB

1-8 dB

Metal Stairs 5 dB

Page 60: CDMA NETWORK PLAN AND OPTIMIZE

The Reciprocity PrincipleDoes it apply to Wireless ?

The Reciprocity Principle:Between two antennas, on the same exact fre

quency, path loss is the same in both directions.

• But things are not exactly the same in wireless --– transmit and receive 45 or 80 MHz. apa

rt– 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

-148.21 dB@ 1871.25 MHz

-151.86 dB@ 1951.25 MHz

-148.21 dB@ 1871.25 MHz

Page 61: CDMA NETWORK PLAN AND OPTIMIZE

Section C. Propagation Models

,dB

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

Page 62: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 63: CDMA NETWORK PLAN AND OPTIMIZE

Propagation ModelsWhy 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

Page 64: CDMA NETWORK PLAN AND OPTIMIZE

Types of Propagation Models and their Uses

• 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

Examples of Various Model Types

Page 65: CDMA NETWORK PLAN AND OPTIMIZE

General Principles of Area Models

• 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

RSSI, dBm

-120

-110

-100

-90

-80

-70

-60

-50

0 3 6 9 12 15 18 21 24 27 30 33

Distance from Cell Site, km

FieldStrength,dBuV/m

+90

+80

+70

+60

+50

+40

+30

+20

Page 66: CDMA NETWORK PLAN AND OPTIMIZE

The Okumura Model:Parent of Hata and Euro/Cost-231 Models

• The Okumura model is the basic template from which the popular Okumura-Hata and Euro/Cost-231 PCS area models are derived from.

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)

Page 67: CDMA NETWORK PLAN AND OPTIMIZE

A (dB) = 69.55 + 26.16 log (F) -13.82 log(H) + (44. 9 -6.55 log(H) )*log (D) + C

Where: AFDHC

C

=====

=

Path lossFrequency in mHz (800-900 mHz)Distance between base station and terminal in kmEffective height of base station antenna in mEnvironment correction factor

0 dB- 5 dB

- 10 dB- 17 dB

====

Dense UrbanUrbanSuburbanRural

Okumura-Hata Model

Page 68: CDMA NETWORK PLAN AND OPTIMIZE

for dense urban environment: high buildings, medium and wide streetsfor medium urban environment: modern cities with small parksfor dense suburban environment, high residential buildings. wide streetsfor medium suburban environment. industrial area and small homesfor rural with dense forests and quasi no hills

A (dB) = 46.3 + 33.9*logF -13.82*logH + (44.9 -6.55*logH)*log D + C

Where:AFDHCC

======

Path lossFrequency in MHz (between 1700 and 2000 MHz)Distance between base station and terminal in kmEffective height of base station antenna in mEnvironment correction factor

Euro/COST-231-HATA Model

Page 69: CDMA NETWORK PLAN AND OPTIMIZE

Statistical Propagation ModelsTypical Results including Environmental Correction

TowerHeight

(meters)

EIRP(watts)

C,dB

Range,kmf = 870 mHz.

Dense Urban Urban

Suburban Rural

30303050

200200200200

-2-5

-10-26

4.04.96.7

26.8

Okumura/Hata

TowerHeight

(meters)

EIRP(watts)

C,dB

Range,kmf =1900 mHz.

Dense Urban Urban

Suburban Rural

30303050

200200200200

0-5

-10-17

2.523.504.8

10.3

COST-231/Hata

Page 70: CDMA NETWORK PLAN AND OPTIMIZE

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

Path Loss = LFS + LRT + LMS

LFS = free space path loss (Friis formula)

LRT = rooftop diffraction loss

LMS = multiscreen reflection loss

-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

Page 71: CDMA NETWORK PLAN AND OPTIMIZE

Urban Out-of-Sight Propagation Model

• 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 lossLFS = Free space lossA = corner inflicted attenuationB = slope in out-of-sight streetd1 = BS and street corner separationd2 = MS and street corner separation

d1

Transmitting Antenna

ReceivingAntenna

ReceivingAntenna

W1

W2

Page 72: CDMA NETWORK PLAN AND OPTIMIZE

Statistical TechniquesDistribution Statistics Concept

• An area model predicts signal strength vs. distance over an area

– this is the median or most probable signal strength at every distance from 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 Median

Signal Strength

,dB

Occurrences

RSSI

Normal Distribution

RSSI, dBm

Distance

Signal Strength predictedby area model

Signal Strength Predicted vs. Observed

Observed Signal Strength

Page 73: CDMA NETWORK PLAN AND OPTIMIZE

Statistical TechniquesPractical Application of Distribution Statistics

• Technique:– use a model to predict RSSI– compare measurements with model

• obtain median signal strength M• 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

RSSI, dBm

Distance

10% of locations exceed this RSSI

50%90%

Percentage of Locations where Observed RSSI exceeds

Predicted RSSI

Median Signal Strength ,

dB

Occurrences

RSSI

Normal Distributio

n

Page 74: CDMA NETWORK PLAN AND OPTIMIZE

Area Availabilityand Probability of Service at Cell Edge

• 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 log-normally distributed around predicted median values, as in mobile environment

– 90%/75% is a commonly-used wireless numerical coverage objective

Statistical View ofCell Coverage

Area Availability:90% overall within area

75%at edge of area

90%

75%

Page 75: CDMA NETWORK PLAN AND OPTIMIZE

Statistical TechniquesExample of Application of Distribution Statistics

• 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 th

e 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!Standard Deviations from Median (Average) Signal

Strength

Cumulative Normal Distribution

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3

75%

0.675

Page 76: CDMA NETWORK PLAN AND OPTIMIZE

Statistical TechniquesNormal Distribution Graph & Table for Convenient

ReferenceCumulative Normal Distribution

Standard Deviations from Mean Signal Strength

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3

CumulativeProbability

0.1%1%5%

10%

StandardDeviation

-3.09-2.32-1.65-1.28-0.84 20%-0.52 30%

0.675 75%

0 50%0.52 70%

0.84 80%1.28 90%1.65 95%2.35 99%3.09 99.9%3.72 99.99%4.27 99.999%

Page 77: CDMA NETWORK PLAN AND OPTIMIZE

Building PenetrationStatistical Characterization

• 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

Building PenetrationVehicle Penetration

Typical penetration Losses, dBcompared to outdoor street level

EnvironmentType

MedianLoss,

dB

Std.Dev., dB

Urban Bldg. 15 8

Suburban Bldg. 10 8

Rural Bldg. 10 8

8 4Typical Vehicle

Dense Urban Bldg. 20 8

Page 78: CDMA NETWORK PLAN AND OPTIMIZE

Composite Probability of Servicewith Multiple Attenuating Mechanisms

• 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 = ((OUTDOOR)2+(PENETRATION)2)1/2

RSSICOMPOSITE = RSSIOUTDOOR+RSSIPENETRATION

Building

Outdoor Loss + Penetration Loss

Page 79: CDMA NETWORK PLAN AND OPTIMIZE

Composite Probability of ServiceCalculating 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 Probability of ServiceCalculating Required Fade Margin

EnvironmentType Median

Loss,dB

Std.Dev., dB

Urban Bldg. 15 8

Suburban Bldg. 10 8

Rural Bldg. 10 8

8 4Typical Vehicle

Dense Urban Bldg. 20 8

BuildingPenetration

Out-DoorStd.Dev., dB

8

8

8

8

8

CompositeTotal

AreaAvailabilityTarget, %

90%/75% @edge

90%/75% @edge

90%/75% @edge

90%/75% @edge

90%/75% @edge

FadeMargin

dB

7.6

7.6

7.6

6.0

7.6

COMPOSITE = ((OUTDOOR)2+(PENETRATION)2)1/2

= ((8)2+(8)2)1/2 =(64+64)1/2 =(128)1/2 = 11.31 dB

On cumulative normal distribution curve, 75%

probability is 0.675 above median. Fade Margin required =

(11.31) (0.675) = 7.63 dB. Cumulative Normal Distribution

Standard Deviations from Median (Average) Signal Strength

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3

75%

.675

Page 80: CDMA NETWORK PLAN AND OPTIMIZE

Link Budget Models

• 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

Receiver

Antenna

Antenna

Trans.Line

Transmitter

Trans.Line

+43 dBm TX output

-3 dB line efficiency= +40 dBm to antenna

+13 dB antenna gain= +53 dBm ERP

-158 dB path attenuation= -105 dBm dipole antenna

+13 dB antenna gain= -92 dBm into line

-3 dB line efficiency= -95 dBm to receiver

Uplink

Downlink

Page 81: CDMA NETWORK PLAN AND OPTIMIZE

CDMA Reverse Link Budget Model Example

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)

23.0 dBm

0.2 W

0.0 dBi

-132.4

6.4 dB

6.2 dB

23.0 dBm

0.2 W

-7.6 dB

4.0 dB

-3.0 dB

-20.0 dB

17.0 dBi

-3.0 dB

-119.8 dB

130.2 dB A+B+C+D+E+F+G-(H+I+J)

Given Budget

A

B

C

D

E

F

G

H+I+J

FormulaTerm or Factor

J

I

H

Page 82: CDMA NETWORK PLAN AND OPTIMIZE

CDMA Forward Link Budget Model Example

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)

44.0 dBm

25.67 W

74%

19

-3.0 dB

17.0 dBi

0.0 dBi

44.0 dBm

25.1 W

-7.6 dB

-3.0 dB

-20.0 dB

Downlink Path Loss (dB) 130.2 dB A+B+C+D+E-F

Given Budget

A

B

C

D

FormulaTerm or Factor

MS RX sensitivity (NF 10.5 dB, Eb/No 5 dB)

-116.8 dBm F

E

Page 83: CDMA NETWORK PLAN AND OPTIMIZE

CDMA Link Budget Conclusions

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 PeNETWORKration 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)

23.0 dBm

0.2 W

0.0 dBi

-132.4

6.4 dB

6.2 dB

23.0 dBm

0.2 W

-7.6 dB

4.0 dB

-3.0 dB

-20.0 dB

17.0 dBi

-3.0 dB

-119.8 dB

130.2 dB

Given BudgetTerm 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)

44.0 dBm

25.67 W

74%

19

-3.0 dB

17.0 dBi

0.0 dBi

44.0 dBm

25.1 W

-7.6 dB

-3.0 dB

-20.0 dB

Downlink Path Loss (dB) 130.2 dB

Given BudgetTerm or Factor

MS RX sensitivity (NF 10.5 dB, Eb/No 5 dB)

-116.8 dBm

Reverse (Uplink) Forward (Downlink)

• 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

Page 84: CDMA NETWORK PLAN AND OPTIMIZE

Section D. Overview of Propagation Measurement Tools and Methods

,dB

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

Page 85: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 86: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 87: CDMA NETWORK PLAN AND OPTIMIZE

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, QCP-1900

•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

Page 88: CDMA NETWORK PLAN AND OPTIMIZE

Field Data CollectionElements 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

CellularReceiver

PC or Collector

GPSReceiver

DeadReckoning

Page 89: CDMA NETWORK PLAN AND OPTIMIZE

Section E. Overview of Propagation Prediction Tools

,dB

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

Page 90: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 91: CDMA NETWORK PLAN AND OPTIMIZE

Point-to-Point Path-drivenPropagation 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

Page 92: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 93: CDMA NETWORK PLAN AND OPTIMIZE

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 (Unix)•ANETWORK (DOS PC)

•CNETWORK•Wings (Unix)•Solutions (mainframe)

•ComSearch•MCAP (Unix)

•AT&T•PACE (DOS PC)

•Motorola•proprietary (Unix)

•TEC Cellular: Wizard (DOS)•Elebra: CONDOR, CELTEC

Page 94: CDMA NETWORK PLAN AND OPTIMIZE

Examples of MSI Planet Output Screens

• Best-Server plot for handoff analysis

• Composite Coverage Plots (not shown: C/I, other capabilities)

Page 95: CDMA NETWORK PLAN AND OPTIMIZE

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

Page 96: CDMA NETWORK PLAN AND OPTIMIZE

QEDesign Output Screens(continued)

• Microcell tool for dense urban clutter environment

• Antenna editor allows pattern visualization and editing

Page 97: CDMA NETWORK PLAN AND OPTIMIZE

QEDesign Output Screens(continued)

• Measurement integration & data profile features automate analysis and correlation of drive-measured data with model predictions

Page 98: CDMA NETWORK PLAN AND OPTIMIZE

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

-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

C/ILegend

>20 dB<20 dB<17 dB<14 dB

Page 99: CDMA NETWORK PLAN AND OPTIMIZE

Structured Survey of Tool Features(continued)

Popular Advanced Features• Accepts measurement input, can automatically ge

nerate predicted-vs-measured statistics and map 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 a

ny display

AA

AA

A A

AA

A AA

A A

A

A

Pred. MeasMean -76 -72Std. Dv 9 12Samples 545 545

7

8

9

1

3

2

1

3

24

5

6

7

8

9

7

8

9

1

3

2

6

4

6

10

11

Area Name: DALLAS

Site Name

Subs: 100,000

Site # LatitudeLongitudeType Capacity

Number of Sites5 Total Capacity (Erlangs)221

SITE - 1SITE - 2SITE - 3SITE - 4SITE - 5

A1A2A3A4A5

33/17/4633/20/0833/16/5033/10/2833/25/21

96/08/3396/11/4996/12/1496/11/5196/03/53

S322S211S332S1101

77379188

Date: Initial Service

Page 100: CDMA NETWORK PLAN AND OPTIMIZE

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

43

2

56

17

43

2

56

17

CELL ERL Channels14 8.3 1722 2.1 526X 1.7 426Y 23 3126Z 14 20

Page 101: CDMA NETWORK PLAN AND OPTIMIZE

Structured Survey of Tool Features(continued)

Popular Advanced Features• Identification of server and interferor sign

al 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 minimi

ze computation time

Cell 51 -82 dBmCell 76 -97 dBmC/I +15 dB

Cell 18Cell 24 48%Cell 16 22%Cell 17 18%Cell 05 8%Cell 22 4%

C/I Pct. of Area>20 dB 93.0%<20 dB 7.0%<17 dB 2.2%

Page 102: CDMA NETWORK PLAN AND OPTIMIZE

Propagation Farewell:A Final Reminder about Cell Size

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

RSSI, dBm

-40

-110

-100

-90

-80

-70

-60

-50

0 4 8 12 16 20 24 28 32

Distance from Cell Site, km

measured signal

Okumura-Hata model

A Picture to Remember

Page 103: CDMA NETWORK PLAN AND OPTIMIZE

The end !


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