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CDMA NETWORK PLAN AND OPTIMIZE Propagation Analysis Link Budget Transmitter Power Feedline Loss Antenna CDMA NETWORK PLAN AND OPTIMIZE Propagation Analysis Link Budget Transmitter Power Feedline Loss Antenna Gain Various Allowances More Allowances +44 -3 +12 -15 -8 +22 0 0 -14 -8 Traffic Factors Antenna Gain Feedline Loss +20 0 +12 -3 Receiver Sensitivity -116 -121 Link Budget 135. 4 Cell Planning 140. 2 Traffic Estimation Antenna Selection and Application Land Use Databases Schedule

CDMA NETWORK PLAN AND OPTIMIZE • RF Propagation – underlying mechanisms – modeling and 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, d. Bm -80 -90 CDMA NETWORK PLAN AND OPTIMIZE -40 -50 -60 -70 RSSI, d. Bm -80 -90 , d. B -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 n Section A: Propagation Basics • Radio Links: Types, CDMA NETWORK PLAN AND OPTIMIZE n Section A: Propagation Basics • Radio Links: Types, key elements, configurations • Frequency and Wavelength; the RF spectrum n 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 n Section C: Propagation Models • Okumura-Hata, COST-231, Walfisch Ikegami • Confidence factors and statistical distribution • Link Budgets n Section D: Overview of Measurement Tools & Methods n Section E: Overview of Propagation Prediction Tools

CDMA NETWORK PLAN AND OPTIMIZE Section A Objectives • • • Recognize the basic 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 Propagation: Basic Elements of a Radio Link Antenna 1 Transmission Line Information Transmitter Antenna 2 Electromag. NET 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 l l power Elements and Parameters of a Radio Link Transmitter Trans. Line Antenna l l power output modulation type spectral density coding, if any l l line loss gain, bandwidth beamwidth polarization • • l path loss Antenna Trans. Line Receiver l gain, bandwidth l beamwidth l polarization l l l 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 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 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 3 x 108 M 1 The Relationship between Frequency and Wavelength F total waves 3 x 108 M 1 second Cell Examples: AMPS cell site speed =C f = 870 m. Hz. 0. 345 m = 13. 6 inches PCS-1900 site f = 1960 m. Hz. 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 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 The Radio Spectrum: Frequencies used by various Radio Systems 1000 500 300 150 AM 0. 3 100 3 0. 4 75 4 5 40 1 6 0. 7 0. 8 0. 9 1. 0 40 1. 2 30 0. 4 6 7 8 9 60 70 80 90 100 0. 06 4 5 Broadcasting 7 8 9 10 15 CB 10 Meters 14 16 18 20 22 24 26 28 30 MHz 30, 000 i. e. , 3 x 10 7 Hz 120 140 160 180 200 1 Meter 240 300 MHz 300, 000 i. e. , 3 x 10 8 Hz 1. 2 0. 03 6 3. 0 MHz VHF TV 7 -13

Mathematics concept review n Understand basic terms of the probability theory n Understand apply Mathematics concept review n Understand basic terms of the probability theory n Understand apply the Poisson, Log-Normal, Gaussian and Rayleigh signal statistical distributions n Understand concept and application of decibel unit n Determine the relationship between d. B, d. Bm, and d. Buv n Apply the logarithm and exponent functions to RF path calculations n Understand apply the slope and intercept parameters n Understand the concept and the use of polar coordinates for plotting antenna radiation patterns

Exponential and Logarithm Functions y 10^x 2^x log 2 a lg a a x Exponential and Logarithm Functions y 10^x 2^x log 2 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 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 x 1, Concepts of Slope, Intercept, and Line y Intercept Points Positive Slope Line x 1, y 1 Negative Slope Line b A a x 2, y 2 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 = (y 2 - y 1) / (x 2 - x 1) = tg A

Concepts of Slope, Intercept, and Line, continued • • • A line with positive 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 Y=mx. X+b • RF Engineering Example. – Path loss in suburban cell is presented by 1 -mile intercept of - 60 d. Bm and slope of 38 d. B/decade. Calculate Receive Signal Strength at 10 mile distance – Solution. RSS[d. Bm} = - 60 d. Bm + ( -38 d. B/decade ) = - 98 d. Bm

Polar Coordinates Concept M rm Am An rn N Polar Graph • • In 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 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 • • • k - is a variable number of successes 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

Variance and Standard Deviation • An average value of RSS across cell site does 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) 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 n RF coverage and interference may appear to be random and unpredictable in nature. Since there are many variables involved, several average properties are used n The probability density and distribution functions become useful for RF engineers n Most often used statistical distributions are: Binomial, Poisson, Gaussian, Log-Normal, Rayleigh and Ricean n Cumulative distribution functions (cdf) specifically important because they allow RF engineer to predict probability that RSS will be below or above a specified level. n 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 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 F (x) = P (X< = 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 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 1 2 3

Confidence Interval and Confidence Level f(x) Bell-shaped • pdf. Values • Area= F(x 1) Confidence Interval and Confidence Level f(x) Bell-shaped • pdf. Values • Area= F(x 1) • x 1 x x 2 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 d. B within which the signal strength measurements fall For standard normal distribution, the confidence interval is defined as RSS - k x (sigma) < = 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(x 1) x 1 • 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

Mobile Signal Strength - Log-Normal and Rayleigh Distributions Signal strength, d. Bm m(t)- local Mobile Signal Strength - Log-Normal and Rayleigh Distributions Signal strength, d. Bm 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 r 0 (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 Mobile Signal Strength - Long-Normal and Rayleigh Distribution, continued • • • The component r 0(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 r 0(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 Mobile Signal Strength - Log-Normal and Rayleigh Distributions, continued • Log-normal distribution means normal distribution in d. B units • Log-normal distribution (or shadowing) implies that measured signals in d. B 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 d. B 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

Mobile Signal Strength - Log-Normal and Rayleigh Distributions, continued • The Rayleigh distribution function Mobile Signal Strength - Log-Normal and Rayleigh Distributions, continued • The Rayleigh distribution function (cdf) is defined as follows p(r) Ricean pdf A=0 • r 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

Mobile Signal Strength - Log-Normal and Rayleigh Distributions, continued • The Ricean distribution is 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.

Decibel Concept P 1 P 2 G 1 • • • P 3 G Decibel Concept P 1 P 2 G 1 • • • P 3 G 2 P 4 L 1 The d. B (decibel) unit was introduced to describe the transfer characteristics of NETWORKworks, so when working in d. B, gains can be added instead of multiplied When two powers P 2 and P 1 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

Decibel Concept, continued • This relationship could also be expressed in d. B as: Decibel Concept, continued • This relationship could also be expressed in d. B as: If an attenuation has L loss, then its output power in watts and d. Bm is defined as Using gains and losses in d. B, the output power P 4 can be expressed as follows

Decibel Concept, continued • • Voltage or field strength at a receiving end is Decibel Concept, continued • • Voltage or field strength at a receiving end is measured in d. Bu. This notation is a simplification of decibels above 1 u. V/m which has been accepted by the Institute of Radio Engineers Relationship between voltage in d. Bu and the power associated with it in d. Bm assuming 50 ohms terminal impedance is as follows: 1 d. Bu = -107 d. Bm Relationship between a field strength in d. Bu and its received power in d. Bm assuming half-wave dipole probe, 50 ohms terminal impedance, and frequency of 850 MHz as follows: 1 dbu = -132 d. Bm 39 dbu = -93 d. Bm 32 dbu = -100 d. Bm At another frequency or using another kind of probe,

Cellular Performance Snapshot - Survey of Cellular Users Versus Cellular Application 2 -way Partable Cellular Performance Snapshot - Survey of Cellular Users Versus Cellular Application 2 -way Partable Radio n Users distribution: • public safety, government and low enforcement agencies - 66% • business and industrial - 17% • service providers and dealers - 10% n Cellular phones are preferred for: • security of conversation • mobility n Portable radios are preferred for: • voice quality • reliability

Cellular Performance Snapshot - Survey of Cellular Users, continued n DISTRIBUTION OF USERS OPINIONS Cellular Performance Snapshot - Survey of Cellular Users, continued n DISTRIBUTION OF USERS OPINIONS n What are the cellular problems? • dead spots in service area - 38% • poor signal quality - 31% • dropped calls - 24% • interference or crosstalk - 19% n Which aspects of cellular service are most important? • reliability of service - 69% • portability - 40% • roaming - 31% n How much time mobile phone is in use? • 5 to 15 minutes per day - 80% • 15 to 30 minutes - 10% n 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 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 capital investment required

Cell Site Planning - An Essential Task of Wireless System Development, continued • • 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 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, 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 d. Bu. V/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 d. B 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 d. Bu. V/m Zone of quality Cell Site Boundary Determination - Carey Contours 60 d. Bu. V/m Zone of quality coverage 39 d. Bu. V/m 32 d. Bu. V/m BS Zone of marginal coverage • • • The FCC has used R. Carey empirical (jingyande) study of TV field strength of 25 d. Bu. V/m for 50 % of locations and 50 % of time For cellular service planning, FCC made a 14 -d. B adjustment to Carey curves to make up a contour of 39 d. Bu. V/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 d. Bu. V/m

Cell Site Boundary Determination - Carey Contours, continued • In 1992 the FCC proposed Cell Site Boundary Determination - Carey Contours, continued • In 1992 the FCC proposed a new cell boundary criteria defined by 32 d. Bu. V/m and so far the dispute had not been settled • The 32 d. Bu. V/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 d. Bu. V/m will provide cell boundary with quality coverage while 32 -39 d. Bu. V/m will provide marginal coverage • The FCC has proposed an approximate formula to calculate the 32 d. Bu. V/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 • • 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 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 d. B 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 d. B 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 d. B 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 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 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, d. Section B. Overview of Propagation Mechanisms and Principles -40 -50 -60 -70 RSSI, d. Bm -80 -90 , d. B -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 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 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 d. B/decade • Reflection – reflected wave 180 out of phase – reflected wave not attenuated much – signal decays 30 -40 d. B/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 Free-Space Propagation • r Free Space spreading Loss energy intercepted by the red square is proportional to 1/r 2 1 st 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, d. B (between two isotropic antennas) = 36. 58 +20*Log 10(FMHZ)+20 Log 10(Dist. MILES ) – Path Loss, d. B (between two dipole antennas) = 32. 26 +20*Log 10(FMHZ)+20 Log 10(Dist. MILES ) – Notice the rate of signal decay: – 6 d. B 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 pe. NETWORKrated 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 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 DMILES • Analysis: – physics Reflection with Partial Cancellation Heights Exaggerated for Clarity HTFT DMILES • Analysis: – physics of the reflection cancellation predicts signal decay approx. 40 d. B per decade of distance • twice as rapid as in free-space! – observed values in real systems range from 30 to 40 d. B/decade Path Loss, d. B = 172 + 34 x Log 10 (DMILES ) - 20 x Log 10 (Base Ant. Ht. FEET) - 10 x Log 10 (Mobile Ant. Ht. FEET) Heights to Scale Comparison of Free-Space and Reflection Propagation Modes Assumptions: Flat earth, TX ERP = 50 d. Bm, @ 1950 MHz. Base Ht = 200 ft, Mobile Ht = 5 ft. Distance. MILES 1 2 4 6 8 10 15 20 FS using Free-Space. DBM -52. 4 -69. 0 -58. 4 -79. 2 -64. 4 -89. 5 -67. 9 -95. 4 -70. 4 -99. 7 -72. 4 -75. 9 -78. 4 -103. 0 -109. 0 -113. 2 FS using Reflection. DBM

Knife-Edge Diffraction • H R 1 = -H R 2 • 1 1 R Knife-Edge Diffraction • H R 1 = -H R 2 • 1 1 R R 2 1 • 2 • 0 -5 atten -10 d. B -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 d. B 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 Recognize Typical Signal Fading Rates Signal Level vs. Distance 0 -10 -20 -30 -40 1 2 One Octave of distance (2 x) 3. 16 5 6 7 8 Distance, Miles One Decade of distance (10 x) 10 We have seen how the signal fades with distance in two simplified modes of propagation: • Free-Space – 20 d. B per decade of distance – 6 d. B per octave of distance • Reflection Cancellation – 40 d. B per decade of distance – 12 d. B per octave of distance • Real-life wireless propagation fading rates fall typically between 30 and 40 d. B per decade of distance

Additional Propagation Modes Refraction by atmospheric layers Ducting by atmospheric layers >100 mi. • 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 • 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 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 d. B t

Space Diversity A Method for Combating Rayleigh Fading D • • • Signal received 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 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 Using Polarization Diversity where Space Diversity is not convenient V+H or +/ 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 • • ? ? Building Penetration Calculation Attempts using Physics Building Penetration Vehicle Penetration • • ? ? • ? Typical Penetration Losses compared to outdoor street level All metal attenuation 26 d. B Foil insulation 3. 9 d. B Concrete block wall 13 -20 d. B Ceiling Duct 1 -8 d. B Metal Stairs 5 d. B • 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 d. B @ The Reciprocity Principle Does it apply to Wireless ? -148. 21 d. B @ 1871. 25 MHz -151. 86 d. B @ 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, d. Bm -80 -90 , Section C. Propagation Models -40 -50 -60 -70 RSSI, d. Bm -80 -90 , d. B -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 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 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 , d. B

Types of Propagation Models and their Uses • • Examples of Various Model Types 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 n Simple Analytical • free space (Friis) • reflection cancellation • knife-edge diffraction n Area • Okumura-Hata • Euro/Cost-231 • Walfisch-Betroni/Ikegami n Point-to-Point • Ray Tracing - Lee- Method, others • Tech-Note 101 • Longley-Rice, Biby-C n Local Variability • Rayleigh Distribution • Normal Distribution • Joint probability Techniques

General Principles of Area Models -50 +90 -60 +80 -70 +70 • +60 Field General Principles of Area Models -50 +90 -60 +80 -70 +70 • +60 Field Strength, +50 d. Bu. V/m -80 RSSI, -90 d. Bm -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, d. B = The Okumura Model: Parent of Hata and Euro/Cost-231 Models Path Loss, d. B = LFS + Amu(f, d) - G(Ht) - G(Hr) - Garea LFS = 32. 26 + 20 Log 10(d. MILES) + 20 Log 10 (f. MHZ) 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 = 20 Log 10 (Ht / 200) for Ht = 10 m to 1000 m G(Hr) = gain due to mobile station antenna height = 10 Log 10 (Hr / 3) for Hr = less than 3 m 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 (d. B) = 69. 55 + 26. 16 log (F) -13. Okumura-Hata Model A (d. B) = 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 m. Hz (800 -900 m. Hz) Distance between base station and terminal in km Effective height of base station antenna in m Environment correction factor C = 0 d. B - 5 d. B - 10 d. B - 17 d. B = = Dense Urban Suburban Rural

Euro/COST-231 -HATA Model A (d. B) = 46. 3 + 33. 9*log. F -13. Euro/COST-231 -HATA Model A (d. B) = 46. 3 + 33. 9*log. F -13. 82*log. H + (44. 9 -6. 55*log. H)*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 m. Hz. Tower Statistical Propagation Models Typical Results including Environmental Correction COST-231/Hata f =1900 m. Hz. Tower Height (meters) EIRP (watts) C, d. B Range, km Dense Urban Suburban Rural 30 30 30 50 200 200 0 -5 -10 -17 2. 52 3. 50 4. 8 10. 3 f = 870 m. Hz. Tower Height (meters) EIRP (watts) C, d. B Range, km Dense Urban Suburban Rural 30 30 30 50 200 200 -2 -5 -10 -26 4. 0 4. 9 6. 7 26. 8 Okumura/Hata

Walfisch-Betroni/Walfisch-Ikegami Models • Propagation in built-up portions of cities is dominated by ray diffraction 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 d. Bm -30 d. Bm -40 d. Bm -50 d. Bm -60 d. Bm -70 d. Bm -80 d. Bm -90 d. Bm -100 d. Bm -110 d. Bm -120 d. Bm 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 W 1 Receiving Antenna W 2 d 1 Receiving Antenna Urban Out-of-Sight Propagation Model W 1 Receiving Antenna W 2 d 1 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 d 1 = BS and street corner separation d 2 = MS and street corner separation

Statistical Techniques Distribution Statistics Concept Signal Strength Predicted vs. Observed • An area model 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 d. Bm 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 , d. B

Statistical Techniques Practical Application of Distribution Statistics • • Percentage of Locations where Observed 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, d. Bm • 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 d. B which will give us that % coverage confidence 10% of locations exceed this RSSI 50% 90% Distance Occurrences Median Signal Strength Normal Distribution RSSI , d. B

Area Availability and Probability of Service at Cell Edge • Statistical View of Cell 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% Statistical Techniques Example of Application of Distribution Statistics Cumulative Normal Distribution • 100% 90% 80% 70% • 75% 60% 50% • 40% 30% 20% 0. 675 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 d. Bm 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 d. B. 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 d. Bm – -95 + (. 675 x 10 ) = -88 d. Bm – So, design for a median signal strength of -88 d. Bm!

Statistical Techniques Normal Distribution Graph & Table for Convenient Reference Cumulative Normal Distribution 100% 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. 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% 75% 80% 95% 99. 9% 99. 999%

Building Penetration Statistical Characterization Building Penetration Vehicle Penetration • • Typical penetration Losses, d. Building Penetration Statistical Characterization Building Penetration Vehicle Penetration • • Typical penetration Losses, d. B compared to outdoor street level Environment Type Dense Urban Bldg. Suburban Bldg. Rural Bldg. Typical Vehicle Median Std. Loss, Dev. d. B , d. B 20 15 10 10 8 8 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 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 Composite Probability of Service Calculating Fade Margin for Link Budget • Example Case: Outdoor is 8 d. B. , and penetration loss is 8 d. B. 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 d. B Cumulative Normal Distribution On cumulative normal distribution curve, 75% probability is 0. 675 above median. Fade Margin required = (11. 31) (0. 675) = 7. 63 d. B. 100% Composite Probability of Service 90% 80% 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 Calculating Required Fade Margin Building Out. Composite Penetration Door Total Environment Type Area Median Std. Fade Availability Loss, Dev. Margin Target, % d. B , d. B 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

Link Budget Models • • • Link Budgets trace power expenditures along path from 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 Transmitter Trans. Line +43 d. Bm TX output -3 = +40 +13 = +53 d. B antenna gain d. Bm into line -3 = -95 Trans. Line d. B path attenuation d. Bm dipole antenna +13 = -92 Antenna d. B antenna gain d. Bm ERP -158 = -105 Antenna d. B line efficiency d. Bm to antenna d. B line efficiency d. Bm to receiver Receiver Downlink Uplink

CDMA Reverse Link Budget Model Example Term or Factor MS TX power (d. Bm) CDMA Reverse Link Budget Model Example Term or Factor MS TX power (d. Bm) MS TX power (watts) MS antenna gain and body loss (d. Bi) MS EIRP (d. Bm) MS EIRP (watts) Fade Margin (d. B) Soft Handoff Gain (d. B) Receiver Interference Margin (d. B) Building Penetration Loss (d. B) BTS RX antenna gain (d. Bi) BTS cable loss (d. B) k. TB (d. Bm/14. 4 k. Hz) BTS noise figure (d. B) Eb/Nt (d. B) BTS RX Sensitivity Uplink Path Loss (d. B) Given 23. 0 d. Bm Budget Formula 23. 0 d. Bm 0. 2 W A -7. 6 d. B 4. 0 d. B -3. 0 d. B -20. 0 d. B 17. 0 d. Bi -3. 0 d. B B C D E F G H 0. 2 W 0. 0 d. Bi -132. 4 6. 4 d. B 6. 2 d. B -119. 8 d. B 130. 2 d. B 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 (d. Bm) CDMA Forward Link Budget Model Example Term or Factor BTS TX power (d. Bm) BTS % Power for traffic channels No. of traffic channels in use (chs. ) BTS cable loss (d. B) BTS TX antenna gain (d. Bi) BTS EIRP/traffic channel (d. Bm) BTS EIRP/traffic channel (watts) Fade margin (d. B) Receiver interference margin (d. B) Building Penetration Loss MS antenna gain and body loss (d. Bi) MS RX sensitivity (NF 10. 5 d. B, Eb/No 5 d. B) Downlink Path Loss (d. B) Given 44. 0 d. Bm Budget Formula 44. 0 d. Bm 25. 1 W -7. 6 d. B -3. 0 d. B -20. 0 d. Bi -116. 8 d. Bm A 130. 2 d. B A+B+C+D+E-F 25. 67 W 74% 19 -3. 0 d. B 17. 0 d. Bi B C D E F

CDMA Link Budget Conclusions Reverse (Uplink) Term or Factor MS TX power (d. Bm) CDMA Link Budget Conclusions Reverse (Uplink) Term or Factor MS TX power (d. Bm) MS TX power (watts) MS antenna gain and body loss (d. Bi) Given Forward (Downlink) Budget 23. 0 d. Bm 0. 2 W 0. 0 d. Bi MS EIRP (d. Bm) 23. 0 d. Bm MS EIRP (watts) 0. 2 W Fade Margin (d. B) -7. 6 d. B Soft Handoff Gain (d. B) 4. 0 d. B Receiver Interference Margin (d. B) -3. 0 d. B Building Pe. NETWORKration Loss (d. B) -20. 0 d. B BTS RX antenna gain (d. Bi) 17. 0 d. Bi BTS cable loss (d. B) -3. 0 d. B k. TB (d. Bm/14. 4 k. Hz) -132. 4 BTS noise figure (d. B) 6. 4 d. B Eb/Nt (d. B) 6. 2 d. B BTS RX Sensitivity Uplink Path Loss (d. B) • • -119. 8 d. B 130. 2 d. B Term or Factor BTS TX power (d. Bm) BTS % Power for traffic channels No. of traffic channels in use (chs. ) BTS cable loss (d. B) BTS TX antenna gain (d. Bi) BTS EIRP/traffic channel (d. Bm) Given 44. 0 d. Bm 25. 67 W 74% Budget 19 -3. 0 d. B 17. 0 d. Bi 44. 0 d. Bm BTS EIRP/traffic channel (watts) Fade margin (d. B) Receiver interference margin (d. B) Building Pe. NETWORKration Loss MS antenna gain and body loss (d. Bi) MS RX sensitivity (NF 10. 5 d. B, Eb/No 5 d. B) 25. 1 W -7. 6 d. B -3. 0 d. B -20. 0 d. Bi -116. 8 d. Bm Downlink Path Loss (d. B) 130. 2 d. B 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, Section D. Overview of Propagation Measurement Tools and Methods -40 -50 -60 -70 RSSI, d. Bm -80 -90 , d. B -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 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 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, 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, Cell. Scope • MLJ • CW test transmitters, receivers • Qualcomm • Mobile Diagnostic Monitor, -1900 QCP • SAFCO • Smart. SAM , Smart. SAM Plus*, PROMAS*, CDMA OPAS 32 • 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 – 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 (d. Bu. V/m) – not just raw RSSI d. Bm 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, d. Bm Section E. Overview of Propagation Prediction Tools -40 -50 -60 -70 RSSI, d. Bm -80 -90 , d. B -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 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 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) 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 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 • Pla. NETWORK (Unix) • LCC • Cell. Cad • ANETWORK (Unix) (DOS PC) • CNETWORK • Wings • Solutions (Unix) (mainframe) • Com. Search • 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 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 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 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 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 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 d. B <17 d. B <14 d. B -20 d. Bm -30 d. Bm -40 d. Bm -50 d. Bm -60 d. Bm -70 d. Bm -80 d. Bm -90 d. Bm -100 d. Bm -110 d. Bm -120 d. Bm

Structured Survey of Tool Features (continued) Popular Advanced Features • Accepts measurement input, can Structured Survey of Tool Features (continued) Popular Advanced Features • Accepts measurement input, can automatically A 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 Pred. Meas Mean -76 -72 Std. Dv 9 12 Samples 545 Area Name: DALLAS Initial Service Date: Subs: 100, 000 Site Name Site # Latitude Longitude. Type Capacity SITE - 1 SITE - 2 SITE - 3 SITE - 4 SITE - 5 A 1 A 2 A 3 A 4 A 5 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 S 322 S 211 S 332 S 11 01 77 37 91 8 8 Total Capacity (Erlangs)221 7 9 6 1 3 2 2 4 8 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 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 26 X 26 Y 26 Z 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 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 d. Bm Cell 76 -97 d. Bm C/I +15 d. B C/I Pct. of Area >20 d. B 93. 0% <20 d. B 7. 0% <17 d. B 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 Propagation Farewell: A Final Reminder about Cell Size A Picture to Remember -40 -50 -60 -70 RSSI, d. Bm -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 d. B and 40 d. B (that is 1000 -10, 000 times!) • to decrease coverage distance by half requires a power decrease of roughly 10 d. B. (that is 10 times) • individual path obstructions and high spots also can easily cause changes of +/- 20 d. B. or more in signal level at any spot

The end ! The end !