Introduction What is communication ? Significance of guided and unguided communication Wireless / Mobile Communication Radio Propagation Effects

Propagation Scenario 2

Mobile Radio Propagation Large Scale Propagation Effects Distance dependent loss Reflection Diffraction Scattering Useful in estimating radio coverage Small Scale Propagation Effects Rapid fluctuations of received signal strength over short durations or short distances Multipath propagation – time dispersive Mobility – frequency dispersive

Large-scale /small-scale propagation

Propagation phenomena 5

1 – 2 Km 50-100 6

Free space propagation model - LOS Pr(d) = Pt Gt Gr 2 / (4d)2 L  Pr(d0)(d0/d)2 Assumes far-field (Fraunhofer region) Far field distance df >> D and df >>  , where D is the largest linear dimension of antenna  is the carrier wavelength df = 2D2/  do > df Fraunhofer region/far field (1m -1 km) No interference, no obstructions Effective isotropic radiated power – EIRP = Pt Gt Effective radiated power – ERP Antenna gains  dBi, dBd Path loss PL(dB) = 10log (Pt/Pr)

Radio Propagation Mechanisms Reflection Propagating EM wave impinges on an object which is large as compared to its wavelength - e.g., the surface of the Earth, buildings, walls, etc. Conductors & Dielectric materials (refraction) Diffraction Radio path between transmitter and receiver is obstructed by a surface with sharp irregular edges Waves bend around the obstacle, even when LOS (line of sight) does not exist Fresnel zones Scattering Objects smaller than the wavelength of the propagating wave - e.g. foliage, street signs, lamp posts “Clutter” is small relative to wavelength

Reflection q qr qt Perfect conductors reflect with no attenuation Light on the mirror Dielectrics reflect a fraction of incident energy “Grazing angles” reflect max* Steep angles transmit max* Light on the water Reflection induces 180 phase shift Why? See yourself in the mirror Reflected field intensity Fresnel reflection coefficient  Brewster angle   = 0 ? q qr qt

Classical 2-ray Ground reflection model

2-Ray Model For d > do, the free space propagating field  E(d,t) = (Eodo/d) cos { c(t – d/c)} ELOS(d’,t) = (Eodo/d’) cos { c(t – d’/c)} Eg(d’’,t) =  (Eodo/d’’) cos { c(t – d’’/c)} i = o  Eg =  Ei ; Et = (1+) Ei

2-Ray Model For small grazing angles, assuming perfect horizontal E-field polarization and ground reflection , | =-1, Et = 0 |ETOT| = |ELOS + Eg | ETOT(d,t) = (Eodo/d’) cos { c(t – d’/c)} +(-1)(Eodo/d’’) cos { c(t – d’’/c)}

Method of images

2-Ray model Using method of images, Path difference  = d’’ – d’ = {(ht+hr)2+d2} 1/2 –{(ht-hr)2+d2} 1/2 If d >> (ht+hr) ; using Taylor series expansion,  = d’’ – d’  2hthr /d  = 2 /  =  c / c and d = / c = /2 fc

2-Ray model At time t = d’’/c ; |ETOT(d) | ETOT(d, t) = (Eodo/d’) cos { c((d’’ – d’)/c)} - (Eodo/d’’) cos0 = (Eodo/d’)   - (Eodo/d’’)  (Eodo/d) [   - 1] |ETOT(d) | = { (Eodo/d)2 cos ( - 1)2 + (Eodo/d)2 sin ( )2 } ½

2-Ray model |ETOT(d) |= { (Eodo/d)2 cos ( - 1)2 + (Eodo/d)2 sin ( )2 } ½ |ETOT(d) |= (Eodo/d) (2-2cos  ) ½ = (2Eodo/d) sin(  /2) sin(  /2)  (  /2) < 0.3 rad  d > 20 ht hr /  ETOT(d)  (2Eodo/d) (2  ht hr / d)  k / d 2 V/m Pr= Pt Gt Gr (ht hr )2/ d 4 PL(dB) = 40 log d – ( 10logGt + 10logGr + 20loght + 20loghr )

2-Ray model Summary For small T-R separation  ETOT(d,t) = (Eodo/d’) cos { c(t – d’/c)} +(-1)(Eodo/d’’) cos { c(t – d’’/c)} For large T-R separation  ETOT(d)  (2Eodo/d) (2  ht hr / d)

2-Ray model Summary For large T-R separation, ETOT(d)  k / d 2 V/m The free space power is related to square of the electric field and hence, Pr= Pt Gt Gr (ht hr )2/ d 4 Path Loss in dB  PL(dB) = 40 log d – ( 10logGt + 10logGr + 20loght + 20loghr )

Diffraction Diffraction occurs when waves hit the edge of an obstacle “Secondary” waves propagate into the shadowed region Water wave example Diffraction is caused by the propagation of secondary wavelets into a shadowed region. Excess path length results in a phase shift The field strength of a diffracted wave in the shadowed region is the vector sum of the electric field components of all the secondary wavelets in the space around the obstacle. Huygen’s principle: all points on a wavefront can be considered as point sources for the production of secondary wavelets, and that these wavelets combine to produce a new wavefront in the direction of propagation. 19

Diffraction geometry 20

Fresnel Screens Path difference between successive zones = /2 21

Fresnel Zones

Fresnel Zone Clearance

Fresnel Zone Clearance

Fresnel Zone Clearance A rule of thumb used for line-of-sight microwave links  55% of the first Fresnel zone to be cleared.

Fresnel Zone Clearance A rule of thumb used for line-of-sight microwave links  55% of the first Fresnel zone to be cleared.

Diffraction geometry 27

Diffraction geometry 28

Diffraction Parameter Assuming h << d1, d2 & h >>, Excess path length   h2 (d1+ d2 )/(2 d1d2) Phase difference  = 2/ =  2 / 2 ?  =+ and considering tan   ,   h (d1+ d2 )/(d1d2) Fresnel-Kirchoff diffraction parameter   = h {2(d1+ d2 )/(d1d2)}1/2 =  {2 d1d2 /((d1+ d2 ))}1/2

Fresnel diffraction geometry 30

Diffraction Gain Electric Field Strength Ed Ed = Eo F() F()  complex Fresnel integral evaluated using tables / graphs Diffraction gain Gd(dB) = 20 log |F()|

Approximate solution for Gd(dB) Gd(dB) = 20log(0.5-0.62  ) -1  0 Gd(dB) = 20log{0.5exp(-0.95  )} 0  1 Gd(dB) = 20log{0.4-[0.1184-(0.38-0.1 2 )]1/2} 1  2.4 Gd(dB) = 20log{0.225/  }  > 2.4

Knife-edge diffraction loss 33

Multiple knife-edge diffraction 34

Scattering Rough surfaces Lamp posts and trees, scatter energy in all directions Critical height for roughness  hc = /(8 sini) Smooth if its minimum to maximum protuberance h < hc For rough surfaces, Scattering loss factor S to be multiplied with surface reflection coefficient, rough = S ; S is a function of , h, i Nearby metal objects (street signs, etc.) Usually modeled statistically Large distant objects Analytical model: Radar Cross Section (RCS) Bistatic radar equation 35

Measured results 36

Measured results 37

Propagation Models Large scale models predict behavior averaged over distances >>  Function of distance & significant environmental features, roughly frequency independent Breaks down as distance decreases Useful for modeling the range of a radio system and rough capacity planning, Path loss models, Outdoor models, Indoor models Small scale (fading) models describe signal variability on a scale of  Multipath effects (phase cancellation) dominate, path attenuation considered constant Frequency and bandwidth dependent Focus is on modeling “Fading”: rapid change in signal over a short distance or length of time. 38

Free Space Path Loss Path Loss is a measure of attenuation based only on the distance to the transmitter Free space model only valid in far-field; Path loss models typically define a “close-in” point d0 and reference other points from there: 39

Log-distance Path Loss Log-distance generalizes path loss to account for other environmental factors  Choose a d0 in the far field. Measure PL(d0) or calculate Free Space Path Loss. Take measurements and derive n empirically. n 40

Typical large-scale path loss 41

Log-Normal Shadowing Model Shadowing occurs when objects block LOS between transmitter and receiver A simple statistical model can account for unpredictable “shadowing” PL(d)(dB)=PL(d)+X Where X is a zero-mean Gaussian RV (in dB) (distributed log normally), with standard deviation of  (in dB)  is usually from 3 to 12 dB 42

Longley-Rice Model (ITS Irregular terrain model) Point-to-point from 40MHz to 100GHz. Predicts median transmission loss, Takes terrain into account, Uses path geometry, Calculates diffraction losses, forward scatter theory Inputs: Frequency Path length Polarization and antenna heights Surface refractivity Effective radius of earth Ground conductivity Ground dielectric constant Climate Disadvantages Does not take into account details of terrain near the receiver Does not consider Buildings, Foliage, Multipath Original model modified by Okamura for urban terrain 43

Longley-Rice Model OPNET implementation 44

Durkin’s Model It is a computer simulator for predicting field strength contours over irregular terrain. Line of sight or non-LOS Edge diffractions using Fresnel zone Disadvantage  cannot adequately predict propagation effects due to foliage, building, and it cannot account for multipath propagation. 45

2-D Propagation Raster data Digital elevation models (DEM) United States Geological Survey (USGS) 46

Algorithm for line of sight (LOS) Line of sight (LOS) or not 47

Multiple diffraction computation 48

Empirical Models Commonly used in cellular system simulations Okumura model Curves based on extensive measurements(site/freq specific) Awkward (uses graphs) Hata model Analytical approximation to Okumura model Cost 231 Model: Extends Hata model to higher frequency (2 GHz) Walfish/Bertoni: Cost 231 extension to include diffraction from rooftops Commonly used in cellular system simulations

Okumura Model It is one of the most widely used models for signal prediction in urban areas, and it is applicable for frequencies in the range 150 MHz to 1920 MHz Based totally on measurements (not analytical calculations) Applicable in the range: 150MHz to ~ 2000MHz, 1km to 100km T-R separation, Antenna heights of BS upto 200m, MS upto 3m 50

Okumura Model The major disadvantage with the model is its low response to rapid changes in terrain, therefore the model is fairly good in urban areas, but not as good in rural areas. Common standard deviations between predicted and measured path loss values are around 10 to 14 dB. 51

Okumura –Correction factor GAREA 52

Hata Model Empirical formulation of the graphical data in the Okamura model. Valid 150MHz to 1500MHz, Used for cellular systems The following classification was used by Hata: ■Urban area ■Suburban area ■Open area 53

Hata Model Urban area Suburban area Open area - E - E 54

PCS Extension of Hata Model COST-231 Hata Model, European standard Higher frequencies: up to 2GHz Smaller cell sizes Lower antenna heights f >1500MHz Metropolitan centers Medium sized city and suburban areas 55

Indoor Propagation Models The distances covered are much smaller The variability of the environment is much greater Key variables: layout of the building, construction materials, building type, where the antenna mounted, …etc. In general, indoor channels may be classified either as LOS or OBS with varying degree of clutter The losses between floors of a building are determined by the external dimensions and materials of the building, as well as the type of construction used to create the floors and the external surroundings. Floor attenuation factor (FAF) 56

Signal Penetration into Buildings RF penetration has been found to be a function of frequency as well as height within the building. Signal strength received inside a building increases with height, and penetration loss decreases with increasing frequency. Walker’s work shows that building penetration loss decrease at a rate of 1.9 dB per floor from the ground level up to the 15th floor and then began increasing above the 15th floor. The increase in penetration loss at higher floors was attributed to shadowing effects of adjacent buildings. Some devices to conduct the signals into the buildings 57

Repeater Extend coverage range Directional antenna or distributed antenna systems

Ray Tracing and Site Specific Modeling Site specific propagation model and graphical information system. Ray tracing. Deterministic model. Data base for buildings, trees, etc. SitePlanner 59

Simple path loss/shadowing model: Find Pr: Find Noise power:

SINR: Without shadowing ( = 0), BPSK works 100%, 16QAM fails all the time. With shadowing (s= 6dB): BPSK: 16 QAM 75% of users can use BPSK modulation and hence get a PHY data rate of 10 MHz · 1 bit/symbol ·1/2 = 5 Mbps Less than 1% of users can reliably use 16QAM (4 bits/symbol) for a more desirable data rate of 20 Mbps. Interestingly for BPSK, w/o shadowing, we had 100%; and 16QAM: 0%!