EE359 – Lecture 2 Outline
Announcements1st HW posted by tonight, due next Friday
at 5pm.Discussion section starts next week,
day/time TBATA OHs start next week (Thu 5-6 pm, Fri 1-
2pm, Packard 109. Email OH : Thu 8-9 pm and Fri 10-11 am.
Review of Last Lecture
TX and RX Signal ModelsPath Loss Models
Free-space and 2-Ray ModelsGeneral Ray TracingSimplified Path Loss ModelEmpirical ModelsmmWave Models
Lecture 1 ReviewCourse InformationWireless VisionTechnical ChallengesCurrent/Next-Gen Wireless
SystemsSpectrum Regulation and
StandardsEmerging Wireless SystemsEmerging systems can be covered in a bonus lecture
Propagation Characteristics
Path Loss (includes average shadowing)
Shadowing (due to obstructions)Multipath Fading
Pr/Pt
d=vt
PrPt
d=vt
v Very slow
SlowFast
Path Loss ModelingMaxwell’s equations
Complex and impracticalFree space and 2-path models
Too simpleRay tracing models
Requires site-specific informationSimplified power falloff models
Main characteristics: good for high-level analysis
Empirical ModelsDon’t always generalize to other
environments
Free Space (LOS) Model
Path loss for unobstructed LOS path
Power falls off :Proportional to 1/d2
Proportional to l2 (inversely proportional to f2) This is due to the effective aperature
of the antenna
d=vt
Two Ray Model
Path loss for one LOS path and 1 ground (or reflected) bounce
Ground bounce approximately cancels LOS path above critical distance
Power falls off Proportional to d2 (small d)Proportional to d4 (d>dc) Independent of l (fc)
Two-path cancellation equivalent to 2-element array, i.e. the effective aperature of the receive antenna is changed.
General Ray TracingModels signal components as
particlesReflectionsScatteringDiffraction
Requires site geometry and dielectric properties
Easier than Maxwell (geometry vs. differential eqns)Computer packages often used
Reflections generally dominate
10-ray reflection model explored in HW
Simplified Path Loss Model
82,0
ddKPP tr
Used when path loss dominated by reflections.
Most important parameter is the path loss exponent , determined empirically.
Empirical Channel Models
Cellular Models: Okumura model and extensions: Empirically based (site/freq specific), uses
graphsHata model: Analytical approximation to
OkumuraCost 231 Model: extends Hata to higher
freq. (2 GHz)Multi-slope modelWalfish/Bertoni: extends Cost 231 to
include diffraction
WiFi channel models: TGn Empirical model for 802.11n developed
within the IEEE tandards committee. Free space loss up to a breakpoint, then slope of 3.5. Breakpoint is empirically-based.
Commonly used in cellular and WiFi system simulations
mmWave: What’s the big deal?
All existing commercial systems fit into a small fraction of the mmWave band
mmWave Propagation (60-100GHz)
Channel models immatureBased on measurements, few accurate
analytical models Path loss proportion to l2 (huge) Also have oxygen and rain absorbtion
l is on the order of a water molecule
mmWave systems will be short range or require “massive MIMO”
mmWMassiveMIMO
Main Points Path loss models simplify Maxwell’s
equations Models vary in complexity and
accuracy Power falloff with distance is
proportional to d2 in free space, d4 in two path model
Main characteristics of path loss captured in simple model Pr=PtK[d0/d]
Empirical models used in simulations
mmWave propagation models still immaturePath loss large due to frequency, rain,
and oxygen
