Transcript Lecture 2: Radio Wave Propagation

Lecture 3:
Propagation Modelling
Anders Västberg
08-790 44 55
[email protected]
Ionospheric propagation
[Slimane]
Refraction in an ionospheric
layer
[Slimane]
Electron density profile
[Slimane]
Ray paths
Cellular Networks
• Network organised in cells
• Each access point has a set
of channels to service the
users within the cell
• The set of channels can be
reused when the signal to
interference ratio is low
enough.
Macrocells
• Give services in urban, suburban and rural
areas. The cell radii varies from about 1
km to many tens of km.
• Few users per area unit.
• Base stations antennas are mounted on
high buildings or on masts to get better
coverage.
Microcells
• In urban or suburban areas
• Cell radii is approximately 500 m
• Very high traffic density (many users per
area unit).
• Antennas mounted lower than the
buildings around it to decrease the cell
coverage are
• More cells/unit area can services more
users.
Indoor Cells (Picocells)
• High data rates and high traffic densities
for both mobile and fixed users
• Coverage area influenced by
– Layout of the building
– Construction material (wood transparent to
radio waves, well reinforced concrete is not).
– Shape of rooms
Propagation modelling
• To predict coverage areas in mobile
cellular telephone systems, simple
propagation models are needed.
– Empirical methods
– Physical models
– Hybrid methods
Measurements
[Saunders, 1999]
Emperical methods
• Models are usually based on actual path loss
measurements.
– Curve fitting is used to obtain an analytical function
for the model.
– Parameters are given by: distance, frequency,
antenna heights, distance to nearest building.
• Validity of the model may be limited (dependent
on the environment)
• Models are practical and easy to use but not
very accurate.
Physical Models
• A physical model needs a very detailed
description of the terrain and other clutter.
– Large amount of data needed.
– Excessive computational effort needed.
• The important parameter for the macrocell
designer is the area covered, not the field
strength at particular locations.
Computerised Planning
Tools
• The enormous increase in the need to
plan cellular systems accurately and
quickly
• The development of fast, affordable
computing resources
• The development of geographical
information systems
• Example:
– TEMS CellPlanner, Ericsson AB
Empircal Models for Macro
Cells
•
•
•
•
Power Law models
Clutter factor models
Okumura-Hata model
Cost 231-Hata Model
Plane Earth Loss
[Saunders, 1999]
Physical Models for Macro
Cells
•
•
•
•
•
Ikegami Model
Rooftop diffraction
Flat Edge model
Walfisch-Bertoni model
COST 231/Walfisch-Ikegami model
Models for Micro Cells
• Dual Slope model (empirical model)
• Physical Models
– Two-ray model
– Street canyon models
– Non-line-of-sight models
Picocells
•
•
•
•
•
•
Wall and floor factor models
COST231 Multi-wall model
Ericsson model
COST 231 Line-of-sight model
Floor Gain Models
COST 231 Non-Line-of Sight model
Physical Model:
Two Ray Model
[Saunders, 1999]
Two-Ray Model
 jkr2 2
1    e
e

R

L  4  r1
r2
2
 jkr1
R is the Fresnel reflection coefficient
Raytrace
[Saunders, 1999]
Indoor models