Download ChannelModelling

CHANNEL MODELLING
Archana K B
Sr. Asst. professor
ECE Dept.
VNR VJIET, HYD.
What U want to know is, what U know – No information
conveyed
What U want to know is, what U don’t know,
but u don’t know what U want to know – Information
useless
What U want to know is, what U don’t know,
but u know what U don’t know – Information conveyed
Hence purpose of communication
or communication system is:
To convey information
Mathematical Modeling of a Communication Channel
Contents
1. Types of channels
2. Mathematical Models for Communications Channels
3. Mathematical Models for Wireless Channels
4. Multipath Fading Channels
5. Types of Multipath Fading Channels
6. Fading channel manifestations
7. Fading channel Mitigations
8. Matlab support for channel models
what is a channel or more precisely
what is communication channel?
1. Types and Characteristics of
channels:
• Wire line channels: operates at frequency few kHz to
several hundreds of kHz.
• Fiber Optical Channels: provides bandwidth in the
magnitude several times higher than that of wire line
channel
• Wireless Electromagnetic Channels: operates in the range
of 10kHz to =~ 100 GHz, this is further categorized as long
wave radio, short wave radio, microwave radio as they
operates in radio frequency they are also known as ‘radio’
or ‘radio channel’.
• Under Water Acoustic Channels: operated at extremely
low frequencies.
• Storage Channels: like magnetic tapes, magnetic disks etc.
2. Mathematical Models for Communications
Channels
• Description of the channel models that are frequently used to
characterize many of the physical channels that we encounter in practice
are:
2.a. The Additive Noise Channel
• The simplest mathematical model for a communication channel is the
additive noise channel. In this model the transmitted signal s(t) is
corrupted by an additive random noise process n(t). Physically, the
additive noise process may arise from electronic components and
amplifiers at the receiver of the communication system, or from
interference encountered in transmission, as in the case of radio signal
transmission.
• r(t) = as(t)+n(t) where a is the attenuation factor
2.b. The Linear Filter Channel
• In some physical channels such as wireline telephone
channels, filters are used to ensure that the transmitted
signals do not exceed specified bandwidth limitations
and, thus, do not interfere with one another. Such
channels are generally characterized mathematically as
linear filter channels with additive noise. Hence, if the
channel input is the signal s(t), the channel output is the
signal
• where h(t) is the impulse response of the linear filter and denotes
convolution.
2.c. The Linear Time-Variant Filter Channel
For an input signal s(t), the channel output signal is
A good model for multipath signal propagation through physical
channels, such as the ionosphere (at frequencies below 30 MHz)
and mobile cellular radio channels, is a special case of above
Equation in which the time-variant impulse response has the
form
where the {ak(t)} represent the possibly time-variant attenuation factors for the L
multipath propagation paths.
Hence, the received signal consists of L multipath components,
where each component is attenuated by {ak} and delayed by {tk}.
3. Mathematical Models for Wireless Channels
There are three broad classes of channel phenomena of Interest
1. Multipath Fading:
constructive and destructive interference caused by multiple
TX-RX paths with different lengths arriving from different
directions.
Signal envelope varies widely over 30 dB in the span of a few
wavelengths in distance
Multipath fading is used for physical layer modem design such
as coder, modulator, interleaver, etc
2. Shadowing
 Short-term average variation or large-scale signal variation
 caused by local changes in terrain features or man-made
obstacles (e.g. blockage)
 Shadowing is used for power control design, 2nd order
interference and TX power
 Analysis and more detailed link budget and cell coverage
analysis
•
•
Path Loss Model
Long-term or large-scale average signal level
depends on the distance between TX and RX
Path loss model is used for system planning, cell coverage and
link budget
4. Multipath Fading Channels
Fading channels are useful models of real-world
phenomena in wireless communications. These
phenomena include multipath scattering effects,
time dispersion, and Doppler shifts that arise from
relative motion between the transmitter and
receiver.
Why Multipath Fading Channels ?
• In the study of communication systems the classical (ideal) additive white
Gaussian noise (AWGN) channel, is not sufficient to model a practical
channel.
• If a radio channel’s propagating characteristics are not specified, one
usually infers that the signal attenuation versus distance behaves as if
propagation takes place over ideal free space. Thus over optimizing the
channel.
• In a wireless mobile communication system, a signal can travel from
transmitter to receiver over multiple reflective paths; this phenomenon is
referred to as multipath propagation. The effect can cause fluctuations in
the received signal’s amplitude, phase, and angle of arrival, giving rise to
the terminology multipath fading which is dynamic, random and relevant
to the environment.
• By taking these hostile conditions into account, it is a challenge to
accurately model the channel mathematically in order to make the model
more realistic, leading to higher performance of the communication
system.
5. Types of Multipath Fading Channels
• Typically, the fading process is characterized
by a Rayleigh distribution for a non line-ofsight path and a Rician distribution for a lineof-sight path.
• A number of other probability distributions
functions are also used to characterize
different types of channels. Below is a list of
distribution functions and the environment
they model.
5.a. Rayleigh fading Channel
5.b. Rician fading Channel
6. Fading channel manifestations
Two types of fading effects that characterize mobile communications: large-scale and
small-scale fading.
Fading channel manifestations
Relationships among the channel correlation
functions and power density functions.
Small-scale fading: mechanisms, degradation
categories, and effects
7. Fading channel Mitigations
Impact of Fading channels on
Wireless communication systems
8. Matlab support for channel models
Communication toolbox of Matlab supports
these types of channels:
• Additive white Gaussian noise (AWGN)
channel
• Fading channel
• Binary symmetric channel, for binary signals
• MATLAB support for channel Modelling
Radio Propagation and
Propagation Path-Loss Models
Refl ection, diffraction and scattering of radio wave.
Propagation Path-Loss Models
• Propagation path-loss models play an important role in the design of
cellular systems to specify key system parameters such as
transmission power, frequency, antenna heights, and so on.
• Several models have been proposed for cellular systems operating in
different environments (indoor, outdoor, urban, suburban, rural).
• Propagation models are used to determine the number of cell sites
required to provide coverage for the network. Initial network design
typically is based on coverage. Later growth is engineered for
capacity.
• The propagation model is also used in other system performance
aspects including handoff optimization, power level adjustments, and
antenna placements.
Widely used empirical models
• The Okumura/Hata model has been used extensively
both in Europe and NA for cellular systems.
• The COST 231 model has been recommended
by the European Telecommunication Standard Institute
(ETSI) for use in (PCN/PCS).
• International Mobile Telecommunication-2000 (IMT2000) for the indoor office environment, outdoor
to indoor pedestrian environment, and vehicular
environment.
The Okumura/Hata model
• Okumura analyzed path-loss characteristics based on a
large amount of experimental data collected around
Tokyo, Japan.
• Applied several correction factors for other
propagation conditions, such as:
a. Antenna height and carrier frequency
b. Suburban, quasi-open space, open space,
or hilly terrain areas
c. Diffraction loss due to mountains
d. Sea or lake areas
e. Road slope
• Hata derived empirical formulas for the median path
loss (L50) to fit Okumura curves. Hata’s equations are
classified into three models such TYPICAL URBAN,
TYPICAL SUBURBAN,RURAL.
COST 231 Model
• This model is a combination of empirical and
deterministic models for estimating the path
loss in an urban area over the frequency range
of 800 MHz to 2000 MHz.
• The model is used primarily in Europe for the
GSM 1800 system.
IMT-2000 Models
• The operating environments are identified by appropriate
subsets consisting of indoor office environments, outdoor to
indoor and pedestrian environments, and vehicular (moving
vehicle) environments.
• The key parameters of the IMT-2000 propagation models are:
a. Delay spread, its structure, and its statistical variation
b. Geometrical path loss rule
c. Shadow fading margin
d. Multipath fading characteristics (e.g., Doppler
spectrum, Rician vs.Rayleigh for envelope of channels)
e. Operating radio frequency