1.
Channel Model
• A channel model is a mathematical representation of the effects
of a communication channel through which wireless signals are
propagated.
• the channel model is the impulse response of the channel
medium in the time domain or its Fourier transform in the
frequency domain.
• Channel models can be classified in four categories:
1. Path loss
2. Purely stochastic
3. Spatial
4. Ray tracing

2.
Path Loss
• Path loss channel models represent the power reduction of a
transmitted signal as it traverses the wireless medium.
• They do not perform any filtering on the signal.
• These channel models are based on the medium through which
the signal travels, such as free space, rain, fog, or gas.

3.
Purely Stochastic
• Purely stochastic channel models address thermal noise
generation and multipath fading channels. They do not require
any knowledge of the geometry of the link being modeled.
• An additive white Gaussian noise (AWGN) channel models
the electronic noise in a receiver front end. This noise is
spectrally flat, and its amplitude follows a Gaussian pdf.
• The delay spread of a channel is the time duration between the
first and last multipath components with significant energy.If
the reciprocal of the delay spread is much greater than the
signal bandwidth, then the fading is called frequency flat.
• If that reciprocal is comparable to or less than the signal
bandwidth, then the fading is called frequency selective.

4.
Spatial Channel Model
• Modern wireless systems typically use beamforming to direct
energy toward desired receivers and away from interferers.
• Beamforming requires a transceiver to use antenna arrays,
giving rise to multiple-input multiple-output (MIMO) systems.
• Spatial channel models were developed to better represent
MIMO links, since previously developed channel models did
not account for array geometries and array responses.
• These models typically define scatterers that reflect
transmitted signals to a receiver.

5.
Ray Tracing Channel Model
• Where spatial channel models do not explicitly specify the
locations of scatterers, ray tracing channel models do.
• They use precise building location information to generate
outdoor channel models, and precise room information to
generate indoor models.

6.
Importance of Channel Models
• They are essential to predict link performance (e.g., BER) in a
single-user scenario.
• They are crucial to predict system performance (e.g.,
throughput, latency) in a multi-user scenario.
• They reduce the need for costly channel measurement projects.

7.
• Path Loss
Calculate Free Space Path Loss
Determine Signal Attenuation with the Crane Rain Model
• Purely Stochastic
Using AWGN Channel Block for Coded Signals
Multipath Fading Channel
WLAN Channel Models
Simulate LTE Propagation Channels
5G TDL Channel Model
• Spatial
Generalized Scattering Channel
WINNER II Channel Model
5G CDL Channel Model
• Ray Tracing
Urban Channel Link Analysis and Visualization Using Ray Tracing
Indoor MIMO-OFDM Communications Link Using Ray Tracing

8.
• Path Loss
Propagation Models
cranerainpl - RF signal attenuation due to rainfall using Crane model
• Purely Stochastic
Fading channels
comm.RayleighChannel - Filter input signal through multipath Rayleigh
fading channel.
wlanTGaxChannel - Filter signal through an 802.11ax multipath fading
channel
• Spatial
phased.ScatteringMIMOChannel
winner2.wim - Generate channel coefficients using WINNER II channel
model
nrCDLChannel - Send signal through CDL channel model
• Ray Tracing
raytrace - Plot propagation paths between sites
buildingMaterialPermittivity - Permittivity and conductivity of building
materials

9.
Massive MIMO
• Massive MIMO (massive multiple-input multiple-output) is a
type of wireless communications technology in which base
stations are equipped with a very large number of antenna
elements to improve spectral and energy efficiency.
• Massive MIMO systems typically have tens, hundreds, or even
thousands of antennas in a single antenna array.
• technologies such as beam forming and spatial multiplexing
enable massive MIMO as one of the key technologies for 5G
NR systems.

10.
• Benefits of Massive MIMO
 Improved coverage at cell edge
 Improved throughput
 Enabled by millimeter wave
• Challenges of Massive MIMO
Modeling, simulation, and testing
Power consumption
Channel reciprocity