09-07-2012, 12:00 PM
Channel Estimation Strategies for Coded MIMO Systems
[attachment=27240]
Introduction
Overview
High transmission data rate, spectral efficiency, and reliability are necessary for future
wireless communications systems. Unlike Gaussian channels, wireless channels suffer
from attenuation due to multipath in the channel. Multiple copies of a single
transmission arrive at the receiver at slightly different times. Without diversity
techniques, severe attenuation makes it difficult for the receiver to determine the
transmitted signal. Diversity techniques provide potentially less-attenuated replica(s) of
the transmitted signal at the receiver.
The MIMO Channel
Multiple-Input Multiple-Output (MIMO) systems yield vast capacity increases when the
rich scattering environment is properly exploited [1]. When examining the performance
of MIMO systems, the MIMO channel must be modeled properly. The MIMO channel
models used throughout this thesis are described in this section. The primary MIMO
channel model under consideration is the quasi-static, frequency non-selective, Rayleigh
fading channel model.
Frequency Selective Fading
MIMO channels are often frequency selective. The channel undergoes frequencyselective
fading when the coherence bandwidth of the channel is small compared to the
bandwidth of the transmitted signal [10]. When the channel is modeled as frequency
selective fading, individual frequencies are attenuated and faded differently.
Block Fading
Most of the work considered in this thesis uses the quasi-static channel model. However,
block fading is considered for comparison purposes. A quasi-static channel can be
transformed into a block fading channel based by manipulating the data at the transmitter
and receiver.
[attachment=27240]
Introduction
Overview
High transmission data rate, spectral efficiency, and reliability are necessary for future
wireless communications systems. Unlike Gaussian channels, wireless channels suffer
from attenuation due to multipath in the channel. Multiple copies of a single
transmission arrive at the receiver at slightly different times. Without diversity
techniques, severe attenuation makes it difficult for the receiver to determine the
transmitted signal. Diversity techniques provide potentially less-attenuated replica(s) of
the transmitted signal at the receiver.
The MIMO Channel
Multiple-Input Multiple-Output (MIMO) systems yield vast capacity increases when the
rich scattering environment is properly exploited [1]. When examining the performance
of MIMO systems, the MIMO channel must be modeled properly. The MIMO channel
models used throughout this thesis are described in this section. The primary MIMO
channel model under consideration is the quasi-static, frequency non-selective, Rayleigh
fading channel model.
Frequency Selective Fading
MIMO channels are often frequency selective. The channel undergoes frequencyselective
fading when the coherence bandwidth of the channel is small compared to the
bandwidth of the transmitted signal [10]. When the channel is modeled as frequency
selective fading, individual frequencies are attenuated and faded differently.
Block Fading
Most of the work considered in this thesis uses the quasi-static channel model. However,
block fading is considered for comparison purposes. A quasi-static channel can be
transformed into a block fading channel based by manipulating the data at the transmitter
and receiver.