One of the fundamental limitations of mobile radio
communications is their time-varying fading channel. This
thesis addresses the efficient use of channel state information
to improve the communication systems, with a particular
emphasis on practical issues such as compatibility with the
existing wireless systems and low complexity implementation.
The closed-loop transmit diversity technique is used to improve
the performance of the downlink channel in MIMO communication
systems. For example, the WCDMA standard endorsed by 3GPP
adopts a mode of downlink closed-loop scheme based on partial
channel state information known as mode 1 of
3GPP. Channel state information is fed back
from the mobile unit to the base station through a low-rate
uncoded feedback bit stream. In these closed-loop systems,
feedback error and feedback delay, as well as the sub-optimum
reconstruction of the quantized feedback data, are the usual
sources of deficiency.
In this thesis, we address the efficient reconstruction of the
beamforming weights in the presence of the feedback
imperfections, by exploiting the residual redundancies in the
feedback stream. We propose a number of algorithms for
reconstruction of beamforming weights at the base-station, with
the constraint of a constant transmit power. The issue of the
decoding at the receiver is also addressed. In one of the
proposed algorithms, channel fading prediction is utilized to
combat the feedback delay. We introduce the concept of Blind
Antenna Verification which can substitute the conventional
Antenna Weight Verification process without the need for any
training data. The closed-loop mode 1 of 3GPP is used as a
benchmark, and the performance is examined within a WCDMA
simulation framework. It is demonstrated that the proposed
algorithms have substantial gain over the conventional method
at all mobile speeds, and are suitable for the implementation
in practice. The proposed approach is applicable to other
closed-loop schemes as well.
The problem of (long-range) prediction of the fading channel is
also considered, which is a key element for many
fading-compensation techniques. A linear approach, usually used
to model the time evolution of the fading process, does not
perform well for long-range prediction applications. We propose
an adaptive algorithm using a state-space approach for the
fading process based on the sum-sinusoidal model. Also to
enhance the widely-used linear approach, we propose a tracking
method for a multi-step linear predictor. Comparing the two
methods in our simulations shows that the proposed algorithm
significantly outperforms the linear method, for both
stationary and non-stationary fading processes, especially for
long-range predictions. The robust structure, as well as the
reasonable computational complexity, makes the proposed
algorithm appealing for practical applications.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/3413 |
| Date | January 2007 |
| Creators | Heidari, Abdorreza |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
Page generated in 0.0084 seconds