Channel Estimation in Coded Modulation Systems
Date
2012-09-20
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Type
Degree Level
Doctoral
Abstract
With the outstanding performance of coded modulation techniques in fading channels,
much research efforts have been carried out on the design of communication
systems able to operate at low signal-to-noise ratios (SNRs). From this perspective,
the so-called iterative decoding principle has been applied to many signal processing
tasks at the receiver: demodulation, detection, decoding, synchronization and
channel estimation. Nevertheless, at low SNRs, conventional channel estimators do
not perform satisfactorily. This thesis is mainly concerned with channel estimation
issues in coded modulation systems where different diversity techniques are exploited
to combat fading in single or multiple antenna systems.
First, for single antenna systems in fast time-varying fading channels, the thesis
focuses on designing a training sequence by exploiting signal space diversity (SSD).
Motivated by the power/bandwidth efficiency of the SSD technique, the proposed
training sequence inserts pilot bits into the coded bits prior to constellation mapping
and signal rotation. This scheme spreads the training sequence during a transmitted
codeword and helps the estimator to track fast variation of the channel gains. A comprehensive
comparison between the proposed training scheme and the conventional
training scheme is then carried out, which reveals several interesting conclusions with
respect to both error performance of the system and mean square error of the channel
estimator.
For multiple antenna systems, different schemes are examined in this thesis for
the estimation of block-fading channels. For typical coded modulation systems with
multiple antennas, the first scheme makes a distinction between the iteration in the
channel estimation and the iteration in the decoding. Then, the estimator begins
iteration when the soft output of the decoder at the decoding iteration meets some
specified reliability conditions. This scheme guarantees the convergence of the iterative
receiver with iterative channel estimator. To accelerate the convergence process
and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination
of the training sequence and soft information. For coded modulation systems
with precoding technique, in which a precoder is used after the modulator, the training
sequence and data symbols are combined using a linear precoder to decrease the
required training overhead. The power allocation and the placement of the training
sequence to be precoded are obtained based on a lower bound on the mean square
error of the channel estimation. It is demonstrated that considerable performance
improvement is possible when the training symbols are embedded within data symbols
with an equi-spaced pattern. In the last scheme, a joint precoder and training
sequence is developed to maximize the achievable coding gain and diversity order
under imperfect CSI. In particular, both the asymptotic performance behavior of the
system with the precoded training scheme under imperfect CSI and the mean square
error of the channel estimation are derived to obtain achievable diversity order and
coding gain. Simulation results demonstrate that the joint optimized scheme outperforms
the existing training schemes for systems with given precoders in terms of error
rate and the amount of training overhead.
Description
Keywords
Channel Estimation, BICM, Bit-interleaved Coded Modulation, Iterative Receiver, Cramer Rao Bound, Soft Information, Error Rate
Citation
Degree
Doctor of Philosophy (Ph.D.)
Department
Electrical and Computer Engineering
Program
Electrical Engineering