110 research outputs found
Turbo Packet Combining for Broadband Space-Time BICM Hybrid-ARQ Systems with Co-Channel Interference
In this paper, efficient turbo packet combining for single carrier (SC)
broadband multiple-input--multiple-output (MIMO) hybrid--automatic repeat
request (ARQ) transmission with unknown co-channel interference (CCI) is
studied. We propose a new frequency domain soft minimum mean square error
(MMSE)-based signal level combining technique where received signals and
channel frequency responses (CFR)s corresponding to all retransmissions are
used to decode the data packet. We provide a recursive implementation algorithm
for the introduced scheme, and show that both its computational complexity and
memory requirements are quite insensitive to the ARQ delay, i.e., maximum
number of ARQ rounds. Furthermore, we analyze the asymptotic performance, and
show that under a sum-rank condition on the CCI MIMO ARQ channel, the proposed
packet combining scheme is not interference-limited. Simulation results are
provided to demonstrate the gains offered by the proposed technique.Comment: 12 pages, 7 figures, and 2 table
Turbo Packet Combining Strategies for the MIMO-ISI ARQ Channel
This paper addresses the issue of efficient turbo packet combining techniques
for coded transmission with a Chase-type automatic repeat request (ARQ)
protocol operating over a multiple-input--multiple-output (MIMO) channel with
intersymbol interference (ISI). First of all, we investigate the outage
probability and the outage-based power loss of the MIMO-ISI ARQ channel when
optimal maximum a posteriori (MAP) turbo packet combining is used at the
receiver. We show that the ARQ delay (i.e., the maximum number of ARQ rounds)
does not completely translate into a diversity gain. We then introduce two
efficient turbo packet combining algorithms that are inspired by minimum mean
square error (MMSE)-based turbo equalization techniques. Both schemes can be
viewed as low-complexity versions of the optimal MAP turbo combiner. The first
scheme is called signal-level turbo combining and performs packet combining and
multiple transmission ISI cancellation jointly at the signal-level. The second
scheme, called symbol-level turbo combining, allows ARQ rounds to be separately
turbo equalized, while combining is performed at the filter output. We conduct
a complexity analysis where we demonstrate that both algorithms have almost the
same computational cost as the conventional log-likelihood ratio (LLR)-level
combiner. Simulation results show that both proposed techniques outperform
LLR-level combining, while for some representative MIMO configurations,
signal-level combining has better ISI cancellation capability and achievable
diversity order than that of symbol-level combining.Comment: 13 pages, 7 figures, and 2 table
Frequency-Domain Turbo Equalisation in Coded SC-FDMA Systems: EXIT Chart Analysis and Performance
In this paper, we investigate the achievable performance of channel coded single-carrier frequency division multiple-access (SC-FDMA) systems employing various detection schemes, when communicating over frequency-selective fading channels. Specifically, three types of minimum mean-square error (MMSE) based frequency-domain (FD) turbo equalisers are considered. The first one is the turbo FD linear equaliser (LE). The second one is a parallel interference cancellation (PIC)-assisted turbo FD decision-feedback equaliser (DFE). The final one is the proposed hybrid interference cancellation (HIC)-aided turboFD-DFE, which combines successive interference cancellation (SIC) with iterative PIC and decoding. The benefit of interference cancellation (IC) is analysed with the EXtrinsic Information Transfer (EXIT) charts. The performance of the coded SC-FDMA systems employing the above-mentioned detection schemes is investigated with the aid of simulations. Our studies show that the IC techniques achieve an attractive performance at a moderate complexity
Channel Estimation in Coded Modulation Systems
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
Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers
We consider channel estimation specific to turbo equalization for
multiple-input multiple-output (MIMO) wireless communication. We develop a
soft-decision-driven sequential algorithm geared to the pipelined turbo
equalizer architecture operating on orthogonal frequency division multiplexing
(OFDM) symbols. One interesting feature of the pipelined turbo equalizer is
that multiple soft-decisions become available at various processing stages. A
tricky issue is that these multiple decisions from different pipeline stages
have varying levels of reliability. This paper establishes an effective
strategy for the channel estimator to track the target channel, while dealing
with observation sets with different qualities. The resulting algorithm is
basically a linear sequential estimation algorithm and, as such, is
Kalman-based in nature. The main difference here, however, is that the proposed
algorithm employs puncturing on observation samples to effectively deal with
the inherent correlation among the multiple demapper/decoder module outputs
that cannot easily be removed by the traditional innovations approach. The
proposed algorithm continuously monitors the quality of the feedback decisions
and incorporates it in the channel estimation process. The proposed channel
estimation scheme shows clear performance advantages relative to existing
channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201
Turbo codes and turbo algorithms
In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding
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