49 research outputs found
Symbol level decoding of Reed-Solomon codes with improved reliability information over fading channels
A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering, 2016Reliable and e cient data transmission have been the subject of current research,
most especially in realistic channels such as the Rayleigh fading channels. The focus
of every new technique is to improve the transmission reliability and to increase
the transmission capacity of the communication links for more information to be
transmitted. Modulation schemes such as M-ary Quadrature Amplitude Modulation
(M-QAM) and Orthogonal Frequency Division Multiplexing (OFDM) were
developed to increase the transmission capacity of communication links without
additional bandwidth expansion, and to reduce the design complexity of communication
systems.
On the contrary, due to the varying nature of communication channels, the message
transmission reliability is subjected to a couple of factors. These factors include the
channel estimation techniques and Forward Error Correction schemes (FEC) used
in improving the message reliability. Innumerable channel estimation techniques
have been proposed independently, and in combination with di erent FEC schemes
in order to improve the message reliability. The emphasis have been to improve
the channel estimation performance, bandwidth and power consumption, and the
implementation time complexity of the estimation techniques. Of particular interest, FEC schemes such as Reed-Solomon (RS) codes, Turbo
codes, Low Density Parity Check (LDPC) codes, Hamming codes, and Permutation
codes, are proposed to improve the message transmission reliability of communication
links. Turbo and LDPC codes have been used extensively to combat
the varying nature of communication channels, most especially in joint iterative
channel estimation and decoding receiver structures. In this thesis, attention is
focused on using RS codes to improve the message reliability of a communication
link because RS codes have good capability of correcting random and burst errors,
and are useful in di erent wireless applications.
This study concentrates on symbol level soft decision decoding of RS codes. In
this regards, a novel symbol level iterative soft decision decoder for RS codes
based on parity-check equations is developed. This Parity-check matrix Transformation
Algorithm (PTA) is based on the soft reliability information derived from
the channel output in order to perform syndrome checks in an iterative process.
Performance analysis verify that this developed PTA outperforms the conventional
RS hard decision decoding algorithms and the symbol level Koetter and Vardy
(KV ) RS soft decision decoding algorithm.
In addition, this thesis develops an improved Distance Metric (DM) method of
deriving reliability information over Rayleigh fading channels for combined demodulation
with symbol level RS soft decision decoding algorithms. The newly
proposed DM method incorporates the channel state information in deriving the
soft reliability information over Rayleigh fading channels. Analysis verify that this
developed metric enhances the performance of symbol level RS soft decision decoders
in comparison with the conventional method. Although, in this thesis, the
performance of the developed DM method of deriving soft reliability information
over Rayleigh fading channels is only veri ed for symbol level RS soft decision
decoders, it is applicable to any symbol level soft decision decoding FEC scheme.
Besides, the performance of the all FEC decoding schemes plummet as a result
of the Rayleigh fading channels. This engender the development of joint iterative channel estimation and decoding receiver structures in order to improve the message
reliability, most especially with Turbo and LDPC codes as the FEC schemes.
As such, this thesis develops the rst joint iterative channel estimation and Reed-
Solomon decoding receiver structure. Essentially, the joint iterative channel estimation
and RS decoding receiver is developed based on the existing symbol level
soft decision KV algorithm. Consequently, the joint iterative channel estimation
and RS decoding receiver is extended to the developed RS parity-check matrix
transformation algorithm. The PTA provides design ease and
exibility, and lesser
computational time complexity in an iterative receiver structure in comparison
with the KV algorithm.
Generally, the ndings of this thesis are relevant in improving the message transmission
reliability of a communication link with RS codes. For instance, it is
pertinent to numerous data transmission technologies such as Digital Audio Broadcasting
(DAB), Digital Video Broadcasting (DVB), Digital Subscriber Line (DSL),
WiMAX, and long distance satellite communications. Equally, the developed, less
computationally intensive, and performance e cient symbol level decoding algorithm
for RS codes can be use in consumer technologies like compact disc and
digital versatile disc.GS201
On an Achievable Rate of Large Rayleigh Block-Fading MIMO Channels with No CSI
Training-based transmission over Rayleigh block-fading multiple-input
multiple-output (MIMO) channels is investigated. As a training method a
combination of a pilot-assisted scheme and a biased signaling scheme is
considered. The achievable rates of successive decoding (SD) receivers based on
the linear minimum mean-squared error (LMMSE) channel estimation are analyzed
in the large-system limit, by using the replica method under the assumption of
replica symmetry. It is shown that negligible pilot information is best in
terms of the achievable rates of the SD receivers in the large-system limit.
The obtained analytical formulas of the achievable rates can improve the
existing lower bound on the capacity of the MIMO channel with no channel state
information (CSI), derived by Hassibi and Hochwald, for all signal-to-noise
ratios (SNRs). The comparison between the obtained bound and a high SNR
approximation of the channel capacity, derived by Zheng and Tse, implies that
the high SNR approximation is unreliable unless quite high SNR is considered.
Energy efficiency in the low SNR regime is also investigated in terms of the
power per information bit required for reliable communication. The required
minimum power is shown to be achieved at a positive rate for the SD receiver
with no CSI, whereas it is achieved in the zero-rate limit for the case of
perfect CSI available at the receiver. Moreover, numerical simulations imply
that the presented large-system analysis can provide a good approximation for
not so large systems. The results in this paper imply that SD schemes can
provide a significant performance gain in the low-to-moderate SNR regimes,
compared to conventional receivers based on one-shot channel estimation.Comment: re-submitted to IEEE Trans. Inf. Theor
Graph Neural Network-Enhanced Expectation Propagation Algorithm for MIMO Turbo Receivers
Deep neural networks (NNs) are considered a powerful tool for balancing the
performance and complexity of multiple-input multiple-output (MIMO) receivers
due to their accurate feature extraction, high parallelism, and excellent
inference ability. Graph NNs (GNNs) have recently demonstrated outstanding
capability in learning enhanced message passing rules and have shown success in
overcoming the drawback of inaccurate Gaussian approximation of expectation
propagation (EP)-based MIMO detectors. However, the application of the
GNN-enhanced EP detector to MIMO turbo receivers is underexplored and
non-trivial due to the requirement of extrinsic information for iterative
processing. This paper proposes a GNN-enhanced EP algorithm for MIMO turbo
receivers, which realizes the turbo principle of generating extrinsic
information from the MIMO detector through a specially designed training
procedure. Additionally, an edge pruning strategy is designed to eliminate
redundant connections in the original fully connected model of the GNN
utilizing the correlation information inherently from the EP algorithm. Edge
pruning reduces the computational cost dramatically and enables the network to
focus more attention on the weights that are vital for performance. Simulation
results and complexity analysis indicate that the proposed MIMO turbo receiver
outperforms the EP turbo approaches by over 1 dB at the bit error rate of
, exhibits performance equivalent to state-of-the-art receivers with
2.5 times shorter running time, and adapts to various scenarios.Comment: 15 pages, 12 figures, 2 tables. This paper has been accepted for
publication by the IEEE Transactions on Signal Processing. Copyright may be
transferred without notice, after which this version may no longer be
accessibl
Iterative receivers and multichannel equalisation for time division multiple access systems
The thesis introduces receiver algorithms improving the performance of TDMA mobile radio systems. Particularly, we consider receivers utilising side information, which can be obtained from the error control coding or by having a priori knowledge of interference sources. Iterative methods can be applied in the former case and interference suppression techniques in the latter.
Convolutional coding adds redundant information into the signal and thereby protects messages transmitted over a radio channel. In the coded systems the receiver is usually comprised of separate channel estimation, detection and channel decoding tasks due to complexity restrictions. This suboptimal solution suffers from performance degradation compared to the optimal solution achieved by optimising the joint probability of information bits, transmitted symbols and channel impulse response. Conventional receiver utilises estimated channel state information in the detection and detected symbols in the channel decoding to finally obtain information bits. However, the channel decoder provides also extrinsic information on the bit probabilities, which is independent of the received information at the equaliser input. Therefore it is beneficial to re-perform channel estimation and detection using this new extrinsic information together with the original input signal.
We apply iterative receiver techniques mainly to Enhanced General Packet Radio System (EGPRS) using GMSK modulation for iterative channel estimation and 8-PSK modulation for iterative detection scheme. Typical gain for iterative detection is around 2 dB and for iterative channel estimation around 1 dB. Furthermore, we suggest two iteration rounds as a reasonable complexity/performance trade-off. To obtain further complexity reduction we introduce the soft trellis decoding technique that reduces the decoder complexity significantly in the iterative schemes.
Cochannel interference (CCI) originates from the nearby cells that are reusing the same transmission frequency. In this thesis we consider CCI suppression by joint detection (JD) technique, which detects simultaneously desired and interfering signals. Because of the complexity limitations we only consider JD for two binary modulated signals. Therefore it is important to find the dominant interfering signal (DI) to achieve the best performance. In the presence of one strong DI, the JD provides major improvement in the receiver performance.
The JD requires joint channel estimation (JCE) for the two signals. However, the JCE makes the implementation of the JD more difficult, since it requires synchronised network and unique training sequences with low cross-correlation for the two signals.reviewe