880 research outputs found
On performance analysis and implementation issues of iterative decoding for graph based codes
There is no doubt that long random-like code has the potential to achieve good performance because of its excellent distance spectrum. However, these codes remain useless in practical applications due to the lack of decoders rendering good performance at an acceptable complexity. The invention of turbo code marks a milestone progress in channel coding theory in that it achieves near Shannon limit performance by using an elegant iterative decoding algorithm. This great success stimulated intensive research oil long compound codes sharing the same decoding mechanism. Among these long codes are low-density parity-check (LDPC) code and product code, which render brilliant performance. In this work, iterative decoding algorithms for LDPC code and product code are studied in the context of belief propagation.
A large part of this work concerns LDPC code. First the concept of iterative decoding capacity is established in the context of density evolution. Two simulation-based methods approximating decoding capacity are applied to LDPC code. Their effectiveness is evaluated. A suboptimal iterative decoder, Max-Log-MAP algorithm, is also investigated. It has been intensively studied in turbo code but seems to be neglected in LDPC code. The specific density evolution procedure for Max-Log-MAP decoding is developed. The performance of LDPC code with infinite block length is well-predicted using density evolution procedure.
Two implementation issues on iterative decoding of LDPC code are studied. One is the design of a quantized decoder. The other is the influence of mismatched signal-to-noise ratio (SNR) level on decoding performance. The theoretical capacities of the quantized LDPC decoder, under Log-MAP and Max-Log-MAP algorithms, are derived through discretized density evolution. It is indicated that the key point in designing a quantized decoder is to pick a proper dynamic range. Quantization loss in terms of bit error rate (BER) performance could be kept remarkably low, provided that the dynamic range is chosen wisely. The decoding capacity under fixed SNR offset is obtained. The robustness of LDPC code with practical length is evaluated through simulations. It is found that the amount of SNR offset that can be tolerated depends on the code length.
The remaining part of this dissertation deals with iterative decoding of product code. Two issues on iterative decoding of\u27 product code are investigated. One is, \u27improving BER performance by mitigating cycle effects. The other is, parallel decoding structure, which is conceptually better than serial decoding and yields lower decoding latency
Reweighted LP decoding for LDPC codes
We introduce a novel algorithm for decoding binary linear codes by linear programming. We build on the LP decoding algorithm of Feldman et al. and introduce a post-processing step that solves a second linear program that reweights the objective function based on the outcome of the original LP decoder output. Our analysis shows that for some LDPC ensembles we can improve the provable threshold guarantees compared to standard LP decoding. We also show significant empirical performance gains for the reweighted LP decoding algorithm with very small additional computational complexity
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
Direct-form adaptive equalization for underwater acoustic communication
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2012Adaptive equalization is an important aspect of communication systems in various
environments. It is particularly important in underwater acoustic communication
systems, as the channel has a long delay spread and is subject to the effects of time-
varying multipath fading and Doppler spreading.
The design of the adaptation algorithm has a profound influence on the performance of the system. In this thesis, we explore this aspect of the system. The
emphasis of the work presented is on applying concepts from inference and decision
theory and information theory to provide an approach to deriving and analyzing
adaptation algorithms. Limited work has been done so far on rigorously devising
adaptation algorithms to suit a particular situation, and the aim of this thesis is to
concretize such efforts and possibly to provide a mathematical basis for expanding it
to other applications.
We derive an algorithm for the adaptation of the coefficients of an equalizer when
the receiver has limited or no information about the transmitted symbols, which we
term the Soft-Decision Directed Recursive Least Squares algorithm. We will demonstrate connections between the Expectation-Maximization (EM) algorithm and the
Recursive Least Squares algorithm, and show how to derive a computationally efficient, purely recursive algorithm from the optimal EM algorithm.
Then, we use our understanding of Markov processes to analyze the performance
of the RLS algorithm in hard-decision directed mode, as well as of the Soft-Decision
Directed RLS algorithm. We demonstrate scenarios in which the adaptation procedures fail catastrophically, and discuss why this happens. The lessons from the
analysis guide us on the choice of models for the adaptation procedure. We then
demonstrate how to use the algorithm derived in a practical system for underwater
communication using turbo equalization. As the algorithm naturally incorporates
soft information into the adaptation process, it becomes easy to fit it into a turbo
equalization framework. We thus provide an instance of how to use the information of a turbo equalizer in an adaptation procedure, which has not been very well explored in the past. Experimental data is used to prove the value of the algorithm in
a practical context.Support from the agencies
that funded this research- the Academic Programs Office at WHOI and the Office of
Naval Research (through ONR Grant #N00014-07-10738 and #N00014-10-10259)
Constellation design for future communication systems: a comprehensive survey
[EN] The choice of modulation schemes is a fundamental building block of wireless communication
systems. As a key component of physical layer design, they critically impact the expected communication
capacity and wireless signal robustness. Their design is also critical for the successful roll-out of wireless
standards that require a compromise between performance, efficiency, latency, and hardware requirements.
This paper presents a survey of constellation design strategies and associated outcomes for wireless
communication systems. The survey discusses their performance and complexity to address the need for
some desirable properties, including consistency, channel capacity, system performance, required demapping
architecture, flexibility, and independence. Existing approaches for constellation designs are investigated
using appropriate metrics and categorized based on their theoretical algorithm design. Next, their application
to different communication standards is analyzed in context, aiming at distilling general guidelines applicable
to the wireless building block design. Finally, the survey provides a discussion on design directions for future
communication system standardization processes.This work was supported in part by the Basque Government under Grant IT1234-19, in part by the PREDOC under
Program PRE_2020_2_0105, and in part by the Spanish Government through the Project PHANTOM (MCIU/AEI/FEDER, UE) under Gran
Reweighted LP Decoding for LDPC Codes
We introduce a novel algorithm for decoding binary linear codes by linear programming (LP). We build on the LP decoding algorithm of Feldman and introduce a postprocessing step that solves a second linear program that reweights the objective function based on the outcome of the original LP decoder output. Our analysis shows that for some LDPC ensembles we can improve the provable threshold guarantees compared to standard LP decoding. We also show significant empirical performance gains for the reweighted LP decoding algorithm with very small additional computational complexity
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