13 research outputs found
Iterative decoding for error resilient wireless data transmission
Both turbo codes and LDPC codes form two new classes of codes that offer energy
efficiencies close to theoretical limit predicted by Claude Shannon. The features of turbo
codes include parallel code catenation, recursive convolutional encoders, punctured
convolutional codes and an associated decoding algorithm. The features of LDPC codes
include code construction, encoding algorithm, and an associated decoding algorithm.
This dissertation specifically describes the process of encoding and decoding for both turbo
and LDPC codes and demonstrates the performance comparison between theses two codes
in terms of some performance factors. In addition, a more general discussion of iterative
decoding is presented.
One significant contribution of this dissertation is a study of some major performance
factors that intensely contribute in the performance of both turbo codes and LDPC codes.
These include Bit Error Rate, latency, code rate and computational resources. Simulation
results show the performance of turbo codes and LDPC codes under different performance
factors
Communications in the observation limited regime
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 141-145).We consider the design of communications systems when the principal cost is observing the channel, as opposed to transmit energy per bit or spectral efficiency. This is motivated by energy constrained communications devices where sampling the signal, rather than transmitting or processing it, dominates energy consumption. We show that sequentially observing samples with the maximum a posteriori entropy can reduce observation costs by close to an order of magnitude using a (24,12) Golay code. This is the highest performance reported over the binary input AWGN channel, with or without feedback, for this blocklength. Sampling signal energy, rather than amplitude, lowers circuit complexity and power dissipation significantly, but makes synchronization harder. We show that while the distance function of this non-linear coding problem is intractable in general, it is Euclidean at vanishing SNRs, and root Euclidean at large SNRs. We present sequences that maximize the error exponent at low SNRs under the peak power constraint, and under all SNRs under an average power constraint. Some of our new sequences are an order of magnitude shorter than those used by the 802.15.4a standard.(cont.) In joint work with P. Mercier and D. Daly, we demonstrate the first energy sampling wireless modem capable of synchronizing to within a ns, while sampling energy at only 32 Msamples per second, and using no high speed clocks. We show that traditional, minimum distance classifiers may be highly sensitive to parameter estimation errors, and propose robust, computationally efficient alternatives. We challenge the prevailing notion that energy samplers must accurately shift phase to synchronize with high precision.by Manish Bhardwaj.Ph.D
Compound codes based on irregular graphs and their iterative decoding.
Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2004.Low-density parity-check (LDPC) codes form a Shannon limit approaching class of linear block codes. With iterative decoding based on their Tanner graphs, they can achieve outstanding performance. Since their rediscovery in late 1990's, the design,
construction, and decoding of LDPC codes as well as their generalization have become one of the focal research points. This thesis takes a few more steps in these directions. The first significant contribution of this thesis is the introduction of a new class of codes
called Generalized Irregular Low-Density (GILD) parity-check codes, which are adapted from the previously known class of Generalized Low-Density (GLD) codes. GILD codes are generalization of irregular LDPC codes, and are shown to outperform GLD codes. In addition, GILD codes have a significant advantage over GLD codes in terms of encoding and decoding complexity. They are also able to match and even beat LDPC codes for small block lengths. The second significant contribution of this thesis is the proposition of several decoding algorithms. Two new decoding algolithms for LDPC codes are introduced. In principle and complexity these algorithms can be grouped with bit flipping algorithms. Two soft-input soft-output (SISO) decoding algorithms for linear block codes are also proposed. The first algorithm is based on Maximum a Posteriori Probability (MAP) decoding of low-weight subtrellis centered around a generated candidate codeword. The second algorithm modifies and utilizes the improved Kaneko's decoding algorithm for soft-input hard-output decoding. These hard outputs are converted to soft-decisions using
reliability calculations. Simulation results indicate that the proposed algorithms provide a significant improvement in error performance over Chase-based algorithm and achieve practically optimal performance with a significant reduction in decoding complexity.
An analytical expression for the union bound on the bit error probability of linear codes on the Gilbert-Elliott (GE) channel model is also derived. This analytical result is shown to be accurate in establishing the decoder performance in the range where
obtaining sufficient data from simulation is impractical
Superposition Mapping & Related Coding Techniques
Since Shannon's landmark paper in 1948, it has been known that the capacity of a
Gaussian channel can be achieved if and only if the channel outputs are Gaussian. In the low signal-to-noise ratio (SNR) regime, conventional mapping schemes suffice for approaching the Shannon limit, while in the high SNR regime, these mapping schemes, which produce uniformly distributed symbols, are insufficient to achieve the capacity. To solve this problem, researchers commonly resort to the technique of signal shaping that mends the symbol distribution, which is originally uniform, into a Gaussian-like one.
Superposition mapping (SM) refers to a class of mapping techniques which use linear superposition to load binary digits onto finite-alphabet symbols that are suitable for waveform transmission. Different from conventional mapping schemes, the output symbols of a superposition mapper can easily be made Gaussian-like, which effectively eliminates the necessity of active signal shaping. For this reason, superposition mapping is of great interest for theoretical research as well as for practical implementations. It is an attractive alternative to signal shaping for approaching the channel capacity in the high SNR regime.
This thesis aims to provide a deep insight into the principles of superposition
mapping and to derive guidelines for systems adopting it. Particularly, the influence of power allocation to the system performance, both w.r.t the achievable power efficiency and supportable bandwidth efficiency, is made clear. Considerable effort is spent on finding code structures that are matched to SM. It is shown that currently prevalent code design concepts, which are mostly derived for coded transmission with bijective uniform mapping, do not really fit with
superposition mapping, which is often non-bijective and nonuniform. As the main
contribution, a novel coding strategy called low-density hybrid-check (LDHC) coding is proposed. LDHC codes are optimal and universally applicable for SM with arbitrary type of power allocation
Proceedings of the Fifth International Mobile Satellite Conference 1997
Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments
Progressive Source-Channel Coding for Multimedia Transmission over Noisy and Lossy Channels with and without Feedback
Rate-scalable or layered lossy source-coding is useful for
progressive transmission of multimedia sources, where the receiver can
reconstruct the source incrementally.
This thesis considers ``joint source-channel'' schemes
for such a progressive transmission, in the presence of
noise or loss, with and without the use of a feedback link.
First we design image communication schemes for memoryless and finite
state channels using limited and explicitly constrained use of
the feedback channel in the form of a variable incremental redundancy
Hybrid ARQ protocol. Constraining feedback allows a direct
comparison with schemes without feedback. Optimized feedback based
systems are shown to have useful gains.
Second, we develop a controlled Markov chain approach for constrained feedback Hybrid ARQ protocol design.
The proposed methodology allows the protocol to be chosen from a collection of signal flow graphs, and
also allows explicit control over the tradeoffs in throughput, reliability and complexity.
Next we consider progressive image transmission in
the absence of feedback. We assign unequal error protection to the bits of
a rate-scalable source-coder using rate compatible
channel codes. We show that, under the framework, the source and
channel bits can be ``scheduled'' in a single bitstream in such a way
that operational optimality is retained for different transmission
budgets, creating a rate-scalable joint source-channel coder.
Next we undertake the design of a joint source-channel decoder that
uses ``distortion aware'' ACK/NACK feedback generation. For
memoryless channels, and Type-I HARQ, the design of optimal ACK/NACK
generation and decoding by packet combining is cast and solved as a
sequential decision problem. We obtain dynamic programming based
optimal solutions and also propose suboptimal, lower complexity
distortion-aware decoders and feedback generation rules which
outperform conventional BER based rules such as
CRC-check.
Finally we design operational rate-distortion optimal ACK/NACK
feedback generation rules for transmitting a tree structured quantizer
over a memoryless channel. We show that the optimal feedback
generation rules are embedded, that is, they allow incremental
switching to higher rates during the transmission. Also, we
obtain the structure of the feedback generation rules in terms
of a feedback threshold function that simplifies the implementation
Iterative multiuser receivers for coded DS-CDMA systems
The introduction of cellular wireless systems in the 1980s has resulted in a continuous and
growing demand for personal communication services. This demand has made larger capacity
systems necessary. With the interest from both the research community and industry in wireless
code-division multiple-access (CDMA) systems, the application of multiuser detection (MUD)
techniques to wireless systems is becoming increasingly important. MUD is an important area
of interest to help obtain the significant increase in capacity needed for future wireless services.
The standardisation of direct-sequence CDMA (DS-CDMA) systems in the third generation of
mobile communication systems has raised even more interest in exploiting the capabilities and
capacity of this type of technology. However, the conventional DS-CDMA system has the major
problem of multiple-access interference (MAI). The MAI is unavoidable because receivers
deal with information which is transmitted not by a single source but by several uncoordinated
and geographically separated sources. As a result, the capacity of these systems is inherently interference
limited by other users. To overcome these limitations, MUD emerges as a promising
approach to increase the system capacity.
This thesis addresses the problem of improving the downlink capacity of a coded DS-CDMA
system with the use of MUD techniques at the mobile terminal receiver. The optimum multiuser
receiver scheme is far too computational intensive for practical use. Therefore, the aim of this
thesis is to investigate sub-optimal multiuser receiver schemes that can exploit the advantages
of MUD but also simplify its implementation. The attention is primarily focused on iterative
MUD receiver schemes which apply the turbo multiuser detection principle. Essentially this
principle consists of an iterative exchange of extrinsic information among the receiver modules
to achieve improved performance.
In this thesis, the implementation of an iterative receiver based on a linear MUD technique and
a cancellation scheme over an additive white Gaussian noise (AWGN) channel is first proposed
and analysed. The interference analysis shows that good performance is achieved using a lowcomplexity
receiver structure. In more realistic mobile channels, however, this type of receiver
suffers from the presence of higher levels of interference resulting in poor receiver performance.
The reason for this is that in such scenarios the desired signals are no longer linearly separable.
Therefore, non-linear detection techniques are required to provide better performance. With
this purpose, a hybrid iterative multiuser receiver is investigated for the case of a stationary
multipath channel. The incorporation of antenna arrays is an effective and practical technique to
provide a significant capacity gain over conventional single-antenna systems. In this context, a
novel space-time iterative multiuser receiver is proposed which achieves a large improvement in
spectral efficiency and performance over multipath fading channels. In addition, it is shown that
this architecture can be implemented without a prohibitive complexity cost. The exploitation
of the iterative principle can be used to approach the capacity bounds of a coded DS-CDMA
system. Using the Shannonâs sphere packing bound, a comparison is presented to illustrate how
closely a practical system can approach the theoretical limits of system performance
Advanced receivers for distributed cooperation in mobile ad hoc networks
Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato