607 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
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Mobile Audiovisual Terminal: System Design and Subjective Testing in DECT and UMTS networks
It is anticipated that there will shortly be a requirement
for multimedia terminals that operate via mobile
communications systems. This paper presents a functional specification
for such a terminal operating at 32 kb/s in a digital
European cordless telecommunications (DECT) and universal
mobile telecommunications system (UMTS) radio network. A terminal
has been built, based on a PC with digital signal processor
(DSP) boards for audio and video coding and decoding. Speech
coding is by a phonetically driven code-excited linear prediction
(CELP) speech coder and video coding by a block-oriented hybrid
discrete cosine transform (DCT) coder. Separate channel coding
is provided for the audio and video data. The paper describes the
techniques used for audio and video coding, channel coding, and
synchronization. Methods of subjective testing in a DECT network
and in a UMTS network are also described. These consisted of
subjective tests of first impressions of the mobile audio–visual
terminal (MAVT) quality, interactive tests, and the completion
of an exit questionnaire. The test results showed that the quality
of the audio was sufficiently good for comprehension and the
video was sufficiently good for following and repeating simple
mechanical tasks. However, the quality of the MAVT was not
good enough for general use where high-quality audio and video
was needed, especially when transmission was in a noisy radio
environment
Network-on-Chip Based H.264 Video Decoder on a Field Programmable Gate Array
This thesis develops the first fully network-on-chip (NoC) based h.264 video decoder implemented in real hardware on a field programmable gate array (FPGA). This thesis starts with an overview of the h.264 video coding standard and an introduction to the NoC communication paradigm. Following this, a series of processing elements (PEs) are developed which implement the component algorithms making up the h.264 video decoder. These PEs, described primarily in VHDL with some Verilog and C, are then mapped to an NoC which is generated using the CONNECT NoC generation tool. To demonstrate the scalability of the proposed NoC based design, a second NoC based video decoder is implemented on a smaller FPGA using the same PEs on a more compact NoC topology. The performance of both decoders, as well as their component PEs, is evaluated on real hardware. An analysis of the performance results is conducted and recommendations for future work are made based on the results of this analysis. Aside from the development of the proposed decoder, a major contribution of this thesis is the release of all source materials for this design as open source hardware and software. The release of these materials will allow other researchers to more easily replicate this work, as well as create derivative works in the areas of NoC based designs for FPGA, video coding and decoding, and related areas
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
The recently developed Distributed Video Coding (DVC) is typically suitable for the
applications where the conventional video coding is not feasible because of its
inherent high-complexity encoding. Examples include video surveillance usmg
wireless/wired video sensor network and applications using mobile cameras etc. With
DVC, the complexity is shifted from the encoder to the decoder.
The practical application of DVC is referred to as Wyner-Ziv video coding (WZ)
where an estimate of the original frame called "side information" is generated using
motion compensation at the decoder. The compression is achieved by sending only
that extra information that is needed to correct this estimation. An error-correcting
code is used with the assumption that the estimate is a noisy version of the original
frame and the rate needed is certain amount of the parity bits. The side information is
assumed to have become available at the decoder through a virtual channel. Due to
the limitation of compensation method, the predicted frame, or the side information, is
expected to have varying degrees of success. These limitations stem from locationspecific
non-stationary estimation noise. In order to avoid these, the conventional
video coders, like MPEG, make use of frame partitioning to allocate optimum coder
for each partition and hence achieve better rate-distortion performance. The same,
however, has not been used in DVC as it increases the encoder complexity.
This work proposes partitioning the considered frame into many coding units
(region) where each unit is encoded differently. This partitioning is, however, done at
the decoder while generating the side-information and the region map is sent over to
encoder at very little rate penalty. The partitioning allows allocation of appropriate
DVC coding parameters (virtual channel, rate, and quantizer) to each region. The
resulting regions map is compressed by employing quadtree algorithm and
communicated to the encoder via the feedback channel. The rate control in DVC is
performed by channel coding techniques (turbo codes, LDPC, etc.). The performance
of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and
an adaptive WZ DVC is designed both in transform domain and in pixel domain. The
transform domain WZ video coding (TDWZ) has distinct superior performance as
compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the
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spatial redundancy during the encoding. The performance evaluations show that the
proposed system is superior to the existing distributed video coding solutions.
Although the, proposed system requires extra bits representing the "regions map" to be
transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art
frame based DVC by 0.6-1.9 dB.
The feedback channel (FC) has the role to adapt the bit rate to the changing
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statistics between the side infonmation and the frame to be encoded. In the
unidirectional scenario, the encoder must perform the rate control. To correctly
estimate the rate, the encoder must calculate typical side information. However, the
rate cannot be exactly calculated at the encoder, instead it can only be estimated. This
work also prbposes a feedback-free region-based adaptive DVC solution in pixel
domain based on machine learning approach to estimate the side information.
Although the performance evaluations show rate-penalty but it is acceptable
considering the simplicity of the proposed algorithm.
vii
A hardware implementation of a Viterbi decoder for a (3,2/3) TCM code
The report details the design of a dedicated Viterbi decoder chip set for an Ungerboek (3,2/3) Trellis Coded Modulation code. It was the specific intention of the thesis to design a system that could be implemented on standard Field Programmable Gate Arrays (FPGA) yet still be able to cope with high bit rates. The focus of the research was to both evaluate and modify the existing VLSI design techniques and to develop new techniques to make this possible. Trellis Coded Modulation refers to a specific sub-class of convolutional codes that ire an example of coded modulation. In coded modulation there is a direct link between the encoding and modulation processes aimed at improving the performance of the code by introducing redundancy in the signal set used to transmit the code. Ungerboek developed a technique for mapping the encoded words onto points in the signal set, called mapping by set partitioning, that maximises the Euclidian distance between adjacent codewords, and hence maximises the minimum distance between any two output sequences in the code. The Viterbi algorithm is a maximum likelihood decoder for convolutional codes such as TCM. The operation of the Viterbi algorithm is based on using soft decision decoding to produce an estimate of how well the received sequence corresponds with any of the allowed code sequences. The code sequences which most closely matches the received sequence is then decoded to form the output of the decoder. A central problem in implementing systems using TCM with Viterbi decoding is that although the encoder is a relatively simple device, the decoder is not. The complexity of the Viterbi decoder for any given TCM scheme will be the major drawback in implementing the scheme. As such techniques for reducing the complexity of Viterbi decoders are of interest to developers of communication systems. The algorithms describing the implementation and operation of the Viterbi algorithm can be categorised into three main layers. The top layer holds the theoretical algorithm itself, in the second layer are the set of algorithms that describe the broad techniques used to manipulate the theoretical algorithm into a form in which it can be implemented, and the third layer of algorithms describe the implementations themselves. The work contained in this thesis concentrates on the second two layers of algorithms
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