58 research outputs found
Analysis of Mismatched First Order A Priori Information in Iterative Source-Channel Decoding
Due to complexity and delay constraints a usually significant amount of residual redundancy remains in the source samples after source coding. This residual redundancy can be exploited by iterative source-channel decoding for error concealment and quality improvements. One key design issue in joint source-channel (de-)coding is the index assignment. Besides conventional index assignments optimized index assignments have been developed, e.g., considering zeroth or first order a priori information of the source samples. However, in real-world scenarios it is unlikely that the amount of residual redundancy is constant over time and thus it may occur that the just deployed index assignment is suboptimal at times when the residual redundancy differs too much from the amount that it is optimized for. In this paper the performance of optimized index assignments is examined that consider first order a priori knowledge under such suboptimal conditions.
Analysis of Joint Source Channel LDPC Coding for Correlated Sources Transmission over Noisy Channels
In this paper, a Joint Source Channel coding scheme
based on LDPC codes is investigated. We consider two concatenated
LDPC codes, one allows to compress a correlated source and the
second to protect it against channel degradations. The original
information can be reconstructed at the receiver by a joint decoder,
where the source decoder and the channel decoder run in parallel by
transferring extrinsic information. We investigate the performance of
the JSC LDPC code in terms of Bit-Error Rate (BER) in the case
of transmission over an Additive White Gaussian Noise (AWGN)
channel, and for different source and channel rate parameters.
We emphasize how JSC LDPC presents a performance tradeoff
depending on the channel state and on the source correlation. We
show that, the JSC LDPC is an efficient solution for a relatively
low Signal-to-Noise Ratio (SNR) channel, especially with highly
correlated sources. Finally, a source-channel rate optimization has
to be applied to guarantee the best JSC LDPC system performance
for a given channel
Nested turbo codes for the costa problem
Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively
Layered Wyner-Ziv video coding for noisy channels
The growing popularity of video sensor networks and video celluar phones has generated the need for low-complexity and power-efficient multimedia systems that can handle multiple video input and output streams. While standard video coding techniques fail to satisfy these requirements, distributed source coding is a promising technique for ??uplink?? applications. Wyner-Ziv coding refers to lossy source coding with side information at the decoder. Based on recent theoretical result on successive Wyner-Ziv coding, we propose in this thesis a practical layered Wyner-Ziv video codec using the DCT, nested scalar quantizer, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information) for noiseless channel. The DCT is applied as an approximation to the conditional KLT, which makes the components of the transformed block conditionally independent given the side information. NSQ is a binning scheme that facilitates layered bit-plane coding of the bin indices while reducing the bit rate. LDPC code based Slepian-Wolf coding exploits the correlation between the quantized version of the source and the side information to achieve further compression. Different from previous works, an attractive feature of our proposed system is that video encoding is done only once but decoding allowed at many lower bit rates without quality loss. For Wyner-Ziv coding over discrete noisy channels, we present a Wyner-Ziv video codec using IRA codes for Slepian-Wolf coding based on the idea of two equivalent channels. For video streaming applications where the channel is packet based, we apply unequal error protection scheme to the embedded Wyner-Ziv coded video stream to find the optimal source-channel coding
trade-off for a target transmission rate over packet erasure channel
Codage de sources avec information adjacente et connaissance incertaine des corrélations
Dans cette thĂšse, nous nous sommes intĂ©ressĂ©s au problĂšme de codage de sources avec information adjacente au dĂ©codeur seulement. Plus prĂ©cisĂ©ment, nous avons considĂ©rĂ© le cas oĂč la distribution jointe entre la source et l'information adjacente n'est pas bien connue. Dans ce contexte, pour un problĂšme de codage sans pertes, nous avons d'abord effectuĂ© une analyse de performance Ă l'aide d'outils de la thĂ©orie de l'information. Nous avons ensuite proposĂ© un schĂ©ma de codage pratique efficace malgrĂ© le manque de connaissance sur la distribution de probabilitĂ© jointe. Ce schĂ©ma de codage s'appuie sur des codes LDPC non-binaires et sur un algorithme de type EspĂ©rance-Maximisation. Le problĂšme du schĂ©ma de codage proposĂ©, c'est que les codes LDPC non-binaires utilisĂ©s doivent ĂȘtre performants. C'est Ă dire qu'ils doivent ĂȘtre construits Ă partir de distributions de degrĂ©s qui permettent d'atteindre un dĂ©bit proche des performances thĂ©oriques. Nous avons donc proposĂ© une mĂ©thode d'optimisation des distributions de degrĂ©s des codes LDPC. Enfin, nous nous sommes intĂ©ressĂ©s Ă un cas de codage avec pertes. Nous avons supposĂ© que le modĂšle de corrĂ©lation entre la source et l'information adjacente Ă©tait dĂ©crit par un modĂšle de Markov cachĂ© Ă Ă©missions Gaussiennes. Pour ce modĂšle, nous avons Ă©galement effectuĂ© une analyse de performance, puis nous avons proposĂ© un schĂ©ma de codage pratique. Ce schĂ©ma de codage s'appuie sur des codes LDPC non-binaires et sur une reconstruction MMSE. Ces deux composantes exploitent la structure avec mĂ©moire du modĂšle de Markov cachĂ©.In this thesis, we considered the problem of source coding with side information available at the decoder only. More in details, we considered the case where the joint distribution between the source and the side information is not perfectly known. In this context, we performed a performance analysis of the lossless source coding scheme. This performance analysis was realized from information theory tools. Then, we proposed a practical coding scheme able to deal with the uncertainty on the joint probability distribution. This coding scheme is based on non-binary LDPC codes and on an Expectation-Maximization algorithm. For this problem, a key issue is to design efficient LDPC codes. In particular, good code degree distributions have to be selected. Consequently, we proposed an optimization method for the selection of good degree distributions. To finish, we considered a lossy coding scheme. In this case, we assumed that the correlation channel between the source and the side information is described by a Hidden Markov Model with Gaussian emissions. For this model, we performed again some performance analysis and proposed a practical coding scheme. The proposed scheme is based on non-binary LDPC codes and on MMSE reconstruction using an MCMC method. In our solution, these two components are able to exploit the memory induced by the Hidden Markov model.PARIS11-SCD-Bib. Ă©lectronique (914719901) / SudocSudocFranceF
Coding for Cooperative Communications
The area of cooperative communications has received tremendous research interest
in recent years. This interest is not unwarranted, since cooperative communications
promises the ever-so-sought after diversity and multiplexing gains typically
associated with multiple-input multiple-output (MIMO) communications, without
actually employing multiple antennas. In this dissertation, we consider several cooperative
communication channels, and for each one of them, we develop information
theoretic coding schemes and derive their corresponding performance limits. We next
develop and design practical coding strategies which perform very close to the information
theoretic limits.
The cooperative communication channels we consider are: (a) The Gaussian relay
channel, (b) the quasi-static fading relay channel, (c) cooperative multiple-access
channel (MAC), and (d) the cognitive radio channel (CRC). For the Gaussian relay
channel, we propose a compress-forward (CF) coding strategy based on Wyner-Ziv
coding, and derive the achievable rates specifically with BPSK modulation. The CF
strategy is implemented with low-density parity-check (LDPC) and irregular repeataccumulate
codes and is found to operate within 0.34 dB of the theoretical limit. For
the quasi-static fading relay channel, we assume that no channel state information
(CSI) is available at the transmitters and propose a rateless coded protocol which
uses rateless coded versions of the CF and the decode-forward (DF) strategy. We
implement the protocol with carefully designed Raptor codes and show that the implementation suffers a loss of less than 10 percent from the information theoretical limit. For
the MAC, we assume quasi-static fading, and consider cooperation in the low-power
regime with the assumption that no CSI is available at the transmitters. We develop
cooperation methods based on multiplexed coding in conjunction with rateless
codes and find the achievable rates and in particular the minimum energy per bit to
achieve a certain outage probability. We then develop practical coding methods using
Raptor codes, which performs within 1.1 dB of the performance limit. Finally, we
consider a CRC and develop a practical multi-level dirty-paper coding strategy using
LDPC codes for channel coding and trellis-coded quantization for source coding. The
designed scheme is found to operate within 0.78 dB of the theoretical limit.
By developing practical coding strategies for several cooperative communication
channels which exhibit performance close to the information theoretic limits, we show
that cooperative communications not only provide great benefits in theory, but can
possibly promise the same benefits when put into practice. Thus, our work can be
considered a useful and necessary step towards the commercial realization of cooperative
communications
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