Iterative source-channel decoder using extrinsic information from softbit-source decoding

Adrat, Marc; Vary, Peter; Spittka, Julian

doi:10.1109/icassp.2001.940547

Cited by 65 publications

(82 citation statements)

References 11 publications

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“…A 1D iterative system model has been proposed and analysed by Vary and co-workers [4][5][6][7] in the context of audio signals. Since their model was designed for 1D signals, it cannot directly exploit the 2D correlation of practical video signals.…”

Section: Iterative Source Decoding Modelmentioning

confidence: 99%

“…The employment of first-order Markov modelling aided softbit source decoding (FOMM-SBSD) was discussed in [5][6][7]. The a-posteriori log-likelihood ratio of bit x i (k) conditioned on y t 0 was derived in [6,7], which may be expressed as in (5), where the components γ, α and β are defined by Adrat and Vary [7] (see (5)) Below, we consider the determination of the pixels x 0 ,…, x t based on the soft pixel information y 0 ,…, y t . Firstly, we propose our novel trellis representation of the first-order Markov process in Section 3.1, namely the pixel sequence x 0 ,…, x t .…”

Section: Markov Modelled Softbit Source Decoding With Reduced Complexitymentioning

confidence: 99%

“…3. Finally, we reduce the complexity of the 1D decoding algorithms derived by Vary and co-workers [6,7] by designing a novel trellis representation of the Markov process and by deriving its decoding rules. This rest of this paper is organised as follows.…”

Section: Introductionmentioning

confidence: 99%

“…Softbit source decoding (SBSD) was proposed for error concealment of speech signals by Fingscheidt and Vary [5] using softbit information, where the correlation of adjacent speech source samples were modelled by a first-order Markov process. Afterwards, Adrat et al [6,7] developed SBSD for iterative source-channel decoding using both forward-and backward-oriented calculations.…”

Section: Introductionmentioning

confidence: 99%

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Iterative source and channel decoding relying on correlation modelling for wireless video transmission

et al. 2013

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Since joint source-channel decoding is capable of exploiting the residual redundancy in the source signals for improving the attainable error resilience, it has attracted substantial attention. Motivated by the principle of exploiting the source redundancy at the receiver, in this treatise, the authors study the application of iterative source-channel decoding (ISCD) aided video communications, where the video signal is modelled by a first-order Markov process. Firstly, the authors derive reduced-complexity formulas for the first-order Markov modelling (FOMM) aided source decoding. Then they propose a bit-based iterative horizontal-vertical scanline model (IHVSM) aided source decoding algorithm, where a horizontal and a vertical source decoder are employed for exchanging their extrinsic information using the iterative decoding philosophy. The iterative IHVSM aided decoder is then employed in a forward error correction (FEC) encoded uncompressed video transmission scenario, where the IHVSM and the FEC decoder exchange softbit-information for performing turbo-like ISCD for the sake of improving the reconstructed video quality. Finally, the authors benchmark the attainable system performance against a near-lossless H.264/AVC video communication system and the existing FOMM-based softbit source decoding scheme, where the softbit decoding is performed by a one-dimensional Markov model aided decoder. The authors simulation results show that E b /N 0 improvements in excess of 2.8 dB are attainable by the proposed technique in uncompressed video applications Q1.

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Section: Iterative Source Decoding Modelmentioning

confidence: 99%

Section: Markov Modelled Softbit Source Decoding With Reduced Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Iterative source and channel decoding relying on correlation modelling for wireless video transmission

et al. 2013

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“…To exploit the residual redundancy in source-coded parameters such as scale factors or predictor coefficients for speech, audio, and video signals in a Turbo process, iterative source-channel decoding (ISCD) has been presented in [1], [2]. This residual redundancy occurs due to imperfect source encoding resulting for instance from the delay constraints.…”

Section: Introductionmentioning

confidence: 99%

Iterative source-coded equalization: turbo error concealment for ISI channels

Schmalen

Clevorn

Vary

2007

2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications

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In this paper, we analyze the behavior of soft decision source decoding for ISI channels and present an iterative scheme similar to Turbo equalization allowing to combat efficiently intersymbol interference effects. In a first step, we investigate the behavior of different index assignments in the quantizer and show that gains are possible by iterative processing without any channel (de)coding. In a second step, we use short block codes resulting in redundant index assignments at the transmitter. The receiver does not perform any explicit channel decoding but exploits the additional redundancy of the index assignment in the soft decision source decoder. Furthermore, we show that a very simple channel precoder permits even larger gains without any additional decoding complexity. Moreover, the extension towards a flexible multi-mode system allowing a trade-off between channel quality and quantization quality over a wide range of channel conditions is presented.

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Iterative Source–Channel Decoding

Hanzo

Maunder

Wang

2010

Near‐Capacity Variable‐Length Coding

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The exploitation of the residual redundancy of source codec parameters by using the Turbo principle is known as iterative source-channel decoding (ISCD). The concept of redundant index assignments was proposed as a powerful improvement for ISCD. In this contribution design and optimization guidelines for such redundant index assignments are presented. Commonly, the redundant index assignment is based on a simple block code. Using extrinsic information transfer (EXIT) chart we demonstrate that weak block codes such as a repetition code should be preferred. Simulation results show significant performance improvements with redundant index assignments based on this guideline.

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Iterative source-channel decoder using extrinsic information from softbit-source decoding

Cited by 65 publications

References 11 publications

Iterative source and channel decoding relying on correlation modelling for wireless video transmission

Iterative source and channel decoding relying on correlation modelling for wireless video transmission

Iterative source-coded equalization: turbo error concealment for ISI channels

Iterative Source–Channel Decoding

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