Andres Kwasinski, Vinay Chande · 2022
This chapter focuses on joint source–channel coding techniques that use at the decoders different forms of side information, other than the source information being communicated. It describes statistical information of the source that can improve the error correction capability of the channel decoder. One of the first works to study a priori and a posteriori source information to improve channel decoding was, where the term source-controlled channel decoding was introduced. The Turbo principle was introduced as an iterative decoding technique for concatenated channel codes. The turbo decoder is formed by one-channel decoder for each channel encoder, connected in the same parallel or serial configuration used for encoding. While the derivation of the Joint Source-Channel Decoding algorithm seen so far is based on the calculation of probability values, the implementation of the algorithm is based on the use of log-likelihood values for these probabilities.
Cited by 1
Tariq Haddad, Abbas Yongaçoğlu · 2003
The design criterion of a joint source/channel soft decision decoder is developed with both binary convolutional codes and nonbinary dual-k codes. The performance of the modified decoder is evaluated and compared to the performance of the decoder proposed by Sayood et al. (1994) by Monte Carlo simulations. As expected, the soft decision system outperforms the hard decision system simulated by Sayood (1994). In the context of decoding 2 and 3-bit DPCM compressed images, we show the advantage of using the nonbinary dual-k code, which matches the alphabets of the source encoder output, over binary convolutional codes. Furthermore, simulation results verify that a coding gain is achieved by exploiting higher residual redundancy levels at the source encoder output.
Cited by 1
2016
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Michel Kieffer, Pierre Duhamel · HAL (Le Centre pour la Communication Scientifique Directe) · 2014
International audience
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Vary, Peter · RWTH Publications (RWTH Aachen) · 2001
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Weidong Yi · 2008
An iterative joint source channel decoding (ISCD) scheme for WMSN is proposed, based on a soft-input-soft-output (SISO) a posteriori probability decoding algorithm for variable-length coded sources, which leads to not only maximum likelihood (ML) sequence estimation but also the computation of bit-based reliability values which are necessary for ISCD. Another innovation is that the technique of scaling extrinsic information is brought into the field of ISCD, and the optimal constant scaling factors is obtained under the guide of extrinsic information transfer characteris- tic. This technique improves the ISCD performance with increasing neglectable complexity. The notable feature of the proposed technique is that it requires very low computational complexity and small memory space, and can be applied to WMSN nodes. Simulation results show that the proposed ISCD scheme provides a significant improvement on error pro- tection capability for the variable-length coded data in WMSN.
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YANG Yang, CHEN Yong-rui, ZHAO Jun-lin et al. · SHILAP Revista de lepidopterología · 2008
An iterative joint source channel decoding （ISCD） scheme for WMSN is proposed, based on a soft-input-soft-output （SISO） a posteriori probability decoding algorithm for variable-length coded sources, which leads to not only maximum likelihood （ML） sequence estimation but also the computation of bit-based reliability values which are necessary for ISCD. Another innovation is that the technique of scaling extrinsic information is brought into the field of ISCD, and the optimal constant scaling factors is obtained under the guide of extrinsic information transfer characteris- tic. This technique improves the ISCD performance with increasing neglectable complexity. The notable feature of the proposed technique is that it requires very low computational complexity and small memory space, and can be applied to WMSN nodes. Simulation results show that the proposed ISCD scheme provides a significant improvement on error pro- tection capability for the variable-length coded data in WMSN.
Cited by 0Open access
Goertz, Norbert, Heute, U. · Zenodo (CERN European Organization for Nuclear Research) · 2015
Publication in the conference proceedings of EUSIPCO, Tampere, Finland, 2000
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Ran An, Guojun Liao, Qiufang Lian et al. · 2023
The Double-Polar (D-Polar) code is an innovative scheme that combines source coding and channel coding into a joint coding framework. It aimed at improving the reliability and efficiency of information transmission. By integrating source coding and channel coding, the D-Polar code aims to minimize the bit error rate, enhance the signal’s resilience to interference, and improve its fault tolerance. In this paper, a new type of joint source-channel decoder called Joint Successive Cancellation (J-SC) Decoder is proposed. The proposed approach aims to enhance the decoding performance of D-Polar codes. The merging of nodes representing the information bits of the channel and the nodes corresponding to the high-entropy bits of the source is achieved through the creation of joint source-channel (J) nodes. Based on this joint coding approach, the J-SC decoder is designed to recover the source message by combining source SC decoding with channel SC decoding. During J-SC decoding, the bit values are recovered symbol by symbol. For each J node, the values of source log-likelihood ratios (LLRs) and channel log-likelihood ratios (LLRc) are considered. The simulation results indicate that the decoding performance of J-SC surpasses that of SC decoding, and the performance improves as the overall code rate decreases.
Cited by 1
Lingling Pu, Zhenyu Wu, Ali Bilgin et al. · 2004
A framework for iterative joint source-channel decoding of JPEG2000 codestreams is presented in this paper. At the encoder, JPEG2000 is used to perform source coding with certain error resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. The decoding is carried out jointly in an iterative fashion. Our results indicate that the proposed method improves the convergence rate as well as the overall system performance.
Cited by 7
Doğrusöz, Bekir Ahmet · Bilkent University Institutional Repository (Bilkent University) · 2016
Ankara : Department of Electrical and Electronics Engineering and Institute of Engineering and Science, Bilkent Univ., 1997.
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Upul Samarawickrama, Pradeepa Yahampath · 2006
In this paper we consider the transmission of multiple descriptions over a channel where there are random errors in addition to erasures. We present a list Viterbi algorithm (LVA) based joint decoding scheme which exploits the correlation introduced by the multiple description encoding to improve the signal to noise ratio at the receiver. The scheme is applied to a two description scalar quantized system and a binary symmetric channel. Simulation results show that it achieves a significant improvement over separate decoding
Cited by 1
2015
(CCOE) is an algorithm which combines source-statistics, bit-reliability informations at the chan-nel output and the redundancy introduced by some channel code to compute the a-posteriori probabil-ities of the possibly transmitted source-encoder in-dices at the receiver. A recursive formula for the computation of the a-posteriori probabilities is de-rived and some special cases are given. The algo-rithm is generalized for the parallel transmission of several quantizer indices which commonly encode each source-signal vector. Simulation results are pre-sented and the performances of several algorithms for source-channel decoding are compared. I.
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Ubolthip Sethakaset, Sumei Sun, Peng Hui Tan · 2012
The key of the multimedia compression technique is trying to remove the correlation between the neighboring frames. Due to the computational complexity limitation, considerable correlation is still observed in the multimedia-coded sequence. This residual redundancy can be modeled as a first-order Markov model with the transition probability of the multimedia-coded parameter between adjacent frames. Therefore, in the multimedia transmission over wireless network, there have been researches on the iterative joint source-channel decoding (ISCD), using the transition probability as source side information (SSI) to reduce errors due to the noisy channel. To further correct the errors after the ISCD, we propose a low-complexity yet efficient bit-flipping (BF) algorithm where restrictions are imposed to prevent incurring high undetected error frames. For the ISCD-BF, the source transition probability is crucial to its performance. However, in practice, it is unknown to the receiver. Thus, we propose an SSI estimation to update the transition probability from the output of the ISCD-BF. The performances of the proposed algorithms are examined by applying to a speech transmission over a wireless network. The simulation results show that our proposed algorithms achieve notable gain over the conventional decoder.
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Çağatay Dikici, Duhamel, P., Michel Kieffer et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2011
Publication in the conference proceedings of EUSIPCO, Barcelona, Spain, 2011
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T. Guinonnet, Christine Guillemot · 2004
This paper addresses the issue of robust and joint source-channel decoding of quasiarithmetic codes. Quasiarithmetic coding is a reduced precision and complexity implementation of arithmetic coding. This paper provides first a state model of a quasiarithmetic decoder for binary and M-ary sources. The design of an error-resilient soft decoding algorithm follows quite naturally. The compression efficiency of quasiarithmetic codes allows to add extra redundancy in the form of markers designed specifically to prevent de-synchronization. The algorithm is directly amenable for iterative source-channel decoding in the spirit of serial turbo codes. The coding and decoding algorithms have been tested for a wide range of channel signal-to-noise ratios. Experimental results reveal improved SER and SNR performances against Huffman and optimal arithmetic codes.
Cited by 6
Slim Chaoui, Osama Ouda, Chafaa Hamrouni · Advances in Science Technology and Engineering Systems Journal · 2019
Cited by 5Open access
Thomas Guionnet, Christine Guillemot · 2004
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Amin Zribi, Sonia Zaïbi, Ramesh Pyndiah et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2008
International audience
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Zijian Liang, Kai Niu, Jincheng Dai · 2021 IEEE Globecom Workshops (GC Wkshps) · 2021
Traditional iterative joint source-channel coding (JSCD) scheme based on soft-in-soft-out (SISO) decoding for arithmetic codes (AC) has a very high implementation complexity, which will cause an unbearable decoding latency due to a plenty of AC decoding steps and cross-layer interactions between physical layer and application layer. To tackle this, we propose a learning-based joint source-channel decoding approach, neural-JSCD, which consists of a series of AC SISO decoders and channel SISO decoders. The proposed approach introduces weights and offset factors to the simplified AC SISO decoders and damping factors to the output extrinsic information of both AC and channel SISO decoders, cooperated with trainable low-density parity-check (LDPC) neural decoders to realize the iterative decoding for AC. Through a greedy training method based on gradient descent, the learnable factors of neural-JSCD can be tuned to learn the a priori information of arithmetic codes, thus avoiding the great number of AC decoding steps together with cross-layer interactions during the iterative decoding process and rapidly reducing the implementation complexity of iterative AC decoding. Simulation results show that with a better decoding performance, neural-JSCD can reduce the number of iterations by at least 50% with no AC decoding steps and cross-layer interactions compared to traditional JSCD, in consequence, it greatly reduces the decoding latency of iterative decoding.
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