Joint Source-channel Decoding Research Articles

Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Models

The implementation of joint source-channel coding (JSCC) schemes using deep learning has accelerated the development of semantic communication research. Existing JSCC schemes based on deep learning (DL) are trained on a fixed signal-to-noise ratio (SNR); however, these trained models are not designed for scenarios in which the SNR is dynamic. Therefore, a novel semantic adaptive model for semantic communication—called joint source-channel coding with adaptive models (AMJSCC)—that has a semantic adaptive model selection (SAMS) module is proposed. The joint source-channel encoding (JSCE) model and the joint source-channel decoding (JSCD) model adapt according to both real-time channel conditions and system available computational power resources. Furthermore, residual networks with different layers are investigated to further improve the accuracy of information recovery. Simulation results demonstrate that our model can achieve higher recovery similarity and is more robust and adaptive to the SNR and communication resources. Meanwhile, compared to the state-of-the-art deep JSCC methods, it reduces storage space and communication resource consumption.

Joint Successive Cancellation List Decoding for the Double Polar Codes

As a new joint source-channel coding scheme, the double polar (D-Polar) codes have been proposed recently. In this letter, a novel joint source-channel decoder, namely the joint successive cancellation list (J-SCL) decoder, is proposed to improve the decoding performance of the D-Polar codes. We merge the trellis of the source polar code and that of the channel polar code to construct a compound trellis. In this compound trellis, the variable nodes corresponding to the information bits of the channel polar code and the variable nodes representing the high-entropy bits are merged into the joint source-channel (JSC) nodes. Based on the compound trellis, the J-SCL decoder is designed to recover the source messages by combining the source SCL decoding and channel SCL decoding. The proposed J-SCL decoder doubles the number of the decoding paths for each JSC node and low-entropy node, and then discard all but the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> paths with the smallest joint path-metric (JPM). For the JSC node, the JPM is updated considering both the channel decision log-likelihood ratios (LLRs) and the source decision LLRs. Simulation results show that the J-SCL decoder outperforms the turbo-like BP (TL-BP) decoder with lower complexity.

Controversial Variable Node Selection-Based Adaptive Belief Propagation Decoding Algorithm Using Bit Flipping Check for JSCC Systems.

An end-to-end joint source–channel (JSC) encoding matrix and a JSC decoding scheme using the proposed bit flipping check (BFC) algorithm and controversial variable node selection-based adaptive belief propagation (CVNS-ABP) decoding algorithm are presented to improve the efficiency and reliability of the joint source–channel coding (JSCC) scheme based on double Reed–Solomon (RS) codes. The constructed coding matrix can realize source compression and channel coding of multiple sets of information data simultaneously, which significantly improves the coding efficiency. The proposed BFC algorithm uses channel soft information to select and flip the unreliable bits and then uses the redundancy of the source block to realize the error verification and error correction. The proposed CVNS-ABP algorithm reduces the influence of error bits on decoding by selecting error variable nodes (VNs) from controversial VNs and adding them to the sparsity of the parity-check matrix. In addition, the proposed JSC decoding scheme based on the BFC algorithm and CVNS-ABP algorithm can realize the connection of source and channel to improve the performance of JSC decoding. Simulation results show that the proposed BFC-based hard-decision decoding (BFC-HDD) algorithm ( = 1) and BFC-based low-complexity chase (BFC-LCC) algorithm ( = 1, = 3) can achieve about 0.23 dB and 0.46 dB of signal-to-noise ratio (SNR) defined gain over the prior-art decoding algorithm at a frame error rate (FER) = . Compared with the ABP algorithm, the proposed CVNS-ABP algorithm and BFC-CVNS-ABP algorithm achieve performance gains of 0.18 dB and 0.23 dB, respectively, at FER = .

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Ultra High-Definition (UHD) and Virtual Reality (VR) video streaming over 5G networks are emerging, in which High-Efficiency Video Coding (HEVC) is used as source coding to compress videos more efficiently and polar code is used as channel coding to transmit bitstream reliably over an error-prone channel. In this article, a novel Joint Source-Channel Decoding (JSCD) of polar codes for HEVC-based video streaming is presented to improve the streaming reliability and visual quality. Firstly, a Kernel Density Estimation (KDE) fitting approach is proposed to estimate the positions of error channel decoded bits. Secondly, a modified polar decoder called R-SCFlip is designed to improve the channel decoding accuracy. Finally, to combine the KDE estimator and the R-SCFlip decoder together, the JSCD scheme is implemented in an iterative process. Extensive experimental results reveal that, compared to the conventional methods without JSCD, the error data-frame correction ratios are increased. Averagely, 1.07% and 1.11% Frame Error Ratio (FER) improvements have been achieved for Additive White Gaussian Noise (AWGN) and Rayleigh fading channels, respectively. Meanwhile, the qualities of the recovered videos are significantly improved. For the 2D videos, the average Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) gains reach 14% and 34%, respectively. For the 360֯ videos, the average improvements in terms of Weighted-to-Spherically-uniform PSNR (WS-PSNR) and Voronoi-based Video Multimethod Assessment Fusion (VI-VMAF) reach 21% and 7%, respectively.

Communicating Correlated Sources Over MAC and Interference Channels II: Joint Source-Channel Coding

We present the second part of our work on communicating correlated sources over multiple access (MAC) and interference channels (IC). Specifically, we undertake a Shannon-theoretic study of the above scenarios and focus on characterizing sufficient conditions for lossless recoverability of the sources at the decoder(s). We enhance the fixed block-length (B-L) coding technique by incorporating the technique of inducing source correlation onto channel inputs, originally discovered by Cover, El Gamal and Salehi. In contrast to the first part, performance analysis of a joint source-channel decoder poses new challenges. We enhance the earlier developed suite of coding and analytical tools to overcome these challenges and derive (simplified) single-letter characterizations for a new set of sufficient conditions for both scenarios. For both the MAC and IC problems, the derived sufficient conditions are (i) subsumed in the current known tightest, and (ii) strictly weaker for identified examples. Lastly, we propose simple `plug-in' approaches that can further weaken the derived sufficient conditions. Our findings enable us to subsume Dueck's findings (1981) and go even further for the example considered therein.

Low-Power Cross-Layer Error Management Using MIMO-LDPC Iterative Decoding for Video Processing

This paper presents a novel low-power joint decoding system composed of a multiple-input multiple-output (MIMO) detector, low-density parity-check (LDPC) channel decoder, and H.264 source decoder for energy-aware and cross-layer source-channel transmission systems. Our aim is to achieve a minimum power design that meets the expected quality of service (QoS) at the application layer. This design includes an iterative MIMO-LDPC decoder for minimizing communication errors and an unequal error protection scheme for reducing energy consumption in transmission. The experiment results reveal that our proposed iterative MIMO-LDPC-H.264 joint decoder achieved up to 66% energy reduction with only 0.09 dB peak signal-to-noise ratio degradation when compared to a non-UEP based joint source-channel decoding system.

On the Performance of Wireless Video Communication Using Iterative Joint Source Channel Decoding and Transmitter Diversity Gain Technique

In this research work, we have presented an iterative joint source channel decoding- (IJSCD-) based wireless video communication system. The anticipated transmission system is using the sphere packing (SP) modulation assisted differential space-time spreading (DSTS) multiple input-multiple output (MIMO) scheme. SP modulation-aided DSTS transmission mechanism results in achieving high diversity gain by keeping the maximum possible Euclidean distance between the modulated symbols. Furthermore, the proposed DSTS scheme results in a low-complexity MIMO scheme, due to nonemployment of any channel estimation mechanism. Various combinations of source bit coding- (SBC-) aided IJSCD error protection scheme has been used, while considering their identical overall bit rate budget. Artificial redundancy is incorporated in the source-coded stream for the proposed SBC scheme. The motive of adding artificial redundancy is to increase the iterative decoding performance. The performance of diverse SBC schemes is investigated for identical overall code rate. SBC schemes are employed with different combinations of inner recursive systematic convolutional (RSC) codes and outer SBC codes. Furthermore, the convergence behaviour of the employed error protection schemes is investigated using extrinsic information transfer (EXIT) charts. The results of experiments show that our proposed R a t e − 2 / 3 SBC-assisted error protection scheme with high redundancy incorporation and convergence capability gives better performance. The proposed R a t e − 2 / 3 SBC gives about 1.5 dB E b / N 0 gain at the PSNR degradation point of 1 dB as compared to R a t e − 6 / 7 SBC-assisted error protection scheme, while sustaining the overall bit rate budget. Furthermore, it is also concluded that the proposed R a t e − 2 / 3 SBC-assisted scheme results in E b / N 0 gain of 24 dB at the PSNR degradation point of 1 dB with reference to R a t e − 1 SBC benchmarker scheme.

Performance of Hybrid Binary and Non-Binary Turbo Decoding Schemes for LTE and DVB-RCS Standards

&#x0D; Binary and Non-Binary Turbo codes have been deployed in several digital communication standards to perform error correction. In order to enhance their error performance, several schemes such as Joint Source Channel Decoding (JSCD), extrinsic information scaling mechanisms, and prioritized QAM constellation mapping have been proposed for improving the error performance of error correcting codes. In this paper, hybrid schemes comprising of JSCD, regression based extrinsic information scaling, and prioritized 16-Quadrature Amplitude Modulation (QAM) with binary and non-binary Turbo codes have been presented. Significant improvement in error performance has been observed with the proposed scheme as compared to the conventional one. The hybrid scheme in the case of binary symmetric and asymmetric LTE Turbo codes, and triple binary Turbo codes outperform the conventional scheme by 0.8 dB on average. With duo-binary Turbo codes for the DVB-RCS standard, the hybrid scheme outperforms the conventional one with an average gain of 0.9 dB in BER performance.&#x0D;

A Joint Source Channel Decoding for Image Transmission

A Joint Source Channel Decoding for Image Transmission

Joint Source Channel Decoding Exploiting 2D Source Correlation with Parameter Estimation for Image Transmission over Rayleigh Fading Channels

This paper investigates the performance of a 2- Dimensional (2D) Joint Source Channel Coding (JSCC) system assisted with parameter estimation for 2D image transmission over an Additive White Gaussian Noise (AWGN) channel and a Rayleigh fading channel. Baum-Welsh Algorithm (BWA) is employed in the proposed 2D JSCC system to estimate the source correlation statistics during channel decoding. The source correlation is then exploited during channel decoding using a Modified Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. The performance of the 2D JSCC system with the BWA-based parameter estimation technique (2D-JSCC-PET1) is evaluated via image transmission simulations. Two images, each exhibits strong and weak source correlation are considered in the evaluation by measuring the Peak Signal Noise Ratio of the decoded images at the receiver. The proposed 2D-JSCC-PET1 system is compared with various benchmark systems. Simulation results reveal that the 2D-JSCC-PET1 system outperforms the other benchmark systems (performance gain of 4.23 dB over the 2D-JSCC-PET2 system and 6.10 dB over the 2D JSCC system). The proposed system also can perform very close to the ideal 2D JSCC system relying on the assumption of perfect source correlation knowledge at the receiver that shown only 0.88 dB difference in performance gain.

Design and analysis of LDPC codes for joint source‐channel decoding of two correlated sensors

This study is concerned with the design of ensembles of systematic low-density parity-check (LDPC) codes to increase the lifetime of wireless sensors by taking advantage of the inherent correlation between the transmitted data of the sensors. The authors consider two correlated sensors where the data is encoded independently at each sensor through a systematic LDPC encoder and sent over two independent channels. At the receiver, a joint source-channel decoder consisting of two component LDPC decoders is considered where the encoded bits at the output of each component decoder are used as the a priori information at the other decoder. The authors first perform asymptotic performance analysis using the concept of extrinsic information transfer (EXIT) charts. Then, the developed modified EXIT charts are used to design ensembles for different values of correlation. Our results show that as the average check node degree of the designed ensembles grow, the decoding thresholds corresponding to the designed ensembles approach the theoretical limit. Finite block-length performance evaluation indicates that for larger values of correlation, deploying the designed ensembles through the joint decoder can almost double the sensor's lifetime without increasing the complexity of the encoder.

Information unequal error protection using polar codes

Unequal error protection (UEP) divides the data into different levels of importance in order to ensure that the most important parts of the source information have more protection than the less important parts. In this study, the authors investigate the application of UEP using polar codes and propose a technique that utilises the channel polarisation property of these codes to achieve UEP without any significant modification. They demonstrate the error bounds of the proposed technique particularly within the context of JPEG2000. In addition, they propose a joint source-channel decoding method that is based on iterative decoding. This method takes the advantage of the error resilience tools that already exist in the JPEG2000 decoder. It will be shown that the proposed technique offers better performance than the conventional transmission with equal error protection.

Video Error Correction Using Soft-Output and Hard-Output Maximum Likelihood Decoding Applied to an H.264 Baseline Profile

Error concealment has long been identified as the last line of defense against transmission errors. Since error handling is outside the scope of video coding standards, decoders may choose to simply ignore corrupted packets or attempt to decode their content. In this paper, we present a novel joint source-channel decoding approach that can be applied to received video packets containing transmission errors. Soft-output information is combined with our novel syntax-element-level maximum likelihood decoding framework to effectively extract valid macroblocks from corrupted H.264 slices. Simulation results show that our video error correction strategy provides an average peak signal-to-noise ratio (PSNR) improvement near 2 dB compared to the error concealment approach used by the H.264 reference software, as well as an average PSNR improvement of 0.8 dB compared to state-of-the-art error concealment. The proposed method is also applicable when only hard-information is available, in which case it performs better than state-of-the-art error concealment especially in high error conditions. Finally, in our simulations, the proposed method increased the decoder computational complexity by only 5% to 20%, making it applicable for real-time applications.

EXIT Chart Analysis of Turbo Compressed Sensing Using Message Passing Dequantization

We propose an iterative decoding method, which we call turbo-CS, for the reception of concatenated source-channel encoded sparse signals transmitted over an AWGN channel. The turbo-CS encoder applies 1-bit compressed sensing as a source encoder concatenated serially with a convolutional channel encoder. At the turbo-CS decoder, an iterative joint source-channel decoding method is proposed for signal reconstruction. We analyze, for the first time, the convergence of turbo-CS decoder by determining an EXIT chart of the constituent decoders. We modify the soft-outputs of the decoder to improve the signal reconstruction performance of turbo-CS decoder. For a fixed signal reconstruction performance RSNR of 10 dB, we achieve more than 5 dB of improvement in the channel SNR after 6 iterations of the turbo-CS. Alternatively, for a fixed SNR of -1 dB, we achieve a 10 dB improvement in RSNR.

Optimal Viterbi Based Total Variation Sequence Detection (TVSD) For Robust Image/Video Decoding In Wireless Sensor Networks

In this letter, we propose a novel scheme for robust reconstruction, based on total variation regularization, towards image/video communication in multimedia wireless sensor networks. We derive the optimal joint source channel decoder as the combination of a maximum likelihood cost function and an anisotropic total variation norm based regularization factor. The proposed scheme exploits the bounded variation (BV) property of images and is thus ideally suited for reconstruction. Subsequently, it is demonstrated that the trellis based Viterbi decoder can be employed for robust image reconstruction using modified total variation state and branch metrics. Simulation results for BTC and JPEG encoded image transmission demonstrate a superior reconstruction performance for the proposed scheme in comparison to conventional methods.

Two-Dimensional Iterative Source-Channel Decoding for Distributed Video Coding

Motivated by the Joint Source-Channel Decoding (JSCD) principle of exploiting the source redundancy, in this treatise we study the application of iterative source-channel decoding (ISCD) conceived for distributed video coding (DVC), where the video signal is modelled by our Iterative Horizontal-Vertical Scanline Model (IHVSM) relying on a first-order Markov process. The IHVSM technique is combined with the classic forward error correction (FEC) codecs employed in the state-of-the-art DVC systems for the sake of reducing the bitrate. Our simulation results show that up to 21.5% bitrate reductions are achieved by employing the proposed ISCD technique in a DVC scheme. Alternatively, a peak signal-to-noise ratio (PSNR) gain of 2.2 dB is achieved at a bitrate of 4.5 Mbps when considering the Foreman sequence.

Motion-Aware Mesh-Structured Trellis for Correlation Modelling Aided Distributed Multi-View Video Coding

A joint source-channel coding has attracted substantial attention with the aim of further exploiting the residual correlation residing in the encoded video signals for the sake of improving the reconstructed video quality. In our previous paper, a first-order Markov process model was utilized as an error concealment tool for exploiting the intra-frame correlation residing in the Wyner-Ziv (WZ) frame in the context of pixel-domain distributed video coding. In this contribution, we exploit the interview correlation with the aid of an interview motion search in distributed multi-view video coding (DMVC). Initially, we rely on the system architecture of WZ coding invoked for multiview video. Then, we construct a novel mesh-structured pixel-correlation model from the inter-view motion vectors and derive its decoding rules for joint source-channel decoding. Finally, we benchmark the attainable system performance against the existing pixel-domain WZ coding based DMVC scheme, where the classic turbo codec is employed. Our simulation results show that substantial bitrate reductions are achieved by employing the proposed motion-aware mesh-structured correlation modelling technique in a DMVC scheme.

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

Since joint source-channel decoding (JSCD) 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 we 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, we derive reduced-complexity formulas for the first-order Markov modelling (FOMM) aided source decoding. Then we 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, we 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 financial support of the RC-UK under the auspices of the India-UK Advanced Technology Centre (IU-ATC) and that of the EU under the CONCERTO project as well as that of the European Research Council’s Advanced Fellow Grant is gratefully acknowledged. The softbit decoding is performed by a one-dimensional Markov model aided decoder. Our simulation results show that Eb=N0 improvements in excess of 2.8 dB are attainable by the proposed technique in uncompressed video applications.

Study on a New Joint Source-Channel Decoder Design

To improve upon the Low-Density Parity-Check (LDPC) codes , incorporating compressed sensing (CS) and information redundancy, a new joint decoding algorithm frame is presented. The proposed system exploits the information redundancy by CS reconstruction during the iterative decoding process to correct decoding of LDPC codes. The simulation results show that the algorithm presented can improve system decoding performance and obviously make bit error ratio (BER) lower then traditional LDPC codes. In addition, a relatively short argument is given on different CS reconstructed algorithms in proposed system, the new design is shown to benefit from different CS reconstructed algorithms.

Spatio-Temporal Iterative Source–Channel Decoding Aided Video Transmission

Low-complexity uncompressed video transmission meets the requirements of home networking and quality/delay-sensitive medical applications. Hence, it has attracted research attention in recent years. The redundancy inherent in the uncompressed video signals may be exploited by joint source–channel decoding to improve the attainable error resilience. Hence, in this treatise, we study the application of iterative joint source–channel decoding aided uncompressed video transmission, where correlation inherent in the video signals is modeled by a first-order Markov process. First, we propose a spatiotemporal joint source–channel decoding system using a recursive systematic convolutional codec, where both the horizontal and vertical intraframe correlations, as well as the interframe correlations, are exploited by the receiver, hence relying on 3-D information exchange. This scheme may be combined with arbitrary channel codecs. Then, we analyze the three-stage decoder's convergence behavior using 3-D extrinsic information transfer (EXIT) charts. Finally, we benchmark the attainable system performance against a couple of video communication systems, including our previously proposed 2-D scheme, where only intraframe correlations were exploited without invoking a channel codec. Our simulation results show that substantial $E_{b}/N_{0}$ improvements are attainable by the proposed technique.