Source Decoding Research Articles

Cosmic Baby and the r-process Nucleosynthesis

Astrophysical origin of the rapid neutron capture process (i.e., r-process) remains a mystery. Among the known r-process sites radio-actively powered kilonova, produced by binary neutron star mergers, attracted the astronomers a promising source in the light of gravitational wave radiation. The first detected binary neutron star merger event GW170817 confirmed the existence of binary neutron star (BNS) in nature while its associated properties such as transient electro-magnetic emission in the form of x-rays, long and short gamma ray bursts (l, s GRBs), First Radio Bursts (FRBs) offer the astronomer to rethink about the origin of the r-process abundances in the light of Magnetars, created in both supernova explosion and also in neutron star merger, as a r-process contributor. Recently detected Cosmic Baby i.e. Swift J1818.0 – 1607 is a young magnetar of 240 years aged with super-strong magnetic fields ~ 8.9424 x 1017 G and ellipticity ~ 9 x 10-3. Due to its youngness among the 31 detected magnetars till today, it may provide x-ray lines emitted by the r-process abundances which makes it as an important promising source in the eyes of LOFT, NuSTAR detectors. This author proposes that this cosmic baby can be considered as a suitable astrophysical source decoding of its observed results may unravel the realistic situations of the magnetar at the time of merger, supernova explosion, etc. for generation of super heavy elements like Eu, Ti.

Rate-Compatible Protograph LDPC Codes for Source Coding in Joint Source—Channel Coded Modulation Systems

Using the source residual redundancy in a joint source and channel coded modulation (JSCCM) system to achieve a shaping gain has proven to be a good solution for probabilistic amplitude shaping. In a JSCCM system, rate-compatible source codes are essential for adapting to dynamically changing source probabilities. However, conventional rate-compatible source codes are not appropriate for JSCCM systems, since they may yield a loss in the shaping gain. Moreover, a code design that depends solely on the source decoding threshold appears to be ill suited, thus complicating the search for good source codes. In this paper, we propose a rate-compatible family of source codes for JSCCM systems based on an achievable system rate analysis and the source protograph extrinsic information transfer (PEXIT) algorithm. The proposed codes not only have good source decoding thresholds but also obtain shaping gains over the whole considered range of source probabilities. Numerical results show that the proposed rate-compatible family of source codes can significantly improve the bit-error-rate (BER) performance of the JSCCM system.

Double Polar Codes for Joint Source and Channel Coding

In this paper, we design a joint source and channel coding (JSCC) framework combining the source polar coding and the channel polar coding. The source is first compressed using a polar code (PC), and source check decoding is employed to construct an error set containing the index of all source decoding errors. Then, the proposed JSCC system employs another PC or systematic PC (SPC) to protect the compressed source and the error set against noise, which is called double PC (D-PC) or systematic double PC (SD-PC), respectively. For a D-PC JSCC system, we prove a necessary condition for the optimal mapping between the source PC and the channel PC. On the receiver side, by introducing the joint factor graph representation of the D-PC and SD-PC, we propose two joint source and channel decoders: a joint belief propagation (J-BP) decoder, and a systematic joint belief propagation (SJ-BP) decoder. In addition, a biased extrinsic information transfer (B-EXIT) chart is developed for various decoders as a theoretical performance evaluation tool. Both B-EXIT and simulation results show that the performance of the proposed JSCC scheme has no error floor and outperforms the turbo-like BP decoder.

Design and Analysis of Joint Source-Channel Code System with Fixed-Length Code

As the demands of multimedia and data services increase, efficient communication systems are being investigated to meet the high data rate requirements. Joint source-channel coding (JSCC) schemes were proposed for improving overall system performance. However, existing JSCC systems may suffer a symbol error rate (SER) performance loss when residual source redundancy is not fully exploited. This paper presents a novel, low-complexity JSCC system, which consists of a fixed-length source block code and an irregular convolutional channel code. A simple approach is proposed to design source codes that minimize the SER of source detection and guarantee the convergence of iterative source-channel decoding (ISCD). To improve the waterfall performance of ISCD, the channel code is optimized by using the extrinsic information transfer (EXIT) chart and the concept of irregular code. The channel code is constituted by recursive non-systematic convolutional (RNSC) subcodes. The weights of subcodes are optimized to make the EXIT curves of the channel decoder and the source decoder well-matched, and therefore, a near-capacity performance is achieved. Simulation results show that the proposed system achieves more than 1 dB gains and 0.3 dB gains compared to the separate source-channel code system and the other optimal JSCC systems, respectively. Additionally, the performance of the proposed system is within 1 dB deviation from the Shannon limit capacity.

Design and Implementation of a Fully Flexible Cognitive Radio Modem

Software-defined radio (SDR)-based cognitive communication radio systems are very popular at present, and there have been many investigations on this topic. This paper proposes a new type of cognitive radio transceiver (TRX) that can detect, recognize, and analyze input signals in real-time with minimal data loss. New hardware is designed and manufactured that combines a transmitter and a receiver in a dedicated integrated circuit. For data processing, a field-programmable gate array (FPGA) is used. For each integrated hardware block, appropriate software modules are developed to construct a complex adaptive radiocommunication system as a radio modem that can be configured as a transceiver or repeater. The source coder, channel coder, modulator, spectrum monitoring module, spectrum analyzer, channelizer, symbol rate detector, modulator, modulation type recognition module, demodulator, channel decoder and source decoder are all developed as software modules.

Polysemantic allusion in a polycultural dimension: definition, structure and semantics (based on Pratchett’s Discworld)

The paper introduces the notion of polysemantic allusion in a polycultural dimension, explored in its semantic, structural and functional facets, based on intertextual contextual interpretative, structural, taxonomic, archetypal analyses added by some inferential pragmatics tools. Polysemantic allusion (PA) is defined as an intertextuality device, which combines two and more facultatively decoded meanings due to their association with more than one precedent source situations, texts or phenomena. The markers of PA include the modified and altered precedential names, designating the literary text or extra-textual sphere of denotation, symbolic or archetypal references of precedential situation or text; a science-associated terms or their structural part, which must satisfy the ambiguity and optional decoding of the precedential sources triggered by the PA. The markers of polysemantic allusion may be one, two- and multicomponent with each structural part capable of creating additional allusive connotations in its unfolding in further context. PA involves several levels of semantic interpretation, which correlate with various precedent texts and differ in degrees of implicitness of the allusive meanings, interpreted with an attraction of the optimally relevant context, implicating, strengthening, confirming or contradicting the hypothetic allusive assumptions. Semantic components of PA may encompass hypertextual references providing coherent relations between Pratchett’s novels, and architextual meanings associated with parodying various genres.

Joint Early Stopping Criterions for Protograph LDPC Codes-Based JSCC System in Images Transmission.

In this paper, a joint early stopping criterion based on cross entropy (CE), named joint CE criterion, is presented for double-protograph low-density parity-check (DP-LDPC) codes-based joint source-channel coding (JSCC) systems in images transmission to reduce the decoding complexity and decrease the decoding delay. The proposed early stopping criterion adopts the CE from the output likelihood ratios (LLRs) of the joint decoder. Moreover, a special phenomenon named asymmetry oscillation-like convergence (AOLC) in the changing process of CE is uncovered in the source decoder and channel decoder of this system meanwhile, and the proposed joint CE criterion can reduce the impact from the AOLC phenomenon. Comparing to the counterparts, the results show that the joint CE criterion can perform well in the decoding complexity and decoding latency in the low–moderate signal-to-noise ratio (SNR) region and achieve performance improvement in the high SNR region with appropriate parameters, which also demonstrates that this system with joint CE is a low-latency and low-power system.

On the Performance of Video Resolution, Motion and Dynamism in Transmission Using Near-Capacity Transceiver for Wireless Communication.

This article investigates the performance of various sophisticated channel coding and transmission schemes for achieving reliable transmission of a highly compressed video stream. Novel error protection schemes including Non-Convergent Coding (NCC) scheme, Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (NCDSTS-SP) scheme and Convergent Coding assisted with DSTS and SP modulation (CDSTS-SP) are analyzed using Bit Error Ratio (BER) and Peak Signal to Noise Ratio (PSNR) performance metrics. Furthermore, error reduction is achieved using sophisticated transceiver comprising SP modulation technique assisted by Differential Space Time Spreading. The performance of the iterative Soft Bit Source Decoding (SBSD) in combination with channel codes is analyzed using various error protection setups by allocating consistent overall bit-rate budget. Additionally, the iterative behavior of SBSD assisted RSC decoder is analyzed with the aid of Extrinsic Information Transfer (EXIT) Chart in order to analyze the achievable turbo cliff of the iterative decoding process. The subjective and objective video quality performance of the proposed error protection schemes is analyzed while employing H.264 advanced video coding and H.265 high efficient video coding standards, while utilizing diverse video sequences having different resolution, motion and dynamism. It was observed that in the presence of noisy channel the low resolution videos outperforms its high resolution counterparts. Furthermore, it was observed that the performance of video sequence with low motion contents and dynamism outperforms relative to video sequence with high motion contents and dynamism. More specifically, it is observed that while utilizing H.265 video coding standard, the Non-Convergent Coding assisted with DSTS and SP modulation scheme with enhanced transmission mechanism results in gain of 20 dB with reference to the Non-Convergent Coding and transmission mechanism at the objective PSNR value of 42 dB. It is important to mention that both the schemes have employed identical code rate. Furthermore, the Convergent Coding assisted with DSTS and SP modulation mechanism achieved superior performance with reference to the equivalent rate Non-Convergent Coding assisted with DSTS and SP modulation counterpart mechanism, with a performance gain of 16 dB at the objective PSNR grade of 42 dB. Moreover, it is observed that the maximum achievable PSNR gain through H.265 video coding standard is 45 dB, with a PSNR gain of 3 dB with reference to the identical code rate H.264 coding scheme.

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.

Analysis and Improvement of Error-Floor Performance for JSCC Scheme Based on Double Protograph LDPC Codes

In a joint source-channel coding (JSCC) system, excessive source compression can cause an error floor. In the original JSCC scheme based on double protograph LDPC (DP-LDPC) codes, only connections exist between check nodes (CNs) of the source protograph and variable nodes (VNs) of the channel protograph, and error floors are observed. In this paper, we investigate the joint protograph that forms the basis of a DP-LDPC code. The joint protograph consists of a source protograph, a channel protograph, and connections between the two protographs. Our main focus is on the complete-source-variable-linking (CSVL) protomatrix of the joint protograph, which determines the error floor of the DP-LDPC code. We propose a generalized source protograph extrinsic information transfer (GSP-EXIT) algorithm for evaluating the source decoding thresholds of the CSVL protomatrix. Based on the proposed algorithm, we analyze CSVL protomatrices with regular or irregular source protographs. We present design criteria for connections between VNs of the source protograph and CNs of the channel protograph. Such design rules will result in a higher source decoding threshold, which implies a lower error floor. We also propose a differential evolution algorithm for optimizing the source protograph. We present/compare analytical results and/with simulation results, and conclude that they are consistent.

Joint Shuffled Scheduling Decoding Algorithm for DP-LDPC Codes-Based JSCC Systems

In this letter, a joint shuffled scheduling decoding algorithm for double-protograph low-density parity-check (DP-LDPC) codes-based joint source-channel coding (JSCC) schemes is presented. The proposed algorithm adopts the shuffled scheduling method to both source decoder and channel decoder, and can improve convergence speed and reduce the decoding complexity. In addition, a unique phenomenon named unequal convergence rates is revealed at the same time. The proposed algorithm can terminate this phenomenon with faster decoding. The results show that this algorithm has faster convergence speed and better error performance, compared with the traditional joint belief propagation (BP) decoding algorithm.

EEG source localization using spatio-temporal neural network

Source localization of focal electrical activity from scalp electroencephalogram (sEEG) signal is generally modeled as an inverse problem that is highly ill-posed. In this paper, a novel source localization method is proposed to model the EEG inverse problem using spatio-temporal long-short term memory recurrent neural networks (LSTM). The network model consists of two parts, sEEG encoding and source decoding, to model the sEEG signal and receive the regression of source location. As there does not exist enough annotated sEEG signals correspond to specific source locations, simulated data is generated with forward model using finite element method (FEM) to act as a part of training signals. A framework for source localization is proposed to estimate the source position based on simulated training data. Experiments are done on simulated testing data. The results on simulated data exhibit good robustness on noise signal, and the proposed network solves the EEG inverse problem with spatio-temporal deep network. The result show that the proposed method overcomes the highly ill-posed linear inverse problem with data driven learning.

EEG source localization using spatio-temporal neural network

Source localization of focal electrical activity from scalp electroencephalogram (sEEG) signal is generally modeled as an inverse problem that is highly ill-posed. In this paper, a novel source localization method is proposed to model the EEG inverse problem using spatio-temporal long-short term memory recurrent neural networks (LSTM). The network model consists of two parts, sEEG encoding and source decoding, to model the sEEG signal and receive the regression of source location. As there does not exist enough annotated sEEG signals correspond to specific source locations, simulated data is generated with forward model using finite element method (FEM) to act as a part of training signals. A framework for source localization is proposed to estimate the source position based on simulated training data. Experiments are done on simulated testing data. The results on simulated data exhibit good robustness on noise signal, and the proposed network solves the EEG inverse problem with spatio-temporal deep network. The result show that the proposed method overcomes the highly ill-posed linear inverse problem with data driven learning.

Decoding of motor imagery EEG based on brain source estimation

The decoding of Motor Imagery EEG (MI-EEG) is the most crucial part of biosignal processing in the Brain-computer Interface (BCI) system. The traditional recognition mode is always devoted to extracting and classifying the spatiotemporal feature information of MI-EEG in the sensor domain, but these brain dynamic characteristics, which are derived from the cerebral cortical neurons, are reflected more immediately and obviously with high spatial resolution in the source domain. With the development of neuroscience, the state-of-the-art EEG Source Imaging (ESI) technology converts the scalp signals into brain source space and excavates the way for source decoding of MI-EEG. Minimum Norm Estimate (MNE) is a classical and original EEG inverse transformation. Due to the lack of depth weighting of dipoles, it may be more suitable for the estimation of superficial dipoles and will be slightly insufficient for further source classification. In addition, the selection of a Region of Interest (ROI) is usually an essential step in the source decoding of MI-EEG by Independent Component Analysis (ICA), and the most relevant independent component of original EEG signals is transformed into the equivalent current dipoles to obtain the ROI by ESI. Although the excellent results of this method can be obtained for unilateral limb motor imaging EEG signals, which shows more distinct phenomena of event-related desynchronization (ERD), the decoding accuracy may be restricted for more complex multi-limb motor imagery tasks, whose ERD is no longer evident. Therefore, in this paper, we propose a novel brain source estimation to decode MI-EEG by applying Overlapping Averaging (OA) in the temporal domain and Weighted Minimum Norm Estimate (WMNE), which overcomes the limitations of general ROI-based decoding methods and introduces weighting factors to complement the estimation of deep dipoles. Its advantages will be evaluated on a public dataset with five subjects by comparing it with MNE, WMNE, sLORETA, OA-MNE and ICA-WMNE. The proposed method reaches a higher average decoding accuracy of 81.32% compared to other methods by 10-fold cross-validation at the same chance level. This study will increase the universality of the source decoding and facilitate the development of a BCI system in the source domain.

Channel Code Using Constrained-Random-Number Generator Revisited

A construction of a channel code by using a source code with decoder side information is introduced. The encoder and decoder pair of any source code can be used for the construction. Constrained-random-number generators, which generate random numbers satisfying a condition specified by a function and its value, are used to construct stochastic encoders and decoders. The result suggests that we can divide the channel coding problem into the problems of channel encoding and source decoding with side information.

Distributed Joint Source Coding and Trellis Coded Modulation for Symbol-Based Markov Sources

A distributed joint source-channel coding scheme based on a unity-rate code (URC) assisted trellis coded modulation (TCM) is proposed, which exploits the spatiotemporal correlation of symbol-based sources. More specifically, asymmetric distributed source coding of two spatially correlated Markov sources is considered, where one of the sources is assumed to be perfectly decoded and to be available at the receiver of the other source as side information. In order to exploit the temporal correlation statistics, an iterative decoding process exchanging extrinsic information between the amalgamated URC-assisted TCM and a soft-symbol source decoder employing a modified symbol-based maximum a posteriori algorithm is invoked. Furthermore, the Slepian–Wolf (SW) bound of symbol-based sources having spatiotemporal correlation is derived and the benefits of exploiting the spatiotemporal correlation using the proposed coding scheme are demonstrated by our extrinsic information transfer chart analysis. It is shown from our simulation results that upon exploiting the spatiotemporal correlation of the sources, the proposed coding scheme is capable of operating within 0.02 b of the SW bound.

The Design of Protograph LDPC Codes as Source Codes in a JSCC System

Although joint source-channel coding (JSCC) based on double protograph low-density parity-check (LDPC) codes has been shown to be an excellent solution for wireless communication, the protograph LDPC code for source coding needs to be optimized to improve the error-floor performance. In this letter, first, it is found that optimized protograph LDPC codes for channel coding are not optimal for source compression, which indicates that the source codes in the JSCC systems need to be designed specifically. Second, a rate-1/2 source code is designed by using the source decoding threshold as evaluation criteria. Finally, low rate source codes are designed by code lengthening. The protograph extrinsic information transfer analysis and the bit error rate simulation have shown that the proposed source codes obtain higher source decoding thresholds than conventional codes, which extend the range of compressible source entropies and improve the error-floor performance in the JSCC system.

An enhancing reversible data hiding for secured data using shuffle block key encryption and histogram bit shifting in cloud environment

Nowadays there are numerous intruders trying to get the privacy information from cloud resources and consequently need a high security to secure our data. Moreover, research concerns have various security standards to secure the data using data hiding. In order to maintain the privacy and security in the cloud and big data processing, the recent crypto policy domain combines key policy encryption with reversible data hiding (RDH) techniques. However in this approach, the data is directly embedded resulting in errors during data extraction and image recovery due to reserve leakage of data. Hence, a novel shuffle block key encryption with RDH technique is proposed to hide the data competently. RDH is applied to encrypted images by which the data and the protection image can be appropriately recovered with histogram bit shifting algorithm. The hidden data can be embedded with shuffle key in the form of text with the image. The proposed method generates the room space to hide data with random shuffle after encrypting image using the definite encryption key. The data hider reversibly hides the data, whether text or image using data hiding key with histogram shifted values. If the requestor has both the embedding and encryption keys, can excerpt the secret data and effortlessly extract the original image using the spread source decoding. The proposed technique overcomes the data loss errors competently with two seed keys and also the projected shuffle state RDH procedure used in histogram shifting enhances security hidden policy. The results show that the proposed method outperforms the existing approaches by effectively recovering the hidden data and cover image without any errors, also scales well for large amount of data.

SIMULATION BASED VIDEO COMPRESSION THROUGH DIGITAL COMMUNICATION SYSTEM

The paper is about the transmission, compression, detection of the video based on simulation for the various communication applications. The video and image compression overcomes the problem of reducing the amount of data required to the information that has to be transmitted and this saves the bandwidth required for transmission of data and memory which is required for storage purpose. Hence video compression reduces the volume of the video data with a small change in quality of the video. Compressed video transmission can be done over a channel by huffman coding for the source at transmitter side and then channel codes is done by technique called hamming. The data which is to be sent through channel is a BPSK modulated so the received data is demodulated followed by the channel decoding, source decoding using inverse of the techniques used in the transmitter side to obtain the original transmitted video. The above procedure is done for the input video taken by camera and this compressed video can be transmitted then detected at receiver by digital communication system(DCS) which is simulated in the MATLAB.

Joint Cooperative Beamforming and Jamming for Physical-Layer Security of Decode-and-Forward Relay Networks

This paper proposes a new joint cooperative beamforming and jamming (JCBJ) scheme for improving the physical layer security of decode-and-forward wireless networks where a source node transmits to its destination with the aid of multiple intermediate nodes in the presence of an eavesdropper. In the proposed JCBJ scheme, we select the intermediate nodes succeeding in source decoding as the relays to forward the source transmission simultaneously by employing a beamforming weight vector, and meanwhile, use the remaining ones as the friendly jammers to disturb the eavesdropper by sending artificial noise. In order to achieve the secrecy rate maximum, we further study on the power allocation among the source, relays, and jammers under two assumptions of the wiretap link's channel state information. We derive the closed-form optimal solutions by first allocating the transmit power at the source within different ranges to consider all the possible relay selection schemes in which different numbers of relays are employed, and then transforming the multivariable power allocation problem to a set of single-variable optimization subproblems. Our numerical results show the superiority of the proposed JCBJ scheme and the proposed power allocation strategies.