Extrinsic Information Research Articles

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.

Asymmetric Dual-Mode Constellation and Protograph LDPC Code Design for Generalized Spatial MPPM Systems

To achieve reliable and efficient transmissions in free-space optical (FSO) communication, this paper designs a new protograph low-density parity-check (PLDPC) coded generalized spatial multipulse position modulation (GSMPPM) system over weak turbulence channels. Specifically, we investigate the PLDPC code, generalized space shift keying (GSSK) modulation, and MPPM constellation. First, we propose a type of novel GSMPPM constellations that intelligently integrates the GSSK into MPPM, referred to as asymmetric dual-mode (ADM) constellations, so as to improve the performance of the PLDPC-coded GSMPPM system. Furthermore, exploiting a protograph extrinsic information transfer (PEXIT) algorithm, we construct a type of improved PLDPC code, referred to as I-PLDPC code, which outperforms the existing PLDPC codes over weak turbulence channels. Analytical and simulation results show that the proposed ADM constellations and the proposed I-PLDPC code can obtain noticeable performance gains over their counterparts. Therefore, the proposed PLDPC-coded GSMPPM system with ADM constellations is competent to satisfy the high-reliability requirement for FSO applications.

Eye-Tracking Study of Cognitive Effort in Processing of Lexical Features in Students and Experts

In this paper, it is our aim to observe the impact that translator training and experience have on different groups of participants (novice, trained and experienced) when evaluating a translation. We will be doing so by measuring the cognitive effort invested by the participants in the processing of lexical features applying an eye-tracking methodology. Participants will be presented with several translated versions from English into Spanish done by translators with different levels of training and experience. This paper offers a detailed description of the experiment carried out. In it, we were also able to observe that while there are common patterns in the three groups, training and experience does have an impact on their behaviour when reading and assessing the different translated versions. We have been able to observe a link between these two factors and the amount of cognitive effort, which is higher in the group of students than in the group of experts, with trained participants leading the numbers, which we believe confirms the skill acquisition model proposed by Dreyfus (2004). Also, that extrinsic information is an element of disruption that influences the decisions made by participants, the amount of cognitive effort employed and how those lexical features have been processed.

Iterative Parallel–Serial Detection Structure Using MAP Algorithm for Bit-Patterned Media Recording Systems

In bit-patterned media recording (BPMR), data are modulated into the magnetic poles and stored in the magnetic islands. Thus, to increase the areal density (AD) of the storage device, we should reduce the distance between the magnetic islands. This leads to a two-dimensional (2-D) interference, wherein each island is affected by the neighboring islands. Therefore, to handle the 2-D interference, we proposed a parallel–serial structure of the detection based on the maximum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$a$ </tex-math></inline-formula> posteriori (MAP) algorithm. The equalized received signal was fed to two branches in parallel. One branch was in the order of horizontal and then vertical detections, and the other was in the reverse order of vertical and horizontal detections. With the MAP algorithm, the serial structure of two branches can improve the bit error rate (BER) performance of the detection. Moreover, we can extract the extrinsic information from the output of the MAP algorithm of two branches and create the iteration of the parallel structure. The original signal was restored with higher accuracy after each iteration. The simulation results showed that the iterative parallel–serial detection structure using MAP improved the BER performance compared to those in previous studies with only parallel or serial structures.

Doubly-Iterative Sparsified MMSE Turbo Equalization for OTFS Modulation

Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios. This paper proposes a doubly-iterative sparsified minimum mean square error (DI-S-MMSE) turbo equalizer, which iteratively exchanges the extrinsic information between a soft-input-soft-input (SISO) MMSE estimator and a SISO decoder. Our proposed equalizer does not suffer from short loops and approaches the performance of the near-optimal symbol-wise maximum a posteriori (MAP) algorithm. To exploit the inherent sparsity of OTFS system, we resort to graph theory to investigate the sparsity pattern of the channel matrix, and propose two sparsification guidelines to reduce the complexity of calculating the matrix inverse at the MMSE estimator. Then, we apply two iterative algorithms to MMSE estimation, i.e., the Generalized Minimal Residual (GMRES) and Factorized Sparse Approximate Inverse (FSPAI) algorithms. The former is used at the initial turbo iteration, whose global convergence is proven in our equalizer, while the latter is used at the subsequent turbo iterations with the help of our proposed guidelines. Simulation results demonstrate that our equalizer can achieve a good bit-error-rate (BER) performance regardless of the fractional Doppler, and only has a linear order of complexity.

Optimization of Protograph LDPC Codes via Surrogate Channel for Unequal Power Allocation

This paper investigates the possibilities of optimizing existing protograph low-density parity-check (PLDPC) codes and designing optimal PLDPC codes on both AWGN and Rayleigh channels under binary modulation with unequal power allocation (UPA) for nonuniform sources. While the binary UPA modulation achieves a power gain, it also results in unequal error protection on the coded bits in systematic codewords during transmission. For irregular codes, it is possible to best protect the information bits by optimizing the classification of variable nodes (VNs). Those VNs represent the coded bits in protograph that allows exploiting jointly the degree irregularity and the power differentiation. An algorithm for UPA-based protograph extrinsic information transfer (UPA-PEXIT) analysis on the Rayleigh channel is proposed with the concept of surrogate channel which circumvents the channel asymmetry problem with UPA. With the RJA code as example, it is shown that classification optimization does improve the decoding threshold when the source entropy is small. To design optimal codes, a UPA-based differential evolution (UPA-DE) algorithm is proposed in conjunction with the UPA-PEXIT analysis. A family of optimized codes are illustrated for three typical nonuniform source distributions and compared with the RJA and NND codes by simulations in error rate performance.

Analysis and Optimization of a General Linking Matrix for JSCC Scheme Based on Double LDPC Codes

A key component of the joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is the introduction of a linking matrix between the source LDPC code and channel LDPC code, by which the decoding information including the source redundancy and channel state information can be transferred iteratively. However, the linking matrix is a fixed one-to-one mapping, i.e., an identity matrix in a conventional D-LDPC code system, which may not take full advantage of the decoding information. Therefore, this paper introduces a general linking matrix, i.e., a non-identity linking matrix, connecting the check nodes (CNs) of the source LDPC code and the variable nodes (VNs) of the channel LDPC code. Further, the encoding and decoding algorithms of the proposed D-LDPC coding system are generalized. A joint extrinsic information transfer (JEXIT) algorithm is derived for calculating the decoding threshold of the proposed system with a general linking matrix. In addition, several general linking matrices are optimized with the aid of the JEXIT algorithm. Finally, the simulation results demonstrate the superiority of the proposed D-LDPC coding system with general linking matrices.

Design and Analysis of Joint Group Shuffled Scheduling Decoding Algorithm for Double LDPC Codes System.

In this paper, a joint group shuffled scheduling decoding (JGSSD) algorithm for a joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is presented. The proposed algorithm considers the D-LDPC coding structure as a whole and applies shuffled scheduling to each group; the grouping relies on the types or the length of the variable nodes (VNs). By comparison, the conventional shuffled scheduling decoding algorithm can be regarded as a special case of this proposed algorithm. A novel joint extrinsic information transfer (JEXIT) algorithm for the D-LDPC codes system with the JGSSD algorithm is proposed, by which the source and channel decoding are calculated with different grouping strategies to analyze the effects of the grouping strategy. Simulation results and comparisons verify the superiority of the JGSSD algorithm, which can adaptively trade off the decoding performance, complexity and latency.

Efficient systematic turbo polar decoding based on optimized scaling factor and early termination mechanism

In this paper, an efficient early termination (ET) mechanism for systematic turbo-polar code (STPC) based on optimal estimation of scaling factor (SF) is proposed. The gradient of the regression line which best fits the distance between a priori and extrinsic information is used to estimate the SF. The multiplication of the extrinsic information by the proposed SF presents effectiveness in resolving the correlation issue between intrinsic and extrinsic reliability information traded between the two typical parallel concatenated soft-cancellation (SCAN) decoders. It is shown that the SF has improved the conventional STPC by about 0.3 dB with an interleaver length of 64 bits, and about 1 dB over the systematic polar code (SPC) at a bit error rate (BER) of . A new scheme is proposed as a stopping criterion, which is mainly based on the estimated value of SF at the second component decoder and the decoded frozen bits for each decoding iteration. It is shown that the proposed ET results in halving the average number of iterations (ANI) without adding considerable complexity. Moreover, the modified codes present comparable results in terms of BER to the codes that utilize fix number of iterations.

Symbol-Level Detection With Matched Non-Binary LDPC Codes for Position Errors in Racetrack Memories

In racetrack memory (RM), insertion and deletion (ID) errors occur owing to alignment faults; such errors are referred to as position errors (PEs). Recently, several coding schemes for PEs have been proposed based on binary low-density parity-check (BI-LDPC) codes with a joint bit-wise (BW) detection and decoding algorithm. Although these schemes yield promising asymptotic performance, they suffer from unsatisfactory finite-length performance in short block sizes. To address this problem, we propose a novel coding scheme based on non-binary LDPC (NB-LDPC) codes and symbol-wise (SW) detection. The factor graph of the proposed scheme avoids generating cycles between the detector and decoder graphs by leveraging RM’s special property that multiple ID errors are caused by PEs simultaneously, which enables the attainment of good finite-length performance while providing fast convergence. With the aim of providing further performance improvement, we also provide an SW extrinsic information transfer chart analysis to design NB-LDPC codes for the proposed scheme.

Global Design of Double Protograph LDPC Codes for Joint Source-Channel Coding

In this letter, a global design of double protograph low-density parity-check (DP-LDPC) codes is proposed for joint source-channel coding (JSCC) system. The maximum number of degree-2 variable nodes (VNs), which is very important for the performance of the system, is determined from a global perspective that considers the joint protograph as a whole. Based on the allocation of degree-2 VNs, the new guidelines with this more comprehensive perspective are summarized and the global optimized DP-LDPC codes are designed. The simulation results that are in consistent with the joint protograph extrinsic information transfer (P-EXIT) analysis indicate that the optimized DP-LDPC codes have better performance compared with the existing re-designed DP-LDPC codes.

Irregular-Mapped Protograph LDPC-Coded Modulation: A Bandwidth-Efficient Solution for 6G-Enabled Mobile Networks

The huge amount of data produced in the 6G networks not only brings new challenges to the reliability and efficiency of mobile devices but also drives rapid development of new storage techniques. With the benefits of fast access speed and high reliability, NAND flash memory has become a promising storage solution for the 6G networks. In this paper, we investigate a protograph-coded bit-interleaved coded modulation with iterative detection and decoding (BICM-ID) utilizing irregular mapping (IM) in the NAND flash-memory systems. First, we propose an enhanced protograph-based extrinsic information transfer (EPEXIT) algorithm to facilitate the analysis of protograph codes in the IM-BICM-ID systems. With the use of EPEXIT algorithm, a simple design method is conceived for the construction of a family of high-rate protograph codes, called irregular-mapped accumulate-repeat-accumulate (IMARA) codes, which possess excellent decoding thresholds and linear-minimum-distance-growth property. Furthermore, motivated by the voltage-region iterative gain characteristics of IM-BICM-ID systems, a novel read-voltage optimization scheme is developed to acquire accurate read-voltage levels, thus minimizing the decoding thresholds (in dB) of protograph codes. Analyses and simulations indicate that the proposed IMARA-aided IM-BICM-ID scheme and read-voltage optimization scheme remarkably improve the convergence and decoding performance of flash-memory systems. Thus, the proposed protograph-coded IM-BICM-ID can be viewed as a reliable and efficient storage solution for the new-generation mobile networks, such as Internet of Vehicles.

Adaptive Curriculum Sequencing and Education Management System via Group-Theoretic Particle Swarm Optimization

The Curriculum Sequencing (CS) problem is a challenging task to tackle in the field of online teaching and learning system development. The current methods of education management might still possess certain drawbacks that would cause ineffectiveness and incompatibility of the whole system. A solution for achieving better user satisfaction would be to treat users individually and to offer educational materials in a customized way. Adaptive Curriculum Sequencing (ACS) plays an important role in education management system, for it helps finding the optimal sequence of a curriculum among various possible solutions, which is a typical NP-hard combinatorial optimization problem. Therefore, this paper proposes a novel metaheuristic algorithm named Group-Theoretic Particle Swarm Optimization (GT-PSO) to tackle the ACS problem. GT-PSO would rebuild the search paradigm adaptively based on the solid mathematical foundation of symmetric group through encoding the solution candidates, decomposing the search space, guiding neighborhood movements, and updating the swarm topology. The objective function is the learning goal, with additional intrinsic and extrinsic information from those users. Experimental results show that GT-PSO has outperformed most other methods in real-life scenarios, and the insights provided by our proposed method further indicate the theoretical and practical value of an effective and robust education management system.

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Novel techniques are conceived for joint compressive sensing (CS) and low-density parity check (LDPC) coding in wireless sensor networks (WSNs), namely, a soft-input soft-output (SISO) tree search sphere decoding (SD) technique and an SISO Hamming distance (HD)-based solution. Factor graphs are utilized to describe the connectivity between the signals and sensors, as well as with the LDPC codes. In the fusion center (FC), the factor graphs may be used for iterative joint LDPC-CS decoding in order to recover the signals observed. However, the CS decoder of the FC suffers from high complexity if the exhaustive Maximum A Posteriori (e-MAP) technique is employed, which considers all possible combinations of source signals detected by each of the associated sensors. Hence, in the proposed SD and HD schemes, only the more likely combinations of source signals are tested for reducing the CS decoding complexity. More specifically, a tree search technique is used in the first step to find the most likely combination of source signal values. Then, in the second step, the proposed SD continues the tree search to find a set of alternative hypotheses. This facilitates the generation of high-quality extrinsic information, which may be iteratively exchanged with the LDPC decoder. By contrast, in the HD approach, the second step obtains the alternative hypotheses within a certain HD of the most likely source signal combination. Both our BLock Error Rate (BLER) results and EXtrinsic Information Transfer (EXIT) charts show that the proposed SD and HD techniques approach the performance of the full-search e-MAP approach at a significantly reduced complexity. In particular, we show that the e-MAP solution is about 56 times more complex than the SD approach and around 210 times more complex than the HD approach. Compared to a separate source-channel coding (SSCC) hard information benchmarker, the proposed SISO schemes improve the decoding performance by about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${1}.{7} \text {dB}$ </tex-math></inline-formula> . Furthermore, the SISO schemes allow the iterations inside the CS decoding to eliminate the error floors and obtain a further <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${2}.{45}$ </tex-math></inline-formula> -dB gain.

Spatially-Coupled Faster-Than-Nyquist Signaling: A Joint Solution to Detection and Code Design

In this paper, we investigate two important issues of faster-than-Nyquist (FTN) signaling, namely, reduced-complexity detection and code design. Different from previous works, we consider these two issues jointly by designing a scheme that increases the minimum squared Euclidean distance of FTN signaling via repetition coding at a cost of an increased complexity. Furthermore, to reduce the rate loss of the repetition, we adopt the idea of spatially-coupling from coding theory to FTN signaling, and the resultant signaling scheme is therefore referred to as spatially-coupled faster-than-Nyquist (SC-FTN) signaling. The signal of SC-FTN signaling is generated in a continuous manner by interleaving and repeating the coded FTN signals and a graph-based iterative sliding-window detector is applied for signal detection. Both bounding and extrinsic information transfer chart analysis are provided to study the error-floor and convergence performances of SC-FTN signaling. These analyses unveil the intrinsic relationship between error floor, decoding threshold, and detection/decoding complexity, which provides guidelines for the designs of practical systems. Simulation results show that the promising error performance can be achieved with a simple FTN detection, where the bit error rate performance of coded SC-FTN signaling outperforms that of state-of-the-art coded FTN systems and the capacity of Nyquist signaling.

Analysis of LDPC Code in Hybrid Communication Systems

Free-space optical (FSO) communication is of supreme importance for designing next-generation networks. Over the past decades, the radio frequency (RF) spectrum has been the main topic of interest for wireless technology. The RF spectrum is becoming denser and more employed, making its availability tough for additional channels. Optical communication, exploited for messages or indications in historical times, is now becoming famous and useful in combination with error-correcting codes (ECC) to mitigate the effects of fading caused by atmospheric turbulence. A free-space communication system (FSCS) in which the hybrid technology is based on FSO and RF. FSCS is a capable solution to overcome the downsides of current schemes and enhance the overall link reliability and availability. The proposed FSCS with regular low-density parity-check (LDPC) for coding techniques is deliberated and evaluated in terms of signal-to-noise ratio (SNR) in this paper. The extrinsic information transfer (EXIT) methodology is an incredible technique employed to investigate the sum-product decoding algorithm of LDPC codes and optimize the EXIT chart by applying curve fitting. In this research work, we also analyze the behavior of the EXIT chart of regular/irregular LDPC for the FSCS. We also investigate the error performance of LDPC code for the proposed FSCS.

Residents' preference for the management of green tides and its determinants: The evidence from Qingdao, China

Green tides, which cause serious harm to the marine ecological environment, have become a serious and recurrent environmental event in China. This paper investigates the residents' willingness to pay for the governance of green tides. The results show that residents' willingness to pay (WTP) for the complete disappearance of green tides and the restoration of coastal environment to the state before green tides reaches 68.59 CNY/a (US $ 9.85) on average. Additionally, the study uses self-identity and information concern to reflect the differences of residents' intrinsic characteristics and the onslaught of the extrinsic information to empirically analyze the sources of the preference differentials. Risk perception, moral norms, and self-efficacy are further introduced to observe the influence mechanism. The results indicate that moral norms are the most important factors affecting the WTP, and a direct relationship between information concern and residents' WTP is observed. Self-identity does not show a direct impact on residents' preference, however, has an indirect influence through moral norms and self-efficacy. This paper helps to increase individual pro-environmental behaviors and provides references for the management of green tides.

A Joint Equalization and Decoding Technique for Multiuser Massive MIMO Uplink System With Transmitter and Receiver RF Impairments Under Doubly Selective Channels

The impairments due to in-phase and quadrature-phase imbalance at the transmitter and/or receiver, carrier frequency offset, and doubly selective channel (DSC) result in multiuser interference (MUI) and self-intercarrier interference (S-ICI) in multiuser massive multiple-input–multiple-output (MIMO) uplink systems. The MUI and S-ICI significantly deteriorate the performance of the receiver and make data detection quite a challenging task. To tackle this issue, we developed a novel crisscross banded effective channel matrix and a joint equalization and detection technique for multiuser massive MIMO single-carrier frequency division multiple access/orthogonal frequency division multiple access uplink systems with RF impairments under DSC. During each iteration of the proposed method, the MUI and S-ICI are calculated using the soft information from the decoder section, and then the interference canceled signal is fed back to the equalizer section for the joint equalization of the mirror subcarrier pairs. Since the proposed method does not put any restriction on the allocation of mirror subcarrier pairs, it is equally applicable to all types of carrier assignment schemes. Further, the extrinsic information transfer chart of the proposed technique is developed for analyzing the convergence. Extensive simulation studies are conducted to validate the performance of the proposed technique.

Performance analysis and design of quasi-cyclic LDPC codes for underwater magnetic induction communications

Magnetic induction (MI) communication is an effective scheme for underwater wireless communication. In this paper, we aim to design an underwater MI communication system based on Quasi-cyclic LDPC (QC-LDPC) codes. Firstly, for a given QC-LDPC code used in underwater MI communication, we propose a novel algorithm to evaluate its performance, which is named as underwater magnetic induction protograph (UWMIP) extrinsic information transfer algorithm. Furthermore, we present a differential evolution UWMIP (DE-UWMIP) algorithm, which incorporates the differential evolution method and the UWMIP algorithm. By this algorithm, we search the optimized QC-LDPC codes with best distance threshold. Simulation results show that the proposed algorithm is effective and provide a good guidance to design the underwater MI communication 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.