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A new method for low-complexity near-maximum-likelihood (ML) decoding of low-density parity-check (LDPC) codes over the additive white Gaussian noise channel is presented. The proposed method termed belief-propagation--list erasure decoding (BP-LED) is based on erasing carefully chosen unreliable bits performed in case of BP decoding failure. A str...
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... 3) the output layer with one neuron. BP neural network is the learning process of error back propagation (EBP), which includes positive information propagation and backward error propagation [41]. Forward propagation is processed layer by layer from the input layer 6 VOLUME , This article has been accepted for publication in IEEE Open Journal of the Communications Society. ...
In this paper, the reliability and security of ambient backscatter (AmBC) non-orthogonal multiple access (NOMA) systems on Nakagami-m distribution are studied. When an eavesdropper exists, the transmitter communicates with two NOMA users through the power domain multiplexing technology and successful interference cancellation (SIC) technology. Actually, assuming that in-phase and quadrature-phase imbalance (IQI) is present in all nodes. To be specific, the precise expressions of the outage probability (OP) and intercept probability (IP) are derived. And Monte Carlo simulation coincides better with the theoretical images, which confirms the accuracy of theoretical derivation. A surprising discovery is that IQI diminishes the reliability of considered networks but strengthens confidentiality. Moreover, the decrease of the average signal-to-noise ratio (SNR) of the link from the transmitter to the eavesdropper can enhance the security. Furthermore, according to the back-propagation (BP) neural networks, we provide a forecast method to achieve real-time analysis of the security performance. Comparing to the popular machine learning algorithms, the results show that the prediction time is shorter and the prediction accuracy is averagely increased by 91.2%. Meanwhile, similar results can be obtained in the prediction of other communication models, which proves that the prediction algorithm has positive applicability.
... number of ''1'', so it is also called low-density parity code, which is also based on this unique sparsity to construct its low complexity and high performance characteristics [9], [10]. It is also considered to be one of the most superior error correction codes based on the following ad-vantages: 1) Approximate Shannon limit, for example, irregular LDPC code (r=1/2), in binary input AWGN (Gaussian white noise channel), when the code length is 107, the difference between the distribution of times and Shannon limit is only 0.0045dB [11]; 2) Parallel decoding operation and simple implementation; ...
The number of ways to obtain information has increased by 5th Generation Mobile Communication Technology commercial. But easier access to information also means more security issues. Digital watermarking is an effective method to solve the security problem of information. Aiming at the problems of one-dimensional single chaotic image encryption algorithm, such as simple structure, small key space, and the invisibility and robustness of traditional information hiding technology cannot be well reconciled. The improved encryption algorithm based on Low Density Parity Check Code and double Logistic chaotic system is proposed, which can expand the key space, reduce the bit error rate, and enhance the security and anti-interference ability of the system. The feasibility, reliability and practicability of the algorithm are verified by MATLAB simulation.
... 22 Compared to other coding schemes, 23 LDPC codes have proven the ability to facilitate reliable communication even under unreliable channel conditions. 24 However, the formulation of an LDPC decoding algorithm for the current and next generation communication standards is a challenging task. The main hurdle faced by the research community is to impart a potential in the decoding process to analyse and evaluate the large number of error patterns without increasing the computational overhead. ...
... 30 To overcome this bottleneck situation, several research proposals were put forward by the research community. [22][23][24] Figure 4 depicts the taxonomy of soft-decision-based LDPC decoding algorithms. From the taxonomy illustration, LDPC codes are classified into three main categories, namely, BPA, 4 SPA 5 and MSA. ...
Information theory coding is an impressive and most celebrated field of research that has spawned numerous extremely important solutions to the intractable problems of secure data communications. Recent advancements in error control coding methods have seen a huge surge in using low‐density parity‐check (LDPC) code‐based decoding algorithms to solve imperative issues related to reliable data transmission and reception. Till date, extensive research efforts have been consistently being made on LDPC codes which focus on algorithm‐driven and hardware‐realization‐based approaches. The main intension of this research work is to provide an extensive systematic elucidation on the recent advancements in LDPC decoding algorithms. In addition, a thorough performance evaluation and analysis of several outstanding LDPC decoding techniques is presented. Finally, conclusions are drawn by summarizing the important research findings, interesting open problems, current challenges and broader perspectives for future directions of research. Overall journal publication count related to LDPC codes published over the years. A comprehensive review of various LDPC decoding algorithms and its key attributes which provides a useful insight about the unique technical ideas of each algorithm. A taxonomy and classification of LDPC decoding algorithms which emphasizes their distinctive research endeavours. A qualitative analysis, which demonstrates the error correction capability and computational complexity of various LDPC decoding algorithms. A unified performance evaluation of various LDPC decoding algorithms proposing possibilities for future research.
... The decoding complexity of high-rate LDPC codes, however, still remains an issue as they typically have a much larger check-node degree d c as compared with low-rate codes. When decoded with the Sum-Product Algorithm (SPA) in the Log-Likelihood Ratio (LLR) domain [16], the conventional check-node operation based on forward/back recursions [17], [18] has a complexity growing linearly with d c , which is computationally intensive for large values of d c . ...
... For clarity purposes, we take the conventional notations of LDPC decoding used in the literature, e.g., [16], [17]. Let us denote the set of bits that participate in check m by N(m)={n: H mn =1}, and the set of checks in which bit n participates as M(n)={m: H mn =1}, m=0,…, M−1 , n=0,…, N−1. ...
In this paper, we propose a fully graph-based iterative detection and decoding scheme for Low-Density Parity-Check (LDPC) coded generalized two-dimensional (2D) intersymbol interference (ISI) channels. The 2D detector consists of a downtrack detector based on the symbol-level sum-product algorithm (SPA) and a bit-level SPA-based crosstrack detector. A LDPC decoder based on simplified check node operations is also proposed to provide soft information for the 2D channel detector. Numerical results show that the proposed receiver achieves better performance as compared with the trellis-based BCJR detector over 2×2 2D channels while at a significantly lower computational complexity.
... Most recently, the work carried out by Mhamdi et al. [11] have used turbo coding system for enhancing the wireless transmission of image encoded by JPEG2000 standard. Low-Density Parity Check (LDPC) is another frequently used approach for encoding image and claimed to offer better optimized performance as seen in the work of Deng et al. [12] and Bocharova et al. [13]. The work of Matin et al. [14] has applied optical encoding system along with the potential of compressive sensing for better optimized results of image transmission. ...
Various encoding schemes have been introduced till date focusing on an effective image transmission scheme in presence of error-prone artifacts in wireless communication channel. Review of existing schemes of channel encoding systems infer that they are mostly inclined on compression scheme and less over problems of superior retention of signal retention as they lacks an essential consideration of network states. Therefore, the proposed manuscript introduces a cost effective lossless encoding scheme which ensures resilient transmission of different forms of images. Adopting an analytical research methodology, the modeling has been carried out to ensure that a novel series of encoding operation be performed over an image followed by an effective indexing mechanism. The study outcome confirms that proposed system outshines existing encoding schemes in every respect.
... Out of these groups, 2500 groups are used for training, while the remaining 50 groups are used for testing. Using the simulation parameters given in Table III, Figs. 8 to 21 show the prediction performance of the ICS-BP, LWLR [31], SVM [32], ELM [33], BP [34], GR [35], and RBF [36] methods. The MSE of the proposed ICS-BP method is 0.000821, which is the lowest out of all the methods. ...
In the field of transportation, the Internet of Vehicles (IoV) is an important component of the Internet of things. The vehicle-to-vehicle communication is particularly challenging in mobile IoV networks because they are operated in complex and highly variable environments. The mobile IoV transmission interruption level can be evaluated by the outage probability (OP) performance. If the OP performance can be analyzed and predicted accurately, the quality of service (QoS) in the mobile IoV networks can be improved. However, the analysis and prediction of mobile IoV transmission channels is very challenging because they are highly dynamic. In this paper, the analysis and prediction of the OP performance for mobile IoV networks are investigated. A hybrid decode-amplify-forward (HDAF) relaying scheme with transmit antenna selection (TAS) is considered. The exact OP expressions are derived in a closed form, and the analytical results are verified. To realize real-time analysis of the OP performance, an intelligent OP prediction algorithm based on the improved cuckoo search (ICS) is presented. The proposed algorithm is compared with different methods and the results show that it has a better OP prediction performance.The prediction accuracy of ICS-BP can be increased by 51.8% compared with the existing algorithms.
... LDPC Codes [52] used belief-propagation (BP) as the decoding algorithm. Further [73] improves the Frame-Error-Rate by employing (BP)-list erasure decoders at the cost of increased complexity. Such decoders provide gain of 0.8 dB for FER of 0.1. ...
Although 4G (fourth generation) i.e. LTE (long term evolution) systems are now in use world-wide. But today’s 4G systems have some challenges left such as spectrum scarcity and energy efficiency. The prime objectives of near-by-future 5G (fifth generation) wireless communications are reliability, higher data rate, higher bandwidth, high spectrum efficiency, higher energy efficient and that too at lower latency. Channel coding tend to increase the reliability of the wireless communications system by adding extra bits in a controlled fashion and is considered to be most persuasive element of communication system. 4G LTE Turbo Codes have already been replaced by LDPC (low density parity check) Codes in many of the standards including mMTC (massive machine type communication), D2D (device to device communication) and URLLC (ultra-reliable low latency reliable communications). LDPC Codes and Polar Codes are securing much more observation because of their inherent advantages of excellent bit-error-rate performance, fast encoding and decoding procedures; which make them the strong contenders for 5G Channel Codes too. This paper provides the broad survey and comparison of the LDPC and Polar Codes along with their advantages and drawbacks which will aid in further improvement of the next generation wireless networks. In order to enlighten future research possibilities in this direction, issues addressed by distinct researchers have been explored too.
With the construction process of smart cities, cyber-physical systems (CPS) are going to become a link to connect all things with intelligence. The low-density parity check (LDPC) code is an import information encryption format in computer networks. In this article, from the perspective of LDPC code decoding algorithm scheduling strategy, we design a dynamic check node scheduling (DCNS) strategy for extended min-sum LDPC decoding in cyber-physical systems. In this strategy, the reliability of the node is checked to determine whether to update. For the un-updated variable node, it is optimized according to the results of real-time scheduling. Compared with the flooding mechanism and LBP scheduling of the usual algorithms, this proposed scheduling strategy improves the error correction performance by selecting some nodes for decoding and performing message optimization, while not significantly increasing the decoding computation. Especially, compared with the LBP, the bit error rate and frame error rate of the proposed algorithm are reduced by 48.3% and 53.2% on average in the finite domain 64F range. Compared with BP, the bit error rate and frame error rate of the proposed algorithm are reduced by 11.3% and 13.2% on average in the finite domain 64F range.
Layered Normalised Min-Sum algorithm is a widely used message passing algorithm for decoding Low Density Parity Check codes. The decoding performance heavily depends on the normalisation factor. Firstly, we leverage the bit structure present in 5G transport blocks to develop an improved decoding algorithm for 5G. Secondly, we determine the optimal normalisation factors of the proposed algorithm using a Deep Neural Network. Performance evaluations show an improvement of 0.3-1.9 dB, with no extra cost on multiplier resources on hardware. Hence, the proposed method is highly attractive for practical 5G decoder implementations.
