In this paper, we address a number of weaknesses of the windowed decoding of spatially coupled low-density parity-check (SC LDPC) codes and propose three modifications that simultaneously improve its performance, complexity, and latency. An effective termination method of the windowed decoding and the reuse of edge messages of previous target symbols provide a good performance-latency tradeoff when compared with the conventional windowed decoder. Also, we propose a scheme that lowers the error floor, in which the amplified edge messages of the previous window are used in the present window. The proposed windowed decoding, consisting of the three schemes, provides a significant performance gain with smaller latency. The validity of the new windowed decoding is verified by the evaluation with codes from different SC LDPC ensembles.

Sharing is undoubtedly one of the most important features of 6G networks, and blockchain can provide an extended trust-as-a-service (TAAS) distributed sharing solution for 6G networks. However, as a special distributed technology system, blockchain naturally needs to face the “impossible triangle” problem: in the case of ensuring security and decentralization, scalability will inevitably become the Achilles heel of the blockchain system. This article will design a high-throughput blockchain system for 6G networks to achieve trusted sharing and efficient scheduling of network infrastructure, assist future networks in integrating an open Internet architecture, and realize the combination of openness and distributed control. We adopt a shard blockchain design and incorporate digital twins and federated learning; formulate an optimization model for maximizing the throughput of the blockchain network by getting the optimal number of shards, also analyzing other factors affecting the throughput such as service distribution; propose a security performance analysis model for the blockchain network to describe the measures taken against the Byzantine attacks on the network. Analysis and simulation results show that the transaction throughput of the proposed method can reach more than 30 times larger than that of a nonsharding scheme. They also show that when one-third of the nodes in the system are attacked, the consensus of the system is hardly affected; even if the number of nodes being attacked at the same time reaches half of the total number of nodes, the probability of the occurrence of failed shards is still less than $10^{-4}$ , and the system still has good survivability.

Smart manufacturing has become a vital technique for increasing productivity and efficiency. Firms are following a smart manufacturing implementation system to compete in the market. Therefore, it is mandatory to find the crucial factors that enable the implementation of intelligent manufacturing in enterprises. This study proposes the framework for a new model factory based on the three-dimensional model that extends the product lifecycle layer. It also analyzes the significant attributes and interdependence relationships of causes and effects through the fuzzy DEMATEL approach for the selected small and medium enterprises discussed as a case study. The results show that the factors in Region 1 are significant attributes that need to be focused on for the development and establishment of small and medium enterprises under consideration. These attributes include design documentation (A11), intelligently management of small and medium enterprises (A3), visualization and monitoring of logistics and production (A6), flow of information, energy, and materials (A12), management platform and data acquisition for equipment (A7), and visualization of quality and process (A5). The sensitivity analysis is also performed to check the results’ validity, reliability, and robustness. This study aids any manufacturing firm in analyzing the critical attributes that contribute to implementing smart manufacturing.

Blockchain is an effective technology that enables secure data sharing and trusted energy trading in smart grids (SGs). The consensus algorithm plays a key role in the blockchain’s security and consistency. However, due to nonconcurrency, long consensus time, low throughput, and high transaction fees, current consensus algorithms are not suitable for SGs, where there is a large-scale distributed wireless field area network (FAN) with limited resources and frequent small transactions. In this paper, we propose a performance analysis model and a new consensus algorithm for the tangle in the FAN. First, we propose an analytical analysis model for the consensus time and probability of a successful parasitic chain attack on the FAN by comprehensively considering the number of data transmission hops, communication protocols, computing resources and checked tips. Furthermore, based on the analysis, a new consensus algorithm is proposed by clustering nodes cooperating with each other to complete the proof of work (PoW). Finally, we show the accuracy of the analysis results by comparing them with the simulation results. Additionally, we show that the proposed consensus algorithm can reduce the required consensus time by approximately 50%.

To perform reliable information processing in quantum computers, quantum error-correction (QEC) codes are essential for the detection and correction of errors in the qubits. Among QEC codes, topological QEC codes are designed to interact between the neighboring qubits, which is a promising property for easing the implementation requirements. In addition, the locality to the qubits provides unusual tolerance to local errors. Recently, various decoding algorithms based on machine learning have been proposed to improve the decoding performance and latency of QEC codes. In this work, we propose a new decoding algorithm for surface codes, i.e., a type of topological codes, by using convolutional neural networks (CNN) tailored for the topological lattice structure of the surface codes. In particular, the proposed algorithm takes advantage of the syndrome pattern which is represented as a part of a rectangular lattice given to the CNN as its input. The remaining part of the rectangular lattice is filled with a carefully selected incoherent value for better logical error-rate performance. In addition, we introduce how to optimize the hyper-parameters in the CNN, according to the lattice structure of a given surface code. This reduces the overall decoding complexity and makes the CNN-based decoder computationally more suitable for implementation. The numerical results show that the proposed decoding algorithm effectively improves the decoding performance in terms of logical error-rate as compared to the existing algorithms, on various quantum error models.

In this letter, protograph-based folded spatially coupled (FSC) LDPC codes are proposed. The new folded-type structure is obtained by folding the spatial coupling chain of a conventional SC LDPC protograph and interlacing the nodes at staggered spatial positions. The proposed codes outperform the SC LDPC codes over single and multiple random-burst erasure channels. We extend the construction of the folded-type structure by connecting multiple one-sided SC LDPC chains for higher resilience to burst erasure channels. The FSC LDPC codes are also compatible with windowed decoder and outperform conventional SC LDPC codes.