This paper presents a formal framework for cooperative and collision-free scheduling of autonomous vehicles at signal-free intersections. The core of our approach leverages Timed Petri Nets (TPN) to model intersection traffic as a verifiable resource allocation system, ensuring strict safety guarantees through spatial-temporal partitioning. A key innovation is the integration of a transformer-based prediction module that captures complex vehicle interactions, enabling accurate passing-order decisions. Combined with adaptive model predictive control (MPC), this transformer-enhanced strategy coordinates multiple intersections in real-time. Simulation results demonstrate an 18~22% reduction in congestion delays compared to conventional methods. Designed for 6G-enabled Intelligent Internet of Things (IIoT) infrastructures, the framework supports ultra-reliable low-latency communication and edge intelligence, providing a robust solution for next-generation transportation networks.

This paper introduces a distributed edge intelligence framework for secure and efficient data sharing in 6G-Internet-of-Vehicles (6G-IoV) environments. The approach integrates a hierarchical blockchain architecture with an innovative asynchronous federated learning algorithm to address the challenges of privacy preservation, communication efficiency, and scalability in 6G-IoV scenarios. The proposed framework employs a multi-layer structure comprising vehicles, roadside units, and cloud servers, each playing a distinct role in the distributed learning process. We present a comprehensive latency model that accounts for computation and communication aspects, considering the unique characteristics of vehicular networks. The asynchronous federated learning algorithm incorporates genetic algorithm-based resource optimization to adaptively allocate communication resources, significantly enhancing efficiency in heterogeneous 6G-IoV environments. Furthermore, we introduce the hierarchical edge intelligence consensus mechanism, a lightweight consensus protocol tailored for edge intelligence scenarios, which accelerates blockchain consensus while maintaining security. Simulations using MNIST and SVHN datasets demonstrate that the proposed framework outperforms state-of-the-art methods regarding model accuracy, communication efficiency, and privacy preservation.

The rapid evolution of transportation cyber-physical systems (T-CPS) has led to unprecedented advancements in mobility and efficiency. However, ensuring the safety and reliability of these complex systems remains a critical challenge, particularly in verifying and refining their temporal behaviors. This paper presents a novel compositional approach for temporal behavior analysis and synthesis in safety-critical T-CPS, the safety-critical temporal analysis, and refinement for the T-CPS (STAR-TCPS) framework, which combines iterative compositional verification with L*-based learning techniques to analyze and refine timing behaviors efficiently. The method leverages the clock constraint specification language for high-level timing specifications and introduces a systematic refinement process to transform abstract requirements into implementable task models. The framework incorporates innovative constraint handling mechanisms tailored for T-CPS, addressing unique challenges such as vehicle-to-infrastructure communication delays and adaptive traffic management timing. Experimental evaluations, including a case study on an intelligent vehicle system, demonstrate STAR-TCPS’s superiority over existing methods. Results show significant improvements in verification time (up to 63% reduction), memory usage (44% decrease), and task generation efficiency (18-25% fewer tasks) compared to state-of-the-art approaches. The STAR-TCPS framework enhances T-CPS’s safety and reliability by enabling more efficient verification and refinement of critical timing properties, paving the way for safer and more robust transportation systems.

Considering the extremely low signal-to-noise ratio (SNR) environment in future satellite internet of Things (IoT) transmission in which the traditional Hamming coded LoRa (Long Range) system in the ground IoT communication is of difficulty to guarantee high reliability, optimal coding scheme selection for the LoRa-based satellite IoT is studied for the first time. In specific, the corresponding system model is described in detail, followed by derivations of two noncoherent detection methods of coded LoRa signals. Subsequently, the channel capacity of the coded LoRa system is provided and used to develop the corresponding relationship between the signal-to-noise ratio (SNR) and the code rate. Based on the obtained relationship and the Monte-Carlo method, it is found that the coded LoRa system with different spreading factors (SFs) can achieve the lowest SNR when the code rate is close to 1/2. Finally, the performance of several coded LoRa systems (including Hamming code, BCH code, RS code, Turbo code, LDPC code and LDGM code with code rates of about 1/2) is compared by means of the Monte-Carlo method. Simulation results show that Turbo or LDPC coded LoRa systems exhibit more than 4.5 dB performance advantages over the Hamming coded LoRa system.

In this paper, we concentrate on one algebraic-based quasi-cyclic low-density parity-check (QC-LDPC) code constructed from two subsets of a finite field and generalize it to propose a class of variable-rate QC-LDPC (VR-QC-LDPC) codes, whose parity-check matrices are nested horizontally and have constant number of rows. Thus the proposed codes are significant at least in terms of storage complexity and can be simply implemented. The constructed codes also inherit the original algebraic-based QC-LDPC codes and their exponent matrices can be obtained from two subsets of the given finite field. We hereby analyze the structural properties from the isomorphism perspective, and present some rules to significantly prune the size of search space and determine the non-isomorphic exponent matrices. By distinguishing the smaller quantities of non-isomorphic matrices with cycle property metric, we can easily construct a series of nested exponent matrices with better cycle distributions and obtain the VR-QC-LDPC codes. Numerical results demonstrate that the constructed codes have better iterative decoding performance within a range of code rates and decoding iterations.

Data collection is an essential operation in wireless sensor networks (WSNs). Topology control and duty-cycle are two popular schemes in WSNs to improve the utilization of various network resource. The problem of low-cost topology control in duty-cycle wireless sensor networks is investigated in this paper. Due to each sensor's awake/sleep schedule, the topological graphs in duty-cycle WSNs are changed over time. A space-time graph model is presented to describe the dynamics of a series of topological graphs. The new topology control problem in a spacetime graph is defined, and then two heuristic algorithms are proposed to find the low-cost topological structures, in which the connectivity from each sensor to the sink is maintained. Simulations validate the effectiveness of the proposed algorithms.

Routing design is an effective mechanism to improve the energy‐efficiency in packet transmissions for wireless multihop networks. Meanwhile, the total energy consumption for packet transmissions over a path comprising of several unreliable links depends on the power assignment on each link. In this study, the authors address the energy‐efficient routing, which integrates with the optimal power assignment, in end‐to‐end (E2E) retransmission systems. The process of packet transmission across a path in E2E systems is modelled as a random walk. The expected energy consumed for the packet transmission is then calculated. As the expected energy consumption closely relies on the transmit power assigned on the path, it is necessary to integrate the power assignment into the energy‐efficient routing. The optimal power assignment on the candidate path is analytically derived for minimising the expected energy consumption. Specially, the energy‐efficient routing integrated with power sssignment (EERPA) algorithm is developed to find the optimal path among all candidate paths with all possible power assignments. Simulations demonstrate the efficiency of the authors' EERPA algorithm.

In this paper we consider the generalization of binary non-uniformly coupled low-density parity-check (LDPC) codes to that over Galois field GF (2m). We will perform an iterative decoding threshold analysis for this class of non-uniformly coupled LDPC ensembles formed by randomly coupled and protograph-based coupled ensembles, respectively. By optimizing the coupling among spatial positions, we can construct codes having excellent thresholds and small rate-loss. Moreover, we propose a list-aided windowed decoding (list-aided WD) scheme for nonbinary SC-LDPC codes with low decoding latency. Numerical results show that the list-aided WD which outperforms conventional WD can perform better performance and lower decoding latency than the flooding-schedule decoding at low SNRs on the additive white Gaussian noise channel.

This paper presents a nonbinary low-density parity-check (LDPC) coded spatial modulation (CSM) for multiple-input multiple-output communication systems, in which the information bits for choosing active transmit antennas and the bits for choosing constellation signals are protected by a nonbinary LDPC code. We apply a many-to-one mapping known as Gallager mapping to signal constellation, resulting in an improved constellation design for the CSM system. Furthermore, we propose a Gallager mapping-based scheme to solve the design problem of the CSM system with arbitrary transmit antennas, in which Gallager mapping is used to map the index information bits to the active antenna, thus an integer-bit transmission can be achieved for any number of transmit antennas. With the use of nonbinary LDPC codes, a non-iterative receiver is able to recover the undistinguished information caused by the many-to-one mapping. Several communication scenarios are studied and simulation results show that the proposed scheme can offer substantial performance gains with design flexibility over the Rayleigh fading channel.

This paper presents a family of rate‐compatible (RC) globally coupled low‐density parity‐check (GC‐LDPC) codes, which is constructed by combining algebraic construction method and graph extension. Specifically, the highest rate code is constructed using the algebraic method and the codes of lower rates are formed by successively extending the graph of the higher rate codes. The proposed rate‐compatible codes provide more flexibility in code rate and guarantee the structural property of algebraic construction. It is confirmed, by numerical simulations over the AWGN channel, that the proposed codes have better performances than their counterpart GC‐LDPC codes formed by the classical method and exhibit an approximately uniform gap to the capacity over a wide range of rates. Furthermore, a modified two-phase local/global iterative decoding scheme for GC‐LDPC codes is proposed. Numerical results show that the proposed decoding scheme can reduce the unnecessary cost of local decoder at low and moderate SNRs, without any increase in the number of decoding iterations in the global decoder at high SNRs.

Quasi‐cyclic (QC) LDPC codes play an important role in 5G communications and have been chosen as the standard codes for 5Genhanced mobile broadband(eMBB) data channel. In this paper, we study the construction of QC LDPC codes based on an arbitrary given expansion factor (or lifting degree). First, we analyze the cycle structure of QC LDPC codes and give the necessary and sufficient condition for the existence of short cycles. Based on the fundamental theorem of arithmetic in number theory, we divide the integer factorization into three cases and present three classes of QC LDPC codes accordingly. Furthermore, a general construction method of QC LDPC codes with girth of at least 6 is proposed. Numerical results show that the constructed QC LDPC codes perform well over the AWGN channel when decoded with the iterative algorithms.

This paper proposes a two-stage decoding algorithm (called BP-LED) for short nonbinary low-density parity-check (LDPC) codes. It consists of the classical belief propagation (BP) decoder and a list erasure decoder (LED). Simulation results show that, for the (16, 8) LDPC code over GF(256) in the CCSDS standard, our proposed BP-LED algorithm can achieve a coding gain of 0.6 dB with respect to the FFT-QSPA. By choosing the parameters suitable for the proposed algorithm, it has a negligible performance loss with lower decoding complexity compared with the BP-MRB (most reliable basis) algorithm in [10].

In this paper, we investigate the application of nonbinary LDPC codes to spatial modulation, and a nonbinary LDPC coded spatial modulation (NBLDPC- SM) system is proposed. In the system, the symbols for choosing the active antennas and the symbols for choosing constellation signals are protected by a nonbinary LDPC code. Furthermore, we combine the NBLDPC-SM system with Gallager mapping, a method of constellation shaping, to improve the system spectral efficiency. We demonstrate that such NBLDPC-SM system can achieve low probability of bit error at near SM capacity. Several communication scenarios are investigated to verify good performance of the proposed system and simulation results are also given to provide substantial performance gains in different channel conditions.

Sparse code multiple access (SCMA) is a promising technique to meet the requirements for massive capacity in 5G communications. In this paper, a nonbinary LDPC- coded SCMA system with a turbo receiver is proposed. We also provide a heuristic approach based on Cartesian product and Euclidean distance to construct the SCMA codebook, which greatly reduces the detection complexity and can be easily extended to large-size constellations. Furthermore, the codebook design for large SCMA systems is presented, and the sparse structure is optimized via the construction of matrices with optimized cycle distribution. Simulation results show that the nonbinary LDPC-coded SCMA system is much more compatible with high-order modulation than its binary counterpart, and the proposed design outperforms the original SCMA codebook design in both the error probability and complexity even in large loading situations.