Ultra-reliable and low-latency communication (URLLC) is becoming a critical component of the wireless networks, particularly in applications like Internet of Things (IoT). Thanks to the development of communication theory in the past few decades, we have a foundational understanding of the trade-off between reliability and latency. This paper provides a new perspective to understand this trade-off by examining its impact on the timeliness and accuracy of actual systems, rather than simply pursuing high reliability or low latency. Specifically, age of information (AoI) and estimation error of dynamic systems over communication channels are our study objects, which are determined by reliability and latency. The closed-form expressions of average AoI and bounded AoI with respect to block length for general communication systems using rateless codes over binary erasure channels are derived, revealing the existence of the minimum value of the two AoI metrics about block length. We extend the universal conclusion to practical scenarios where application-layer rateless codes are combined with dynamic systems. The average AoI and estimation error of the proposed system are characterized as functions of communication reliability and latency. Furthermore, considering the correlation between reliability and latency, we substitute coding parameters into reliability and latency to determine the optimal coding parameters in terms of average AoI and estimation error of the proposed system.

The industrial Internet of Things (IIoT), particularly in the context of 6G-enabled networks, has greatly accelerated the industrial data sharing. While data sharing realizes large-scale data circulation, it also brings numerous data security problems. Fortunately, ciphertext-policy attribute-based encryption (CP-ABE) can effectively ensure the confidentiality of data and achieve the high granularity of access control. However, with the development of quantum computers, CP-ABE based on bilinear pairing is theoretically vulnerable to potential quantum attacks, and current CP-ABE based on ring learning with error (CP-ABERLWE) schemes suffer from limitations in efficiency, privacy, and dynamism. In view of the above problems, this paper proposes an efficient and revocable attribute-based encryption scheme based on ring learning with error (RLWE) with hidden policy for 6G-enabled IIoT. Our scheme is sINDCPA secure under the RLWE assumption, which can resist the quantum attack. We design an online/offline encryption algorithm based on RLWE and linear secret-sharing scheme, enhancing the encryption efficiency for 6G-enabled IIoT. The online/offline encryption also enables devices to complete policy hiding during the offline phase, thereby reducing the impact of the policy hiding on the encryption efficiency. We design efficient update keys to implement an effective RLWE-based indirect revocation. We develop a RLWE-based policy hiding that hides attribute values containing sensitive information within ciphertexts. The analysis proves that our scheme is secure and efficient.

This paper proposes an enhanced version of the CFS signature scheme, leveraging QC-LDPC codes with puncturing and random insertion techniques. The puncturing process is designed based on the selection of minimum Hamming weight codewords, ensuring that the remaining structure of the parity-check matrix retains sufficient error-correcting capabilities. Random insertion of new rows into the punctured parity-check matrix further enhances security by introducing randomness. The cyclic structure of QC-LDPC codes greatly reduces the key size while the BP decoding algorithm improves the decoding success rate, thereby enhancing the signature generation efficiency. The scheme proposed in this paper reduces the key size to 6144 bytes compared to the original CFS scheme's 6283256 bytes under the similar parameters setting. Additionally, the average number of signing attempts is reduced from$t!$to a constant multiple of$t$. It also greatly enhances security compared to recent improvements, particularly in resisting structural attacks, Stern's attacks, OTD attacks, and forgery attacks. Similar to the original CFS scheme, the proposed scheme can be proven to satisfy Existential Unforgeability under Chosen Message Attacks (EUF-CMA) security.

In multimodal communication, the importance of different modalities varies due to factors such as the nonuniform distribution of information, differences in error tolerance, variations in information redundancy, network environment, and bandwidth limitations, as well as the synergistic effects between modalities. During transmission, due to network conditions and bandwidth constraints, it may not be possible to transmit the information of each modality to the receiver in an intact form to perform multimodal tasks. In response to the transmission characteristics and the unequal error protection requirements described above, this paper proposes an end-to-end multimodal rateless codes unequal error protection scheme from the perspective of logical links. We also introduced a feedback mechanism to implement algorithms such as adaptive code length adjustment, adaptive degree distribution, adaptive weight rotation allocation, and maximum weight constraints. Compared to previous schemes, the proposed solution in this paper further reduces the decoding overhead and recovery latency of less important modality, thus improving resource utilization.

With the Internet of Things (IoT) playing an increasingly crucial role in connecting diverse devices, applications have different requirements for communication and various evaluation metrics have emerged, such as Age of Information (AoI) and estimation error. Considering the fundamental trade-off between reliability and latency of the communication system, the relationship among reliability, latency, AoI and estimation error is complex. This paper proposes a remote state observation system with application-layer rateless codes to explore above relationships, addressing how to design the system for optimal performance based on varying requirements by adjusting coding parameters. By emphasizing flexible and adaptable coding strategies, we aim to convey the idea that the error-correction codes can be designed to optimize the communication system for diverse practical metrics. It is different from the traditional designs that focus on approaching the Shannon limit.

Currently, the majority of authentication mechanisms in Vehicular Ad Hoc Networks (VANETs) are predominantly based on Elliptic Curve Cryptography (ECC). However, with the rise of quantum computing, traditional cryptographic algorithms such as RSA and ECC face significant security threats, underscoring the need for exploring alternative cryptographic approaches that can provide robust security guarantees in a post-quantum era. The National Institute of Standards and Technology (NIST) is working on the standardization of quantum-resistant public-key cryptographic algorithms, with code-based cryptosystems emerging as a promising alternative. In this paper, we introduce a code-based anonymous authentication scheme tailored for VANETs. Our approach leverages code-based group signatures to ensure both anonymity and traceability, facilitating efficient user registration and revocation through fully dynamic group signatures. By utilizing punctured and randomly inserted QC-MDPC codes, we significantly reduce key sizes while enhancing resistance to attacks. Compared to conventional number-theoretic VANET authentication schemes, our method exhibits strong security and quantum resistance. Compared to recent code-based cryptographic solutions, our scheme notably decreases key sizes without increasing signature lengths. Security proofs and analyses validate that our scheme offers high security and meets essential requirements such as anonymity, traceability, nonframeability, and tracing soundness. Efficiency evaluations further demonstrate that our proposal is the first to achieve code-based anonymous authentication scheme for VANETs with constant signature size.

The Industrial Internet of Things (IIoT) is an important cornerstone to realize the fourth industrial revolution. Data sharing is one of the key elements of IIoT, and cloud-edge–device technology is a new paradigm for achieving data sharing. In multiuser scenarios of IIoT, guaranteeing data privacy and granting fine-grained access control over data for senders and receivers is important. Matchmaking attribute-based encryption (MABE) can solve the above issues. However, current MABE schemes have a fatal problem: they ignore the malicious behaviors of data owners (DOs). In particular, there are three malicious behaviors: 1) malicious DOs encrypt data with a pernicious way; 2) malicious DOs release improper data; and 3) a malicious DO does not encrypt the ciphertext with the claimed access structure and attributes. Moreover, current MABE schemes require large computations, which are not suitable for resource-constrained IIoT. Hence, this article proposes an attribute-based bilateral access control with trust management and sanitization for IIoT called TS-MABE. For the first malicious behavior, TS-MABE uses sanitization to rerandomize ciphertexts, destroying ciphertexts encrypted in a pernicious way to make them lose information. For other malicious behaviors, TS-MABE uses trust management to evaluate the DO based on the data user’s evaluation of the ciphertext. If a DO publishes improper data, data users make poor evaluations due to low data quality. If a DO does not embed the claimed access structure or attributes into the ciphertext, data users cannot actually complete the decryption or match and make poor evaluations. DOs are afraid of being punished for low trust values, so that they dare not make malicious behaviors. Through analysis, TS-MABE is safe and efficient, suitable for IIoT.

The main performance challenge of industrial automation communication networks is the end to end latency-bounded reliability from an industry 4.0 perspective. However, the existing degree distributions for the design of rateless codes have not been optimized for industrial automation scenarios, especially lack of adaptability, flexibility, modifiability, scalability and robustness for different industrial tasks. To solve this problem, this paper proposes an intelligent degree distribution (IDD) based on deep reinforcement learning. The simulation results show that the IDD can greatly reduce the latency and improve the reliability for matching the different industrial scenarios compared with the other methods.

The Industrial Internet is the combination of traditional industry and Internet technology to achieve intelligent, automated, information-based, and networked production modes. From the closed industrial environment to the open Internet network environment, data sharing in the industrial scenario is facing various risks brought by an open network. Ciphertext policy attribute-based encryption (CP-ABE) can guarantee industrial data confidentiality while achieving precise and flexible access control. However, the current CP-ABE schemes cannot fully meet the requirements of the Industrial Internet, due to inefficient algorithms, incomplete functionality, poor dynamic monitoring capability, and separation from the Industrial Internet framework. Therefore, this article proposes a unified CP-ABE data security sharing scheme matching the Industrial Internet framework. To decrease the local calculation cost of the industrial device, outsourced encryption is implemented by using multiple computing nodes to encrypt the subkeys, respectively. Online/offline encryption can be outsourced to computing nodes. Attribute revocation can efficiently update the revoked user’s private key. Search-related costs are all constant. To enhance the dynamic monitoring, trust is set as an attribute and is updated adaptively in time through the attribute revocation algorithm. To further improve the security of data sharing, encapsulation is combined with on-chain ciphertext storage, which not only prevents symmetric ciphertext from being stolen and tampered with but also modifies the ciphertext component of the key ciphertext as needed. The scheme also realizes functions, including outsourced decryption and policy hiding. The scheme can resist the chosen plaintext and keyword attack, and ensure the forward and backward security of attribute revocation. By analysis and experiment, although our scheme achieves massive functions, it also has excellent algorithm efficiency.

The scale of industrial Internet networks contin-ues to grow, and equipment intelligence continues to improve. Traditional industrial Internet security solutions can no longer meet the requirements of privacy and efficiency. Trust man-agement is an effective way to promote security, efficiency, and scalability in Industrial Internet networks. In this paper, a dy-namic trust management model for the Edge Devices in the Industrial Internet based on the feedback under the edge com-puting architecture is proposed. We divide trust into two parts, direct trust and indirect trust. The model calculates the direct trust between devices based on long-term and short-term trust. Long-term and short-term trust help honest devices restore their trust as soon as possible after experiencing short-term trust decline. They can also prevent dishonest devices from obtaining higher trust due to short-term honest behavior. Be-sides, the model calculates the indirect trust of the edge broker to devices based on the reward-punishment mechanism. The mechanism improves the accumulation speed of the indirect trust of honest devices and reduces the indirect trust of dishon-est devices rapidly. The trust fusion algorithm is then used to aggregate the direct and indirect trust to calculate the compre-hensive trust of the device. Experimental results show that the proposed model outperforms the existing methods in local and global performance in different attack scenarios.

With the development of 5G and ultrareliable and low-latency communication (URLLC), wireless network for automation processes has important applications in the envisioned Industry 4.0. In general cloud control, communication and control systems are generally designed independently, which leads to substantial wireless resource consumption. This article analyzes and summarizes the existing communication–control co-design methods. The strong correlations between control and communication systems are analyzed and two kinds of communication–control co-design methods are summarized: 1) control optimization problem with communication constraints and 2) communication optimization problem with control constraints. This article proposes to find the essence of the co-design problem and then build an effective co-design model. Therefore, one of the use cases, the cloud control of automated guided vehicle (AGV) in a future factory, is presented. It is critically challenging to find the interaction between the AGV control system and communication system and build the co-design model. The coding rate threshold is optimized by adjusting control parameters. This article reveals that applying the communication–control co-design can lower the requirements on the coding rate and lower the consumption of wireless resources. This co-design method also achieves better results in the probability of system instability and the number of admissible AGVs.

With the thriving of digitalization in industry and the rapid development of cloud computing and Internet of Things (IoT), it has become a growing trend to integrate industrial control with the cloud platform to form industrial cloud control systems (ICCSs). However, ICCSs bring great challenges to legacy communication networks, especially, wireless networks, on reliability and determinacy. This article utilizes fountain code as application-layer coding to provide high-reliability low-latency deterministic communication for ICCSs. According to the simulation results, fountain code scheme, especially, RaptorQ code significantly improves communication reliability. The performance difference of fountain codes between time-critical use cases and nontime-critical use cases provides another perspective to analyze and evaluate fountain codes. Then, we propose a self-adaptive coding parameter selection method based on different industrial use cases, to better meet the communication requirements and reduce the coding cost.

Carrier Aggregation (CA) is introduced by 3GPP to support much wider transmission bandwidth and higher data rate by aggregating multiple component carriers (CC). In the LTE-Advanced (LTE-A) systems with CA, the CC selection method is of great significance to the system efficiency and fairness because user equipment (UEs) may have different capabilities of aggregating carriers. This paper proposes a novel UE preference based dynamic CC selection (UP-DCS) algorithm to optimize system throughput, with an emphasis on dynamic load balancing among the CCs. UEs select their preferred CCs on the basis of both the load and channel conditions of different CCs. Simulation results demonstrate that the proposed algorithm can achieve a better system performance in terms of throughput, coverage and fairness compared to the existing algorithms.

In order to meet the growing demand of higher transmission rate, carrier aggregation (CA) technology has been proposed in 3GPP Release 10. In a backward compatible LTE-Advanced (LTE-A) system with CA, a well-designed component carrier (CC) selection scheme is critically significant for system performance, especially when lots of user equipment (UE) with different CA capabilities are coexisted. This paper presents a novel dual priority CC selection (DPCS) algorithm, considering not only UE's CA capability but also carrier load and channel conditions on different CCs. Simulation results demonstrate that the given algorithm is able to improve the system performance in terms of throughput and fairness compared to the existing algorithms.

In this paper, we investigate three-dimensional (3D) multi-user (MU) multiple-input multiple-output (MIMO) transmission for long term evolution advanced (LTE-A) downlink systems. We investigate some key techniques for 3D MU-MIMO to improve the performance of LTE-A systems, including rank and precoding matrix (PM) determination and user pairing. To reduce the complexity caused by a large number of co-scheduled users in 3D MU-MIMO, we develop a simplified and high efficient 3D MU-MIMO scheduling algorithm. The performance improvement of the proposed algorithm is demonstrated by system level simulation.

In this paper, we investigate three-dimensional (3D) multiple-input multiple-output (MIMO) techniques with dynamic rank selection for long term evolution advanced (LTE-A) downlink cellular networks. To facilitate users to transmit different numbers of data streams, we develop a new structure for designing 3D precoding matrix (PM). Then based on the designed PM, 3D MIMO transmission with rank adaptation is proposed. The performance improvement of the proposed algorithms is demonstrated by system level simulation.

In this paper, we investigate mode selection for coordinated multi-point (CoMP) transmission in downlink LTE-A networks, where inter-cluster interference exists. The proposed scheme selects the single-cell (SC) or coordinated beamforming (CB) transmission mode according to interference level to maximize the weighted sum rate with fairness consideration. To formulate the optimization problem, an approximated closed-form expression for the achievable rate is derived by modeling the probability distributions of signal and interference powers as Gamma distributions. Since the original optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity and sub-optimal algorithm is proposed, which first performs coordinated cell selection and then transmission mode selection. Simulation results show that the closed-form approximation of the achievable rate is very tight and the proposed mode selection scheme can improve the average system throughput by 13% and the 10th percentile user throughput by 10% compared with the existing scheme.

Multi-cell coordinated beamforming (CB) can mitigate inter-cell interference. However, previous study on CB focuses on systems with only one receive antenna. This paper considers CB for systems with multiple receive antennas. To take fairness among scheduled users into account, CB is designed to maximize the harmonic sum of signal-to-interference-plus-noise ratio (SINR). We develop an iterative algorithm that can guarantee convergence. Simulation shows that the proposed algorithm have 70% and 47% throughput gains over single cell beamforming for 10th percentile user throughput and median user throughput, respectively.

In LTE uplink systems, single-carrier frequency-division multiple access (SC-FDMA) has been employed. In SC-FDMA, orthogonal frequency resources are assigned to different users to avoid intra-cell interference. However, inter-cell interference (ICI) caused by the users in neighboring cells significantly deteriorates the performance. Cooperation among base stations must be used to deal with ICI for multi-cell systems. In this paper, we investigate multi-cell scheduling in SC-FDMA for LTE uplink. We propose a novel cooperative scheduling algorithm that takes inter-cluster and intra-cluster interference into account. We first perform coordinated scheduling and then link adaptation to select modulation and coding scheme (MCS). Simulation results show that the proposed algorithm has significant gains over the single-cell proportional fair (PF) scheduling algorithm on both cell-edge and average throughput. It also outperforms the existing cooperative algorithm under full path loss compensation and fractional open-loop power control (OLPC).