Ultra-high Reliability Research Articles

URLLC-Based Cooperative Industrial IoT Networks With Nonlinear Energy Harvesting

The efficient and effective framework for next-generation (5G and beyond 5G) wireless networks should include mission-critical aspects such as ultralow latency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\leq \!\!1$</tex-math></inline-formula> ms), ultrahigh reliability (99.999%), and enhanced data rate. Billions of ubiquitously connected devices are expected to serve various industrial applications in upcoming industry standards such as Industry 5.0. These industrial applications include mission-critical tasks such as smart grids, remote surgery, and intelligent transportation systems. This article considers an industrial Internet of Things (IIoT) environment in mission-critical ultrareliable low latency communication (URLLC) application where the main industrial unit or industrial control node (CN) sends messages to the target device (TD) with the aid of a cooperative device (CD). We investigate a novel transmission protocol and analyze the network’s performance. Considering the nonlinear energy harvesting (EH) mechanism at power-constrained nodes and direct and cooperative phase transmissions, the outage probability (OP) and block error rate (BLER) performances are evaluated for Rayleigh distributed fading channels. The analytical results are validated through Monte–Carlo simulations.

SparkLink: A short-range wireless communication protocol with ultra-low latency and ultra-high reliability

SparkLink: A short-range wireless communication protocol with ultra-low latency and ultra-high reliability

Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks

Vehicular ad hoc networks (VANETs) are self-organizing, open-structure inter-vehicle communication networks, along with wireless communication technology and transportation. Vehicle communication aims to improve the driver’s response-ability and ensure traffic safety when encountering traffic accidents. The 5G NR on V2V communication, compared to fourth-generation (4G) long-term evolution (LTE), is more sophisticated and has ultra-high reliability. This research proposes intelligent driver model-lane changes (IDM-LC) and intelligent driver model-avoidance (IDM-A) models, which enhance the performance accuracy of the V2V communication through the 5G NR system. In this case, the authenticity of the vehicle movement models is tested on different road scenarios, i.e., square, hexagon, heptagon and triangle. In these scenarios, the vehicles’ movements over the 5G networks receive widespread coverage whenever the vehicles receive signals from the roadside unit (RSU). Hence, the flexibility of VANET is used to improve the device-to-device (D2D) or vehicle-to-vehicle (V2V) communication efficiency in the fifth-generation (5G) new radio (NR) system. In addition, the VANET simulation platform, i.e., simulation of urban mobility (SUMO) and network simulator-3 (NS-3), simulate and evaluate the comparison of V2V through the 5G networks, which receives widespread coverage in 15 to 20 m/s. The simulation results and analysis show that the V2V communication through the 5G system performs better on the IDM models.

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, we propose a seamless migration technique for complex edge computing structures. The developed migration scheme enables services to adapt to the required load on the radio channels. The proposed algorithm is analyzed for various use cases, and a test bench has been developed to emulate the operator’s infrastructure. The obtained results are introduced and discussed.

Real-Time Transmission Optimization for Edge Computing in Industrial Cyber-Physical Systems

With the rapid development of Industry 4.0, the industrial cyber-physical systems (ICPS) are expected to realize the digital sensing, automatic control, and refined management in smart factories. However, limited bandwidth resources and severe industrial interference make it difficult to meet the real-time and ultrahigh reliability in edge computing (EC)-based next-generation industrial automation networks. To tackle these challenges, in this article, we propose a real-time transmission optimization scheme to accelerate EC. First, we establish a hierarchical system model for smart manufacturing and automation scenarios. Then we present a power control optimization method based on noncooperative game to alleviate interference and reduce energy consumption. Finally, we propose a path optimization scheme based on Q-learning for low-latency and ultrahigh reliability transmission requirements. Extensive simulation results reveal that our proposals perform better in terms of transmission delay and packet-loss rate compared with traditional methods, and therefore, contributes to EC deployment in ICPS.

Game Theoretic Approach for Multipriority Data Transmission in 5G Vehicular Networks

The vehicle-to-vehicle (V2V) communication driven by the fifth generation (5G) cellular mobile network with the features of ultra-high reliability and low latency provides promising solutions to various applications in the intelligent transportation system (ITS). To improve the resource utilization and guarantee the quality-of-service (QoS), users in 5G vehicular networks have to select appropriate communication modes and control their own transmission power. However, the highly dynamic network topology and channel status pose challenges to the mode selection. In this paper, we propose a scheme for joint mode selection and power adaptation based on the game theoretic approach with the objective of maximizing the overall system throughput. We consider the transmission requirements of multi-priority packets of different vehicular applications, where packets with higher priority have more stringent latency constraints. The segmented auction method with reserve price is performed to select modes for the vehicular users (VUEs) and the Stackelberg gaming model is introduced to solve the problem of cochannel interference. We compare our approach with three existing methods in extensive simulations. The results show that our approach outperforms the existing methods in terms of network performance, including the network throughput, resource utilization and QoS violation rate.

Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems

Ultra-reliable low-latency communication (uRLLC) is a group of fifth-generation and sixth-generation (5G/6G) cellular applications with special requirements regarding latency, reliability, and availability. Most of the announced 5G/6G applications are uRLLC that require an end-to-end latency of milliseconds and ultra-high reliability of communicated data. Such systems face many challenges since traditional networks cannot meet such requirements. Thus, novel network structures and technologies have been introduced to enable such systems. Since uRLLC is a promising paradigm that covers many applications, this work considers reviewing the current state of the art of the uRLLC. This includes the main applications, specifications, and main requirements of ultra-reliable low-latency (uRLL) applications. The design challenges of uRLLC systems are discussed, and promising solutions are introduced. The virtual and augmented realities (VR/AR) are considered the main use case of uRLLC, and the current proposals for VR and AR are discussed. Moreover, unmanned aerial vehicles (UAVs) are introduced as enablers of uRLLC. The current research directions and the existing proposals are discussed.

Achieving Covertness and Security in Broadcast Channels With Finite Blocklength

Considering multi-user downlink ultra-high reliability and low latency communications (URLLC), this paper employs the artificial noise (AN) technique to establish a secure and covert broadcast communication paradigm for the first time. Specifically, a multi-antenna transmitter (Alice) broadcasts the confidential information to multiple legitimate users in the presence of a multi-antenna malicious warden (Willie) and a multi-antenna eavesdropper (Eve). It is well known that AN is an effective technique for securing the physical layer security (PLS) of signal transmissions. Nevertheless, AN emission also exposes the signal transmission and decreases the signal covertness. Taking into account the impact of short-packet URLLC transmissions, we investigate the joint optimization of the precoder and AN to maximize the secrecy rate under the covertness constraint. Although the considered problem is nonconvex, we propose a branch-reduce-and-bound (BRB)-based algorithm to solve it optimally. However, the nested-loop structure of the BRB-based algorithm incurs a high computational complexity. To strike a balance between the performance and computational complexity, we also propose a low-complexity penalty successive convex approximation (SCA)-based algorithm, whose performance approaches that of the optimal BRB-based algorithm, particularly in the low to medium transmit power regime. Simulation results demonstrate the excellent performance of our proposed optimization algorithms compared with various benchmark algorithms and unveil the importance of exploiting AN for secrecy provisioning.

Guest Editorial: Artificial Intelligence Enabled Internet of UAVs for Emergency Communications

The unprecedented demands for high-quality and ubiquitous wireless services impose enormous challenges to the existing cellular networks to meet the challenges of connectivity, reliability, etc. The targeted applications in designing the beyond fifth generation (BSG) systems include enhanced mobile broadband (eMBB), ultra-reliable, low latency communications (URLLC), and massive machine-type communications (mMTC). Recently to meet those diverse requirements, the latest technologies like millimeter wave (mmWave) communications, ultra-dense networks (UDN), and massive multiple-input and multiple-output (MIMO) are under consideration. Moreover, we also require an evolution in an architectural platform that performs joint communications, sensing, localization, and computing while ensuring ultra-high throughput, ultra-low latency, and ultra-high reliability for real-time emergency communications.

An Overall Research on Industry Ecological and Technical Solutions for 5G-V2X in Port Park Scenario

Aiming at improving the user’s driving safety and travel efficiency and satisfying their future needs of highly autonomous driving services and based on the features of 5G’s ultralow latency, ultrahigh reliability, and ultrawide broadband, this paper proposes an overall solution for 5G-V2X, including industry ecological solutions and technical solutions. The industry ecological solutions include the analysis of the Internet of Vehicles industry chain architecture, future business models, and innovative ecosystems. The technical solutions include the overall solution for V2X, the overall blueprint of the planning function for V2X, core technology scenarios, and key technical capabilities. These solutions can integrate users, vehicles, and roads completely and effectively, which helps the government to achieve effective monitoring and management of intersection of user-vehicle-road and realizes the 5G-based V2X pan-transportation and logistics ecology. The validity and feasibility of these solutions are verified by some applications in the port park.

Vehicular Wireless Communication Standards

Autonomous vehicles (AVs) are the future of mobility. Safe and reliable AVs are required for widespread adoption by a community which is only possible if these AVs can communicate with each other &amp;amp; with other entities in a highly efficient way. AVs require ultra-reliable communications for safety-critical applications to ensure safe driving. Existing vehicular communication standards, i.e., IEEE 802.11p (DSRC), ITS-G5, &amp;amp; LTE, etc., do not meet the requirements of high throughput, ultra-high reliability, and ultra-low latency along with other issues. To address these challenges, IEEE 802.11bd &amp;amp; 5G NR-V2X standards provide more efficient and reliable communication, however, these standards are in the developing stage. Existing literature generally discusses the features of these standards only and does not discuss the drawbacks. Similarly, existing literature does not discuss the comparison between these standards or discusses a comparison between any two standards only. However, this work comprehensively describes different issues/challenges faced by these standards. This work also comprehensively provides a comparison among these standards along with their salient features. The work also describes spectrum management issues comprehensively, i.e., interoperability issues, co-existence with Wi-Fi, etc. The work also describes different other issues comprehensively along with recommendations. The work describes that 802.11bd and 5G NR are the two potential future standards for efficient vehicle communications; however, these standards must be able to provide backward compatibility, interoperability, and co-existence with current and previous standards.

Toward a Fog-Based Traffic Flow Framework for Tactile Internet

Empowered by sufficient robotics and haptic hardware at the edges of a communication network system, tactile Internet (TI) is the upcoming transformation that will empower the control of Internet of Things in real time and facilitate a true paradigm shift in making a dream into a reality. However, one of the most crucial challenges in realizing TI is to achieve round-trip time (RTT) of 1 ms or less. This RTT includes transmission, queuing, processing (operator’s end), and acknowledgement times (controlled end). Another challenge is to achieve ultrahigh reliability for establishing haptic communications for TI. This article proposes a novel fog-based traffic flow framework employing software-defined networking (SDN) and fog computing (FC) to address these challenges. An efficient traffic flow algorithm is developed to effectively manage complex and critical traffic in the network to reduce extra processing and waiting times at each level of clouds. The SDN and FC approaches provide an effective solution to route the traffic efficiently in the system. Hence, the traffic flow paths from the master to slave sections are reduced, and consequently, RTT is also reduced. The performance of the proposed system is evaluated by an iFogSim simulator in terms of throughput, RTT, energy consumption, and reliability. The simulation results obtained show that the proposed system outperforms the existing edge, cloud, and cellular networks.

Clock Synchronization for Wireless Time-Sensitive Networking: A March From Microsecond to Nanosecond

Industrial control systems in the era of Industry 4.0 present significant challenges from a communication perspective, that is, low latency, ultrahigh reliability, and accurate synchronization. Time-sensitive networking (TSN) has emerged as the main solver of these challenges. As a research trend, TSN and wireless technologies are expected to converge in the wireless TSN paradigm. This convergence starts with the adoption of accurate clock synchronization over wireless systems. In this article, we review the existing wireless clock-synchronization approaches and their attainable performances, and we discuss their feasibility to enable wireless TSN. We conclude that the existing clock-synchronization techniques are enough to enable wireless TSN, although significant implementation efforts are required to incorporate accurate clock synchronization over wireless systems.

Empowering the Internet of Things Using Light Communication and Distributed Edge Computing

With the rapid growth of connected devices, new issues emerge, which will be addressed by boosting capacity, improving energy efficiency, spectrum usage, and cost, besides offering improved scalability to handle the growing number of linked devices. This can be achieved by introducing new technologies to the traditional Internet of Things (IoT) networks. Visible light communication (VLC) is a promising technology that enables bidirectional transmission over the visible light spectrum achieving many benefits, including ultra-high data rate, ultra-low latency, high spectral efficiency, and ultra-high reliability. Light Fidelity (LiFi) is a form of VLC that represents an efficient solution for many IoT applications and use cases, including indoor and outdoor applications. Distributed edge computing is another technology that can assist communications in IoT networks and enable the dense deployment of IoT devices. To this end, this work considers designing a general framework for IoT networks using LiFi and a distributed edge computing scheme. It aims to enable dense deployment, increase reliability and availability, and reduce the communication latency of IoT networks. To meet the demands, the proposed architecture makes use of MEC and fog computing. For dense deployment situations, a proof-of-concept of the created model is presented. The LiFi-integrated fog-MEC model is tested in a variety of conditions, and the findings show that the model is efficient.

SDN-Assisted Safety Message Dissemination Framework for Vehicular Critical Energy Infrastructure

The proliferation of fifth-generation (5G) networks toward vehicle-to-everything (V2X) communication has paved the way for driverless autonomous vehicles (AVs) in vehicular critical energy infrastructures (CEI). Though technological advancements improve AVs, the safety-critical messages (SCMs) still play a vital role in reducing crashes, preventing injuries, and saving lives. AVs’ high speed and complex network topology challenge disseminating SCMs with a highly successful delivery ratio and extremely low latency. Furthermore, the typical SCM dissemination schemes cause channel congestion and minimize the delivery ratio, making the systems incompatible with the AVs. Therefore, in this article, a software-defined-networking-assisted continuous clustering approach called migrating consignment region (MiCR) based on the federated <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> -means algorithm is proposed for disseminating SCMs to the AVs via 5G V2X communication. Unlike other methods that create clusters for every instance of SCM dissemination, MiCR continuously holds moving clusters for disseminating SCMs to AVs with ultrahigh reliability and low latency. The proposed MiCR approach has been simulated under real-time highway road maps and compared with other methods. The simulation results prove the superiority of MiCR in terms of network overload, SCM delivery ratio, latency, dissemination efficiency, and collision rate compared with the existing methods.

Guest Editorial Special Issue on Next Generation Multiple Access—Part II

As the long-term evolution (LTE) system is reaching maturity and the fifth-generation (5G) systems are being commercially deployed, researchers have turned their attention to the development of next-generation wireless networks. Compared to current wireless networks, on the one hand, next-generation wireless networks are expected to achieve significantly higher capacity, extremely low latency, ultra-high reliability, as well as massive and ubiquitous connectivity for supporting diverse disruptive applications (e.g., virtual reality (VR), augmented reality (AR), and industry 4.0). On the other hand, the evolution toward next-generation wireless networks requires a paradigm shift from the communication-oriented design to a multi-functional design, including communication, sensing, imaging, computing, and localization. Looking back at the history of wireless communication systems, multiple access (MA) techniques have been key enablers. From the first generation (1G) to the fifth generation (5G), orthogonal multiple access (OMA) schemes are mainly employed, where multiple users are allotted in orthogonal frequency/time/code resources, and the uplink transmission of the code code-division multiple-access (CDMA) uses non-orthogonal code resources. However, given the enormous challenges and diverse services of next-generation wireless networks, which significantly differ from that in current and previous wireless networks, existing MA schemes may not be applicable. As a result, a fundamental issue is the design of next-generation multiple access (NGMA) techniques. The key concept of NGMA is to enable a very large number of users/devices to be efficiently, flexibly, and intelligently connected with the network over the given wireless radio resources to not only satisfy stringent communication requirements but also realize heterogeneous functions. The investigation of NGMA is still in the infancy stage, and extensive research efforts have to be devoted to areas, including but not limited to 1) the development of new MA schemes, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), which are capable of achieving higher bandwidth efficiency and higher connectivity compared with conventional MA schemes; 2) the development of innovative techniques, such as reconfigurable metasurfaces, random access, advanced modulation, and channel coding, which are beneficial to the overall design of NGMA; and 3) the exploitation of advanced machine learning (ML) tools and big data techniques for providing effective solutions to address newly emerging NGMA problems.

Application Layer-Forward Error Correction Raptor Q Codes in 5G Mobile Networks for Factory of the Future

The future communication requirements for industrial automation will differ significantly from existing technologies. Traffic in Industry 4.0 imposes real-time requirements, requiring ultra-reliable communication (URC) with high reliability and minimal latency. The demand for ultra-high reliability as high as 99.999999 percent and as low as 1 ms end-to-end latency is the major challenge of the NOMA communication system in the factory of the future. The high expectations on reliability and latency need modifications to the radio system’s baseband signal processing, medium access control (MAC) layer, and application layer to protect against packet losses. Thus, this paper investigates the utilization of Raptor Q codes, which is a type of Application Layer Forward Error Correction (AL-FEC), by developing an end-to-end system level simulator to evaluate and analyze the performance of the transmission signals based on cross-layer approach; from the physical layer (PHY), MAC layer, and application layer parameters in an indoor factory network setting. The factory is assumed to be operated with various factory robots of different speeds, from static to 10 km/h. The 5G technology relies heavily on flexible network operations. High user density, high user mobility, deployment, and coverage are all qualities that allow for this flexibility. Through extensive simulations, the results showed that the Raptor Q codes are not only able to give good results, i.e., packet reception rate PRR = 0.9 of 10 m or 1.8% to 10 m or 3.4% depending on different scenarios, but are also able to meet PRR = 0.9 in the mobility scenario at 10 km/h. Thus, the Raptor Q codes can be seen as a good candidate for obtaining results within a strict range of requirements set by URC communications for the factory of the future replacing RLNC.

Resource Allocation in Time Slotted Channel Hopping (TSCH) Networks Based on Phasic Policy Gradient Reinforcement Learning

The concept of the Industrial Internet of Things (IIoT) is gaining prominence due to its low-cost solutions and improved productivity of manufacturing processes. To address the ultra-high reliability and ultra-low power communication requirements of IIoT networks, Time Slotted Channel Hopping (TSCH) behavioral mode has been introduced in IEEE 802.15.4e standard. Scheduling the packet transmissions in IIoT networks is a difficult task owing to the limited resources and dynamic topology. In IEEE 802.15.4e TSCH, the design of the schedule is open to implementation. In this paper, we propose a phasic policy gradient (PPG) based TSCH schedule learning algorithm. We construct the utility function that accounts for the throughput, and energy efficiency of the TSCH network. The proposed PPG based scheduling algorithm overcomes the drawbacks of totally distributed and totally centralized deep reinforcement learning-based scheduling algorithms by employing the actor–critic policy gradient method that learns the scheduling algorithm in two phases, namely policy phase and auxiliary phase. In this method, we show that the schedule converges quickly compared to any other actor–critic method and also improves the system throughput performance by 58% compared to the minimal scheduling function, a default TSCH schedule.

Special Issue on Next Generation Multiple Access—Part I

As the long-term evolution (LTE) system is reaching maturity and the fifth-generation (5G) systems are being commercially deployed, researchers have turned their attention to the development of next-generation wireless networks. Compared to current wireless networks, on the one hand, next-generation wireless networks are expected to achieve significantly higher capacity, extremely low latency, ultra-high reliability, as well as massive and ubiquitous connectivity for supporting diverse disruptive applications (e.g., virtual reality (VR), augmented reality (AR), and industry 4.0). On the other hand, the evolution toward next-generation wireless networks requires a paradigm shift from the communication-oriented design to a multi-functional design, including communication, sensing, imaging, computing, and localization. Looking back at the history of wireless communication systems, multiple access (MA) techniques have been key enablers. From the first generation (1G) to the fifth generation (5G), orthogonal multiple access (OMA) schemes are mainly employed, where multiple users are allotted in orthogonal frequency/time/code resources, and the uplink transmission of the code code-division multiple-access (CDMA) uses non-orthogonal code resources. However, given the enormous challenges and diverse services of next-generation wireless networks, which significantly differ from that in current and previous wireless networks, existing MA schemes may not be applicable. As a result, a fundamental issue is the design of next-generation multiple access (NGMA) techniques. The key concept of NGMA is to enable a very large number of users/devices to be efficiently, flexibly, and intelligently connected with the network over the given wireless radio resources to not only satisfy stringent communication requirements but also realize heterogeneous functions. The investigation of NGMA is still in the infancy stage, and extensive research efforts have to be devoted to areas, including but not limited to 1) the development of new MA schemes, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), which are capable of achieving higher bandwidth efficiency and higher connectivity compared with conventional MA schemes; 2) the development of innovative techniques, such as reconfigurable metasurfaces, random access, advanced modulation, and channel coding, which are beneficial to the overall design of NGMA; and 3) the exploitation of advanced machine learning (ML) tools and big data techniques for providing effective solutions to address newly emerging NGMA problems.

Series Editorial: Ultra-Low-Latency and Reliable Communications for Future Wireless Networks

Ultra-low-latency and reliable communications is perhaps the most challenging task in future wireless networks because of its demanding requirements of low latency combined with ultra-high reliability. The number of connected devices and data traffic is increasing exponentially every day, and future data-intensive applications like augmented/virtual reality (AR/VR), holographic communications, vehicle-to-everything (V2X), autonomous driving, high precision manufacturing, and ultra-massive machine-type communications wil demand high throughput, ultra-reliable transmission, extremely low latency, and high energy efficiency. This Series issue introduces four high-quality articles presenting discussions on new techniques and concepts, standards, future applications, network architectures, challenges, and promising solutions for ultra-high-speed, low-latency, and reliable communications in future networks. In the following, we introduce these articles and highlight their main contributions.