Ultra-low Latency Communication Research Articles

Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network

Non-terrestrial network (NTN) is a trending topic in the field of communication, as it shows promise for scenarios in which terrestrial infrastructure is unavailable. Unmanned autonomous intelligent systems (UAISs), as a physical form of artificial intelligence (AI), have gained significant attention from academia and industry. These systems have various applications in autonomous driving, logistics, area surveillance, and medical services. With the rapid evolution of information and communication technology (ICT), 5G and beyond-5G communication have enabled numerous intelligent applications through the comprehensive utilization of advanced NTN communication technology and artificial intelligence. To meet the demands of complex tasks in remote or communication-challenged areas, there is an urgent need for reliable, ultra-low latency communication networks to enable unmanned autonomous intelligent systems for applications such as localization, navigation, perception, decision-making, and motion planning. However, in remote areas, reliable communication coverage is not available, which poses a significant challenge for intelligent systems applications. The rapid development of non-terrestrial networks (NTNs) communication has shed new light on intelligent applications that require ubiquitous network connections in space, air, ground, and sea. However, challenges arise when using NTN technology in unmanned autonomous intelligent systems. Our research examines the advancements and obstacles in academic research and industry applications of NTN technology concerning UAIS, which is supported by unmanned aerial vehicles (UAV) and other low-altitude platforms. Nevertheless, edge computing and cloud computing are crucial for unmanned autonomous intelligent systems, which also necessitate distributed computation architectures for computationally intensive tasks and massive data offloading. This paper presents a comprehensive analysis of the opportunities and challenges of unmanned autonomous intelligent systems in UAV NTN, along with NTN-based unmanned autonomous intelligent systems and their applications. A field trial case study is presented to demonstrate the application of NTN in UAIS.

On Construction of Low-Density Parity-Check Codes for Ultra Reliable and Low Latency Communications

On Construction of Low-Density Parity-Check Codes for Ultra Reliable and Low Latency Communications

Ultra-low latency communication technique for augmented reality application in mobile edge computing

Ultra-low latency communication technique for augmented reality application in mobile edge computing

Tele-proctoring for minimally invasive surgery across Japan: Aninitial step toward a new approach to improving the disparity of surgical care and supporting surgical education.

The aim of this study was to verify the clinical feasibility of tele-proctoring using our ultra-low latency communication system with shared internet access. Connections between two multiple remote locations at various distances were established through the TELEPRO® tele-proctoring system. The server records the latency between the two locations for tele-proctoring using the annotations. Questionnaires were administered to the surgeons, assistants, and medical staff. Respondents rated the quickness and quality of communication in terms of latency and disturbances in the audio, video, and usefulness of the live telestrations with annotation. Seven hospitals tele-proctored with Sapporo Medical University between January 2021 and September 2022. The median latency of annotation between the two locations ranged from 24.5 to 48.5 ms. No major technological problems occurred, such as streaming interruption, loss of video or audio, poor resolution. The video encoding time was 10 ms, and its decoding time was 0.8 ms. The total latency positively correlated with the distance between two locations (R = 0.55, p < 0.01). The quality of communication regarding latency, disturbance, and surgical education with intraoperative annotative instructions showed similar trends, with perfectly fine being the most common response. No significant differences in surgical quality, educational effect, or social impact were observed between the latency ≥30 and <30 ms groups for whether the size of latency affects surgical education. The feasibility of the tele-proctoring system is expected to be a sustainable approach to help education for young surgeons and surgical supports in rural areas, thereby reducing disparities in health care.

Service Function Chaining to Support Ultra-Low Latency Communication in NFV

Network function virtualization (NFV) has the potential to fundamentally transform conventional network architecture through the decoupling of software from dedicated hardware. The convergence of virtualization and cloud computing technologies has revolutionized the networking landscape, offering a wide range of advantages, including improved flexibility, manageability, and scalability. The importance of network capability in enabling ultra-low latency applications has been greatly amplified in the current era due to the increased demand for emerging services such as autonomous driving, teleoperated driving, virtual reality, and remote surgery. This paper presents a novel and efficient methodology for service function chaining (SFC) in an NFV-enabled network that aims to minimize latency and optimize the utilization of physical network resources, with a specific focus on ultra-low latency applications. In our proposed methodology, we offer flow prioritization and an adjustable priority coefficient factor (µ) to reserve a portion of physical network resources exclusively for ultra-low latency applications in order to optimize the deployment paths of these applications further. We formulate the SFC deployment problem as an integer linear programming (ILP) optimization model. Furthermore, we propose a set of heuristic algorithms that yield near-optimal solutions with minimal optimality gaps and execution times, making them practical for large-scale network topologies. Performance evaluations demonstrate the effectiveness of our proposed methodology in enabling ultra-low latency applications in an NFV-enabled network. Compared to existing algorithms, our proposed methodology achieves notable enhancements in terms of the end-to-end delay (up to 22 percent), bandwidth utilization (up to 28 percent), and SFC acceptance rate (up to 13 percent).

Ultra-low latency communication technology for Augmented Reality application in mobile periphery computing

Abstract Improved Reliability and Low Latency Communication (IRLC) with Augmented Reality (AR) has become an emerging technology in today’s world. To minimize an accessory adaptation for Customer Equipment (CE) in AR, it may be feasible to offload the AR workload onto the onboard devices. Mobile-Edge Computation (MEC) will improve the throughput of a CE. MEC has caused enormous overhead or communication omissions on wireless media, making it difficult to choose the optimal payload proposition. The proposed system explores on-board devices that work together to achieve an AR goal. Code splitting is a Bayesian network used to examine the overall interdependence of efforts. From a longevity and endurance perspective, it is used to reduce the Probability of Supplier Failure (PSF) of an MEC-enabled AR environment. Weighed Particle Swarm Optimization (WPSO) was proposed despite the reality based on the emphasis on balancing the issue. As a result, a heuristic-based WPSO facilitates to improve the performance measures. A hybrid method could significantly increase the assertion of a predicted PSF in various network scenarios compared to the existing communication technologies. A preliminary iterative approach is suitable for AR operations and IRLC scenarios to generalize the attributes.

Study of Uplink Resource Allocation for 5G IoT Services by Using Reinforcement Learning

&lt;p&gt;In order to support real time IoT services, the ultra Reliable and Low Latency Communications (uRLLC) was proposed in 5G wireless communication network. Different from the grant based access in 4G, the grant free technique is proposed in 5G to reduce the random access delay of uRLLC-required applications. This paper proposes the dedicated resource for exclusive access of individual UE and the shared resource pool for the contention of multiple UEs by adopting the reinforcement learning approach. The objective of this paper is to accomplish the uplink successful rate above 99.9% under certain transmission error probability. The proposed Prediction based Hybrid Resource Allocation (PHRA) scheme allocates the access resource in a heuristic manner by referring to the activity of UEs. The dedicated resource is mainly allocated to the high activity UEs and the initial transmission of UEs with medium activity while the shared resource pool is allocated for the re-transmission of medium activity UEs and low activity UEs by using the reinforcement learning model. The burst traffic model was applied during the exhaustive experiments. And the simulation results show that the proposed scheme achieves higher uplink packet delivery ratio and more effective resource utilization than the other schemes.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Cloud-Edge Architecture With Virtualized Hardware Functionality for Real-Time Diagnosis of Transients in Smart Grids

Edge Cloud is providing unprecedented opportunities for IoT and WAMS (Wide Area Monitoring Systems) in electrical grid operation. It is an orchestrated environment able to address low latency events through appropriate edge-cloud computing configurations.Transient State Estimation (TSE) is a key monitoring tool for capturing a reliable knowledge of the Smart Grid status in real-time, given the impediments introduced by the increasing penetration of Distributed Energy Resources in the energy mix. Frequency response anomalies, large scale transients, and voltage swings can be captured by TSE for real time or post failure data analytics. This work presents a cloud edge framework for the efficient calculation of TSE which, albeit its benefits, demands high computational resources at the edge (close to the measurement units) along with ultra low latency communications. The framework enables TSE as a service through the coordination of Virtual Machines (VMs) running on virtualized infrastructure and other non-virtualized physical nodes. In order to support the stringent time requirements, part of the TSE is offloaded to dedicated hardware acceleration units (FPGA). The proposed TSE framework is validated using an IEEE 30-bus, and the results show a significant superiority in terms of total latency compared to conventional cloud and edge deployments.

An Intelligent Deterministic Scheduling Method for Ultralow Latency Communication in Edge Enabled Industrial Internet of Things

Edge enabled Industrial Internet of Things (IIoT) platform is of great significance to accelerate the development of smart industry. However, with the dramatic increase in real-time IIoT applications, it is a great challenge to support fast response time, low latency, and efficient bandwidth utilization. To address this issue, time sensitive network (TSN) is recently researched to realize low latency communication via deterministic scheduling. To the best of our knowledge, the combinability of multiple flows, which can significantly affect the scheduling performance, has never been systematically analyzed before. In this article, we first analyze the combinability problem. Then, a noncollision theory based deterministic scheduling (NDS) method is proposed to achieve ultralow latency communication for the time-sensitive flows. Moreover, to improve bandwidth utilization, a dynamic queue scheduling (DQS) method is presented for the best-effort flows. Experiment results demonstrate that NDS/DQS can well support deterministic ultralow latency services and guarantee efficient bandwidth utilization.

Development of an ultralow-latency communication system using shared internet access: promoting the implementation of telemedicine.

Telemedicine is becoming increasingly important to address the shortage of gastrointestinal surgeons and disparities in domestic and international treatment outcomes for patients with colorectal cancer. The development of a low-latency communication system using existing communication infrastructure (shared internet access: SIA) is necessary to promote the use of telemedicine. The aim of this study was to develop a low-latency communication system using SIA. We conducted an experiment between Sapporo and Tokyo using an ultralow-latency communication system for remote medical education (TELEPRO®). The latency was measured using 2000 annotations from a monitor in Sapporo, which confirmed a median latency of 27.5ms. A low-latency communication system based on SIA with latency lower than the maximum allowable latency for telemedicine was developed successfully.

Towards Fully Secure 5G Ultra-Low Latency Communications: A燙ost-Security Functions Analysis

Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those new security components into different groups according to their purpose and deployment scope. We propose to analyze them in the context of existing 5G architectures using two different approaches. First, using model checking techniques, we will evaluate the probability of an attacker to be successful against each security solution. Second, using analytical models, we will analyze the impact of these security mechanisms in terms of delay, throughput consumption, and reliability. Finally, we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture. Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced, dedicated non-native mechanisms could only guarantee secure URLLC with a probability of ∼55%.

Dynamic Manager Selection Assisted Resource Allocation in URLLC With Finite Block Length for 5G-V2X Platoons

In this paper, we investigate a fifth generation cellular vehicle-to-everything based platoon system and propose low-complexity dynamic manager selection and resource allocation algorithms in the finite block length regime, to meet the ultra reliable and low latency communication requirements of intra-platoon safety-related data transmission. A closed-form expression for the platoon manager index is derived, based on which a low-complexity dynamic platoon manager selection algorithm is proposed, enabling a significant communication performance enhancement over the conventional head vehicle platoon manager algorithm. This is also the first work to investigate the impact of finite block length on platoon communication. The optimal finite block length coding rate under automatic repeat request retransmission is obtained. A subchannel multiplexing criterion is proposed and closed-form expressions for the optimal transmission powers of the platoon manager and its subchannel multiplexing partner are derived. Based on the theoretical findings, a joint resource allocation and coding rate optimization algorithm is proposed, achieving a near-optimal performance in terms of groupcast latency with a significant complexity reduction over exhaustive search.

Visible Light and Reconfigurable Intelligent Surfaces for Beyond 5G V2X Communication Networks at Road Intersections

Traffic safety at road intersections can be enhanced by improving opportunistic exchange of safety messages between vehicles. In urban intersection scenario, obstacles such as buildings and road side installations/signboards block the line-of-sight communication between vehicles. In order to enhance the reliability of communication link, the existing vehicular solution utilizes relay placement at road intersection. However, as the vehicular density increases, the existing vehicular-radio frequency (V-RF) communication with relaying tends to suffer from higher interference, lower packet reception rate, and longer communication delays due to channel congestion. In contrast to the existing solutions, we propose to use practical deployment strategies namely hybrid vehicular-visible light communication (V-VLC)/V-RF with relaying and reconfigurable intelligent surface (RIS) aided V-RF solutions to improve the communication range for urban vehicle-to-vehicle (V2V) communication. We present stochastic geometry based analytical framework to analyze the performance of proposed solutions in terms of outage probability, throughput and delay outage rate (DOR). Numerical results illustrate that the proposed solutions can achieve considerable performance improvement in outage, throughput while ensuring low latency as compared to conventional V-RF with relaying. These deployment strategies may also serve as a preferred alternative for Intelligent Transportation System (ITS) to meet ultra-high reliable and ultra-low latency communication for beyond 5 G (B5G) vehicular networks.

State-of-the-Art Strategies and Research Challenges in Wireless Communication for Building Smart Systems

The upcoming 6G communication network will revolutionize the scenario of customer services and related applications by building smart, autonomous systems. We first discuss here about 6G enabled smart applications like healthcare, smart city building, industrial IoTs, etc. We next provide a brief survey of the enabling technologies for achieving the required goals of 6G, such as terahertz communication, cell-free communication, holographic communication using beamforming, wireless power transfer, ultra-low latency communication, etc., with a view to tackle very large amounts of data traffic from several billions of smart interconnected devices while supporting ultra-low end-to-end communication latency. Finally, we present various research challenges involved in 6G communication towards building such smart systems.

AI-driven, Context-Aware Profiling for 5G and Beyond Networks

In the era of Industrial Internet of Things (IIoT) and Industry 4.0, an immense volume of heterogeneous network devices will coexist and contend for shared network resources, in order to satisfy the very challenging IIoT applications, requiring ultra-reliable and ultra-low latency communications. Although novel key enablers, such as Network Slicing, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have already offered significant advantages towards more efficient and flexible network and resource management approaches, the particular characteristics of IIoT applications pose additional burdens, mainly due to the complex wireless environments, high number of heterogeneous network devices, sensors, user equipments (UEs), etc., which may stochastically demand and contend for the - often scarce - computing and communication resources of industrial environments. To this end, this paper introduces PRIMATE, a novel, Artificial Intelligence (AI)-driven framework for the profiling of the networking behavior of such UEs, devices, users and things, which is able to operate in conjunction with already standardized or forthcoming, AI-based network resource management processes towards further gains. The novelty and potential of the proposed work lies on the fact that instead of attempting to either predict raw network metrics in a reactive manner, or predict the behavior of specific network entities/devices in an isolated manner, a big data-driven classification approach is introduced, which models the behavior of any network device/user from both a macroscopic, as well as service-specific perspective. The extended evaluation at the last part of this work shows the validity and viability of the proposed framework.

Ultra-low latency communication technique for augmented reality application in mobile edge computing

Ultra-low latency communication technique for augmented reality application in mobile edge computing

Design of Edge Computing for 5G-Enabled Tactile Internet-Based Industrial Applications

5G-enabled Tactile Internet (TI) will rely on sensors, actuators, and ultra-reliable and ultralow latency communication for providing haptic human-machine interaction services. However, stringent requirements in terms of high reliability and sub-millisecond latency pose many daunting challenges that have limited the development of Tl services. In this article, we shed light on the design of edge computing for Tl industrial applications. We discuss major industrial use cases that will be transformed with the development of TI. We thoroughly present the benefits and challenges of the processing of Tl computation-in-tensive tasks in edge computing servers. Moreover, we highlight the current designs of edge resource allocation algorithms for tasks offloading and haptic and non-haptic feedback delivery in Tl industrial applications. Furthermore, we thoroughly discuss the current missing building blocks in edge computing to unleash TI industrial applications. Finally, open challenges that emerge when designing edge computing for supporting Tl industrial applications are discussed.

Internet of Things and Next Generation Wireless Communication Systems

Next generation wireless communication systems will connect billions of Internet of Thing (IoT) devices and user elements along with billions of people, enable machine-to-ma-chine communications across heterogeneous and dynamic environment, and provide low-latency computing and storage resources on demand at the deep edge as well as in the cloud. Tremendous research and development efforts have already been emphasized on the enabling technologies toward next generation wireless systems to support a variety of critical and personalized services in multiple application domains, including industry use cases, environment, transportation, education, public health and safety, and defense. Wireless communication networks have been greatly advanced by exploiting technologies such as millimeter wave, dynamic spectrum sharing, massive MIMO, beam forming, network slicing and virtualization, and artificial intelligence and machine learning. These technology breakthroughs can empower wireless networks to support extreme high capacity, massive connectivity, and ultra-low latency communications for new use cases identified for next generation wireless systems. In order to design and deploy wireless communication systems with IoT devices across heterogeneous and dynamic environments to provide next generation wireless services, however, there are many critical technical challenges yet to be addressed. In this issue of IEEE Wireless Communications, we are pleased to present two feature topics to bring together researchers, industry practitioners, and individuals working on the related areas to address some of these technical challenges for IoT and next generation wireless systems. One feature topic on “Massive Machine-Type Communications for IoT” includes four articles, and was organized by guest editors W. Ji, T. Ebrahimi, Z. Li, J. Yuan, D. O. Wu, and Y. Xin; the other feature topic on “Emerging Visual IoT Technologies for Future Communications and Networks” includes six articles, and was organized by guest editors L. Liu, E. G. Larsson, P. Popovski, G. Caire, X. Chen, and S. R. Khosravirad. Thanks to the two guest editor teams who did an excellent job in editing these two feature topics for our readers. Please stay tuned for new developments in the research area of IoT and next generation wireless communications and read the editorials and the papers in the feature topics.

5G URLLC: Evolution of High-Performance Wireless Networking for Industrial Automation

At the core of digital transformation of the manufacturing industry is the objective to unlock data at multiple points of the production system and produce insights to improve and optimize all aspects of the business operations. Tremendous advances in artificial intelligence and machine learning make it possible to analyze a vast volume of the field and production data and translate them into optimization decisions. Real-time access to the data complements efficient machine learning inference for timely and actionable insights. Flexible and re-configurable manufacturing also demands high-performance, pervasive, and low-la-tency communication links supporting mobility of workers, devices, and robots. Fifth Generation (5G) New Radio (NR) introduced basic support for Ultra Reliable and Low Latency Communication (urLLC) in Release-15 through intrinsic design features. Release-16 extends real-time capabilities of 5G NR to different verticals, addressing use cases in factory automation, the transport industry, and electrical power distribution. Wireless technologies such as 5G urLLC should co-exist with incumbent and emerging industrial Ethernet systems such as Time Sensitive Networking (TSN) in a heterogenous networking architecture. Hence, specification of interworking with TSN is also part of 3GPP Release-16. In this article, we discuss low-latency and high-reliability features supporting industrial automation, focusing on Release-16 design specifications. The interworking aspects with TSN and time synchronization accuracy limits are also highlighted, followed by performance evaluation of control and data traffic channels of 5G NR with respect to urLLC requirements.

COMBINED CRITERION FOR THE CHOICE OF ROUTING BASED ON D2D TECHNOLOGY

Context. 5G network is able to improve existing services and provide a new quality of services. 5G communication networks combine various radio technologies and technologies of fixed communication networks, therefore they are often called heterogeneous, which emphasizes their difference from other networks. One of the main features of such networks is over-density and ultra-low latency. It is the Internet of things that is the basic component of the concept of super dense networks. 3GPP suggests planning 5G networks based on the condition that 1 million devices is 1 km2. Also, ultra-low latency communications networks have a big impact on networking methods, especially for the tactile Internet concept. Such networks require decentralization through 1 ms delay requirements. This requires new approaches to building a new generation of networks, which is the reason for the development of new technologies. One such technology is D2D (device-to-device) technology. This technology allows you to reduce the load on the core of the network due to the use of a significant proportion of the traffic directly between devices and reduces the delay in providing services.&#x0D; Objective. The goal of the work is to create an optimal combined criterion for choosing effective traffic routes in a wireless network based on D2D technology.&#x0D; Method. Many modern works are devoted to the study of D2D technology, but they are not exhaustive in the study of routing in such networks. It is objective enough to study networks built on the basis of the interaction of devices with each other using D2D technology, since such interactions have proven to be effective technologies. This, in turn, involves the development of appropriate routing methods in networks using D2D technology, especially taking into account the property of over-density 5G networks. The paper proposes a criterion for selecting routes, taking into account interference within the channels forming the network nodes. This criterion combines the choice of routes according to the length criteria and the criterion of maximum throughput.&#x0D; Results. A developed combined criterion for selecting traffic routing in a wireless network that uses D2D technology. The results of the study are shown in graphic data.&#x0D; Conclusions. The experiments confirmed the efficiency and effectiveness of the developed method and allow us to recommend this method for practical use as a result of route selection, taking into account those network properties that are more likely to affect the quality of the route.