Ultra-Reliable Low-Latency Communications: Foundations, Enablers, System Design, and Evolution Towards 6G

Ultra-reliable low latency communication (URLLC) is an innovative service offered by fifth-generation (5G) wireless systems. URLLC enables various mission-critical applications by facilitating reliable and low-latency signal transmission. Apart from reliability and latency, ensuring the security of URLLC data transmission has been a prominent issue in recent years. URLLC uses finite blocklength signals to achieve the stringent reliability and latency requirement which eliminates the possibility of using conventional complex secret key-based cryptographic techniques. In this regard, lightweight security mechanisms like physical layer Security (PLS) have emerged as a powerful alternative to the complex cryptographic security techniques for URLLC by exploiting the randomness of the wireless channel. Therefore, this survey presents a comprehensive and in-depth review of the state-of-the-art PLS enhancements utilized to unleash secure URLLC in 5G and upcoming sixth-generation (6G) wireless networks. Moreover, the survey discusses the impact of system design parameters on the PLS of URLLC. It also incorporates a detailed overview of the recent advancements in ensuring PLS for mission-critical applications, URLLC enabling technologies, and Machine Learning (ML) based intelligent PLS schemes for URLLC. Then, for the first time, the survey introduces the extended service class of URLLC in 6G, i.e., Hyper Reliable Low Latency Communication (HRLLC), and provides an outlook on the future security aspects while identifying various promising new technologies that can provide secure HRLLC in 6G. Finally, the survey discusses several key challenges and identifies interesting future research directions for developing efficient PLS schemes for 5G URLLC and HRLLC service in 6G wireless networks.

Background. Ultra-Reliable Low Latency Communication (URLLC) as a service offered by fifth and sixth generation (5G/6G) wireless systems is a technological response to the needs of various mission-critical applications that require reliable data transmission with low latency. These applications also include Intelligent Transportation Systems services, which, among other things, provide connectivity and autonomous vehicle control. The combination of high reliability and low latency requirements in URLLC usage scenarios creates a security problem for URLLC data transmission that cannot be solved using conventional complex cryptographic methods based on a secret key. The article discusses in detail the approach to using physical layer security mechanisms (physical layer security - PLS) as a powerful alternative to classical cryptographic security methods for URLLC, and also proposes the application of the wire-tap channel concept in URLLC with an analysis of the efficiency that can be achieved for physical layer security. Objective. The aim of the article is to provide an overview of information security solutions in URLLC usage scenarios, as well as to propose a constructive method for information protection for reliable data transmission with low latency without the use of cryptographic mechanisms based on a secret key. Methods. Theoretical research in the field of the branch channel concept was used to create solutions that allow data protection with information-theoretic stability in URLLC usage scenarios for providing IoT, connected car and autonomous driving services. Results. The article examines in detail the data security issues in ultra-reliable low latency communication (URLLC) as a service offered by fifth and sixth generation (5G/6G) wireless systems. It is determined that URLLC is a technological response to the needs of various critical applications that require reliable signal transmission with low latency, and among these applications are Intelligent Transportation Systems services, which, among other things, provide connectivity and autonomous vehicle control. It is shown that the combination of high reliability and low latency requirements in URLLC scenarios creates a security problem for URLLC data transmission that cannot be solved using conventional complex cryptographic methods based on a secret key. The feasibility of using physical layer security mechanisms (PLS) as a powerful alternative to classical cryptographic security methods for URLLC is substantiated. The approach to applying the concept of a wire-tap channel in URLLC is considered in detail, as well as the results that can be achieved for physical layer security, and the influence of code parameters for probabilistic cryptographic transformations in accordance with the concept of a wire-tap channel on PLS URLLC. Estimates of the effectiveness of PLS URLLC for finite block length codes are provided. Conclusions. An effective way to ensure data security for ultra-reliable low-latency physical layer link (PLS URLLC) of fifth-generation 5G wireless systems in the field of connected cars and vehicles of 4-5 levels of automation can be approaches based on the concept of a tapped channel ("wire-tap channel").

The rapid advancement of technology has brought about the era of Ultra Reliable Low Latency Communication (URLLC) which holds importance in todays world. This paper explores the significance of URLLC in relation, to the generation of mobile communications technology (5G) and the Internet of Things (IoT) by employing a methodical approach of literature analysis and synthesis. Through analysis, this paper discovered that both 5G and IoT individually play substantial roles in enhancing communication and connectivity, and their combined potential is truly transformative especially when it comes to achieving URLLC across industries. This convergence opens up possibilities for reality virtual reality warehouse automation and other groundbreaking applications. However, there are challenges that must be carefully examined and addressed on the path to achieving an integrated URLLC in the future. These challenges encompass problems related to scheduling and energy efficiency, alongside technical concerns such as economics and regulatory obstacles. By confronting these challenges and promoting a mindset it is possible to fully embrace the opportunity to enter an era where URLLC, 5G and IoT blend harmoniously enabling groundbreaking applications and fueling innovation, in industries.

<p>Ultra-Reliable Low Latency Communications (URLLC) is a key service in fifth generation (5G) networks, that requires stringent Quality of Service (QoS) in terms of latency and reliability. As URLLC services may require specific numerology and/or specific channel access and re-transmission strategies, network slicing has been proposed as a solution for multiplexing them with other services such as enhanced Mobile Broadband (eMBB). Once the URLLC slice is configured and resources are dimensioned and allocated to it, URLLC performance targets should be attained thanks to the 5G New Radio (NR) low latency and high reliability features. However, in vehicular services such as safety message exchange, URLLC slice resource dimensioning cannot be static due to the varying number of vehicles in the cell. We show in this paper how the delay for slice reconfiguration alters the URLLC performance and propose a proactive resource reservation scheme that anticipates slice needs and allows ensuring URLLC targets. In order to reduce the impact of this proactive reservation on eMBB performance, we make use of vehicle trajectory prediction and show that limiting anticipated reservation to fewer cells allows reaching the target URLLC QoS with a limited degradation of the network capacity.</p>

In this paper, a novel multi-objective resource allocation scheme is proposed for downlink joint enhanced mobile broadband (eMBB) and ultra reliable low latency communication (URLLC) traffic with different quality-of-service (QoS) requirements. eMBB and URLLC are two service categories in the emerging fifth generation (5G) cellular networks which encompass applications with high throughput and stringent latency and reliability demands, respectively. To meet these heterogeneous requirements, 5G networks need impressive improvements in the air interface and core network architecture. In this paper, by applying a scalarization method for multi- objective optimization, both the eMBB and URLLC performance in the downlink channel are improved. Different types of URLLC users with various latency requirements are considered. To further enhance the reliability, the URLLC users with stringent delay demands are prioritized over the users with looser latency needs. In the simulation results, the performance of the proposed resource allocation policy is assessed and it is shown that our introduced scheme can achieve higher reliability and lower delay for the URLLC traffic compared with the other approaches in the literature.

International audience

5G systems are supposed to support coexistence of multiple services such as ultra reliable low latency communications (URLLC) and enhanced mobile broadband (eMBB) communications. The target of eMBB communications is to meet the high-throughput requirement while URLLC are used for some high priority services. Due to the sporadic nature and low latency requirement, URLLC transmission may pre-empt the resource of eMBB transmission. Our work is to analyze the URLLC impact on eMBB transmission in mobile front-haul. Then, some solutions are proposed to guarantee the reliability/latency requirements for URLLC services and minimize the impact to eMBB services at the same time.

The 3rd Generation Partnership Project (3GPP) organization has considered Ultra Reliable Low Latency Communications (URLLC)'s low latency requirement and spectrum resources shortage. So it has proposed a multiplexing enhanced Mobile Broad Band (eMBB) and URLLC method based on puncturing. But this multiplexing will cause the loss of eMBB users' data rate. Therefore, we propose a two-stage eMBB resource allocation scheme and preference-based URLLC resource preemption schemes for bandwidth-sensitive URLLC and time-sensitive URLLC respectively to enhance eMBB reliability. Particularly, we design the comprehensive preference value to provide protection for eMBB users with poor channel conditions and high service requirements during URLLC preemption, thereby improving these users' satisfaction. Simulation results show the advantages of our proposed scheme.

Ultra-reliable low-latency communication (URLLC) has been introduced in 5G new radio for new applications that have strict reliability and latency requirements such as augmented/virtual reality, industrial automation and autonomous vehicles. The first full set of the physical layer design of 5G release, Release 15, was finalized in December 2017. It provided a foundation for URLLC with new features such as flexible sub-carrier spacing, a sub-slot-based transmission scheme, new channel quality indicator, new modulation and coding scheme tables, and configured-grant transmission with automatic repetitions. The second 5G release, Release 16, was finalized in December 2019 and allows achieving improved metrics for latency and reliability to support new use cases of URLLC. A number of new features such as enhanced physical downlink (DL) control channel monitoring capability, new DL control information format, sub-slot physical uplink (UL) control channel transmission, sub-slot-based physical UL shared channel repetition, enhanced mobile broadband and URLLC inter-user-equipment multiplexing with cancellation indication and enhanced power control were standardized. This article provides a detailed overview of the URLLC features from 5G Release 15 to Release 16 by describing how these features allow meeting URLLC target requirements in 5G networks. The ongoing Release 17 targets further enhanced URLLC operation by improving mechanisms such as feedback, intra-user-equipment multiplexing and prioritization of traffic with different priority, support of time synchronization and new quality of service related parameters. In addition, a fundamental feature targeted in URLLC Release 17 is to enable URLLC operation over shared unlicensed spectrum. The potential directions of URLLC research in unlicensed spectrum in Release 17 are presented to serve as a bridge from URLLC in licensed spectrum in Release 16 to URLLC in unlicensed spectrum in Release 17.

Ultra-reliable low latency communications (URLLC) is one of the most important scenarios in 5G. URLLC with strict latency and reliability requirements is widely used in delay-sensitive applications such as self-driving. As the 3GPP claimed, the URLLC is amenable to 99.999% transmission correctness and within 1 ms delay bound. How to meet the requirements of reliability and latency is still an open issue. Few efforts have been made on applying a theoretical method to analyze the delay bound. Stochastic network calculus is an elegant way to obtain the delay bound based on traffic models and service guarantees. In this paper, we take the character of 5G architecture into account and use the stochastic network calculus to analyze the delay in URLLC. A tandem model is built to simulate the generation of delay in 5G network. Some factors which can influence on the delay are obtained. Numerical results are presented to verify the correctness of the delay analysis. Optimizing these factors to reduce the delay will provide valuable guidelines for the early design of URLLC architecture.

In this paper, we study the joint resource scheduling problem for multiplexing two distinct 5 G services: enhanced mobile broadband (eMBB) and ultra-reliable low latency communications (URLLC). While eMBB services require high data rates, URLLC services lay more emphasis on extremely low latency and high reliability. To satisfy these heterogeneous requirements for eMBB and URLLC coexistence, we propose a risk-resistant scheme for resource allocation to both eMBB and URLLC traffic that aims to maximize the eMBB data rate, while considering the URLLC delay threshold violation to maintain URLLC delay requirements. Based on the M/G/1 queueing model, the URLLC packet latency target is realized by minimizing the average packet delay in violation cases, where “violation” is judged by introducing the “conditional value at risk (CVaR)” as a risk metric (i.e., “risk” here is defined as URLLC delay threshold violation). To solve the formulated problem, we transform it into two convex optimization problems to obtain a near-optimal resource allocation solution. Simulation results show that the proposed scheme improves the fairness among the eMBB users and eMBB throughput by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$30\%\sim 34\%$</tex-math></inline-formula> compared to existing works, while satisfying the stringent URLLC delay requirements.

The tactile internet (TI) is believed to be the prospective advancement of the internet of things (IoT), comprising human-to-machine and machine-to-machine communication. TI focuses on enabling real-time interactive techniques with a portfolio of engineering, social, and commercial use cases. For this purpose, the prospective $5^{th}$ generation (5G) technology focuses on achieving ultra-reliable low latency communication (URLLC) services. TI applications require an extraordinary degree of reliability and latency. The $3^{rd}$ generation partnership project (3GPP) defines that URLLC is expected to provide 99.99% reliability of a single transmission of 32 bytes packet with a latency of less than one millisecond. 3GPP proposes to include an adjustable orthogonal frequency division multiplexing (OFDM) technique, called 5G new radio (5G NR), as a new radio access technology (RAT). Whereas, with the emergence of a novel physical layer RAT, the need for the design for prospective next-generation technologies arises, especially with the focus of network intelligence. In such situations, machine learning (ML) techniques are expected to be essential to assist in designing intelligent network resource allocation protocols for 5G NR URLLC requirements. Therefore, in this survey, we present a possibility to use the federated reinforcement learning (FRL) technique, which is one of the ML techniques, for 5G NR URLLC requirements and summarizes the corresponding achievements for URLLC. We provide a comprehensive discussion of MAC layer channel access mechanisms that enable URLLC in 5G NR for TI. Besides, we identify seven very critical future use cases of FRL as potential enablers for URLLC in 5G NR.

At a density of one million devices per square kilometer, the10’s of billions of devices, objects, and machines that form a massive Internet of things (mIoT) require ubiquitous connectivity. Among a massive number of IoT devices, a portion of them require ultra-reliable low latency communication (URLLC) provided via fifth generation (5G) networks, bringing many new challenges due to the stringent service requirements. Albeit a surge of research efforts on URLLC and mIoT, access mechanisms which include both URLLC and massive machine type communications (mMTC) have not yet been investigated in-depth. In this paper, we propose three novel schemes to facilitate priority-based initial access for mIoT/mMTC devices that require URLLC services while also considering the requirements of other mIoT/mMTC devices. Based on a long term evolution-advanced (LTE-A) or 5G new radio frame structure, the proposed schemes enable device grouping based on device vicinity or/and their URLLC requirements and allocate dedicated preambles for grouped devices supported by flexible slot allocation for random access. These schemes are able not only to increase the reliability and minimize the delay of URLLC devices but also to improve the performance of all involved mIoT devices. Furthermore, we evaluate the performance of the proposed schemes through mathematical analysis as well as simulations and compare the results with the performance of both the legacy LTE-A based initial access scheme and a grant-free transmission scheme.

In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile BroadBand (eMBB). While eMBB services focus on high data rates, URLLC is very strict in terms of latency and reliability. In view of this, the resource slicing problem is formulated as an optimization problem that aims at maximizing the eMBB data rate subject to a URLLC reliability constraint, while considering the variance of the eMBB data rate to reduce the impact of immediately scheduled URLLC traffic on the eMBB reliability. To solve the formulated problem, an optimization-aided Deep Reinforcement Learning (DRL) based framework is proposed, including: 1) eMBB resource allocation phase, and 2) URLLC scheduling phase. In the first phase, the optimization problem is decomposed into three subproblems and then each subproblem is transformed into a convex form to obtain an approximate resource allocation solution. In the second phase, a DRL-based algorithm is proposed to intelligently distribute the incoming URLLC traffic among eMBB users. Simulation results show that our proposed approach can satisfy the stringent URLLC reliability while keeping the eMBB reliability higher than 90%.

QoS aware resource allocation for coexistence mechanisms between eMBB and URLLC: Issues, challenges, and future directions in 5G