5G Ultra-reliable Low-latency Communication Research Articles

Adaptive contrastive learning based network latency prediction in 5G URLLC scenarios

With the increasing demand for 5G Ultra-Reliable Low Latency Communication (URLLC), accurate network time delay analysis is crucial. However, current network latency prediction models designed for 5G URLLC scenarios overlook the multiple downstream tasks case, such as network intrusion detection, recognition of network operational states, and decision-making for network resource scheduling.Furthermore, the robustness of the models needs to be enhanced. In this paper, we propose a Contrastive Convolutional Structure for Network Delay (CCSND), an adaptive contrastive learning framework that utilizes a temporal representation extraction module for capturing temporal periodicity and statistical features. To improve robustness and adaptability in time-series representation, CCSND designs strategic data augmentation methods, including temporal segmentation and delay obscuration. Experiment results on several real-world 5G URLLC scenario datasets demonstrate the superior performance of the proposed CCSND. It outperforms the current state-of-the-art Informer model by 38.7% and the traditional LSTM model by 64.5% in terms of mean squared error (MSE). Our code can be accessed at https://github.com/MerelyBreeze/CCSND.

Converging Game Theory and Reinforcement Learning For Industrial Internet of Things

The fifth-generation (5G) wireless network provides high-rate, ultra-low latency, and high-reliability connections that can meet the Industrial Internet of Things (IIoT) requirements in factory automation, especially for robot motion control. In this paper, we address 5G service provisioning in an automated warehouse scenario, where swarm robotics is controlled by an industrial controller that provides routing and job instructions over the 5G network. Leveraging the coordinated multipoint (CoMP), we formulate a time-varying joint CoMP clustering and 5G ultra-reliable low-latency communication (URLLC) beamforming design problem to control the robots that move around the automated warehouse for goods storage with the planned reference tracks. Traditional iterative optimization approaches are impractical in such a dynamic wireless environment due to high computational time. We propose a game-theoretic CoMP clustering algorithm combined with the Proximal Policy Optimization method to obtain a stationary solution closed to that of the exhaustive search algorithm considered as the global optimal solution.

XURLLC in 6G with meshed RAN

5G Ultra-Reliable Low Latency Communications Technology (URLLC) will not be able to provide extremely reliable low latency services to the complex networks in 6G. Moreover, URLLC that began with 5G has to be refined and improved in 6G to provide xURLCC (extreme URLCC) with sub-millisecond latency, for supporting diverse mission-critical applications. This paper aims to highlight the importance of peer-to-peer mesh connectivity for services that require xURLLC. Deploying mesh connectivity among RAN nodes would add significant value to the current 5G New Radio (5G NR) enabling 6G to increase flexibility and reliability of the networks while reducing the inherent latency introduced by the core network. To provide a mesh connectivity in RAN, the nodes should be able to communicate with each other directly and be independent from the mobile core network so that data can be directly exchanged between base stations (gNBs) whereas certain aspects of signalling procedure including data session establishment will be managed by RAN itself. In this paper, we introduce several architectural choices for a mesh network topology that could potentially be crucial to a number of applications. In addition, three possible options to create mesh connectivity in RAN are provided, and their pros and cons are discussed in detail.

Beyond 5G URLLC evolution: New service modes and practical considerations

Ultra-Reliable Low Latency Communications (URLLC) arose to serve Industrial IoT (IIoT) use cases within 5G. However, currently, it has inherent limitations in supporting future services. Therefore, in this article, based on state-of-the-art research and practical deployment experience, from two distinct test networks from Finland and South Korea, we introduce and advocate for three variants of critical Machine-Type Communications (MTC), namely, broadband, scalable and extreme URLLC. Moreover, we discuss use cases and key performance indicators and identify two critical technology enablers for each new service class. Finally, we bring practical considerations from the IIoT testbed and provide an outlook towards new research directions.

Interference Prediction for Low-Complexity Link Adaptation in Beyond 5G Ultra-Reliable Low-Latency Communications

Traditional link adaptation (LA) schemes in cellular network must be revised for networks beyond the fifth generation (b5G), to guarantee the strict latency and reliability requirements advocated by ultra reliable low latency communications (URLLC). In particular, a poor error rate prediction potentially increases retransmissions, which in turn increase latency and reduce reliability. In this paper, we present an interference prediction method to enhance LA for URLLC. To develop our prediction method, we propose a kernel based probability density estimation algorithm, and provide an in depth analysis of its statistical performance. We also provide a low complexity version, suitable for practical scenarios. The proposed scheme is compared with state-of-the-art LA solutions over fully compliant 3rd generation partnership project (3GPP) calibrated channels, showing the validity of our proposal.

Efficient resource allocation in 5G URLLC with packet duplication based macro-diversity

Packet duplication based macro-diversity is a potential solution to achieve high reliability and low latency, for ultra-reliable low-latency communication (URLLC) applications, like mission critical internet of things (IoT), in 5G cellular systems. Increased radio resource usage is the price paid for the benefits accrued. This paper proposes a framework to find the relaxed per link reliability targets and to perform radio resource and power allocation over the links, which can guarantee the user equipment (UE) reliability target and also provide spectrum efficient resource usage, when multiple base stations (BSs) serve each UE. The resource allocation problem that involves BS selection, packet length adaptation, and power allocation, is formulated to minimize the overall resource usage within the constraints of reliability, latency, resource availability, and transmit power. Inherent system dynamics that exist among packet length, decoding error probability, and transmit power are used in devising a lightweight heuristic solution. The two important findings are that: (i) with each UE, a stringent reliability target for the best link and relaxed reliability targets for the other links can provide a spectrum efficient solution; (ii) additional resource savings can be achieved by allocating more power to the UEs with poor channel conditions, at each BS. The proposed method can achieve up to 20% resource saving when compared to the blind duplication with equal power allocation.

Cluster-Based Transmission Diversity Optimization in Ultra Reliable Low Latency Communication

Intra-vehicular communication is an emerging technology explored spontaneously due to higher wireless sensor-based application demands. To meet the upcoming market demands, the current intra-vehicular communication transmission reliability and latency should be improved significantly to fit with the existing 5G and upcoming 6G communication domains. Ultra-Reliable Low-Latency Communication (URLLC) can be widely used to enhance the quality of communication and services of 5G and beyond. The 5G URLLC service is highly dependable for transmission reliability and minimizing data transmission latency. In this paper, a multiple-access scheme named Cluster-based Orthogonal Frequency Subcarrier-based Multiple Access (C-OFSMA) is proposed with 5G URLLC’s high requirement adaptation for intra-vehicular data transmission. The URLLC demanded high reliability of approximately 99.999% of the data transmission within the extremely short latency of less than 1 ms. C-OFSMA enhanced the transmission diversity, which secured more successful data transmission to fulfill these high requirements and adapt to such a network environment. In C-OFSMA, the available sensors transmit data over specific frequency channels where frequency selection is random and special sensors (audio and video) transmit data over dedicated frequency channels. The minimum number of subcarrier channels was evaluated for different arrival rates and different packet duplication conditions in order to achieve 99.999% reliability within an air-interface latency of 0.2 ms. For the fixed frequency channel condition, C-OFSMA and OFSMA were compared in terms of reliability response and other packet duplication. Moreover, the optimal number of clusters was also evaluated in the aspects of the reliability response for the C-OFSMA system.

HARQ Optimization for PDCP Duplication-Based 5G URLLC Dual Connectivity

Packet duplication (PD) with dual connectivity (DC) was newly introduced in the 5G New Radio (NR) specifications to meet the stringent ultra reliable low latency communication (URLLC) requirements. PD technology uses duplicated packets in the packet data convergence protocol (PDCP) layer that are transmitted via two different access nodes (ANs) to the user equipment (UE) in order to enhance the reliability performance. However, PD can result in unnecessary retransmissions in the lower layers since the hybrid automatic retransmission request (HARQ) operation is unaware of the transmission success achieved through the alternate DC link to the UE. To overcome this issue, in this paper, a novel duplication-aware retransmission optimization (DRO) scheme is proposed to reduce the resource usage induced by unnecessary HARQ retransmissions. The proposed DRO scheme can minimize the average channel use while satisfying the URLLC requirements. The proposed DRO scheme derives the optimal HARQ retransmission attempts for different ANs by solving a nonlinear integer programming (NLIP) problem. The performance of the proposed DRO scheme was evaluated using MATLAB simulation and is compared to the existing 5G HARQ support schemes. The simulations results show that the proposed DRO scheme can provide a 14.71% and 15.11% reduced average channel use gain compared to the selective data duplication upon failure (SDUF) scheme and latency-aware dynamic multi-connectivity algorithm (LADMA) scheme, respectively, which are the existing 5G PD schemes that use HARQ.

Analysis of Power Allocation for NOMA-Based D2D Communications Using GADIA

The new era of IoT brings the necessity of smart synergy for diverse communication and computation entities. The two extremes are, on the one hand, the 5G Ultra-Reliable Low-Latency Communications (URLLC) required for Industrial IoT (IIoT) and Vehicle Communications (V2V, V2I, V2X). While on the other hand, the Ultra-Low Power, Wide-Range, Low Bit-rate Communications, such as Sigfox, LoRa/LoRaWAN, NB-IoT, Cat-M1, etc.; used for smart metering, smart logistics, monitoring, alarms, tracking applications. This extreme variety and diversity must work in synergy, all inter-operating/inter-working with the Internet. The communication solutions must mutually cooperate, but there must be a synergy in a broader sense that includes the various communication solutions and all the processing and storage capabilities from the edge cloud to the deep-cloud. In this paper, we consider a non-orthogonal multiple access (NOMA)-based device to device (D2D) communication system coexisting with a cellular network and utilize Greedy Asynchronous Distributed Interference Avoidance Algorithm (GADIA) for dynamic frequency allocation strategy. We analyze a max–min fairness optimization problem with energy budget constraints to provide a reasonable boundary rate for the downlink to all devices and cellular users in the network for a given total transmit power. A comprehensive simulation and numerical evaluation is performed. Further, we compare the performance of maximum achievable rate and energy efficiency (EE) at a given spectral efficiency (SE) while employing NOMA and orthogonal frequency-division multiple access (OFDMA).

Cognitive Sub-Band Scheduling and Link Adaptation for 5G URLLC

Link adaptation for downlink 5G ultra-reliable low latency communication (URLLC) is quite challenging. While reduced feedback schemes for link adaptation are crucial to achieve high spectral efficiency, accuracy of sub-band channel quality indicator (CQI) reports is more critical in 5G URLLC because of the ultra-high reliability and efficient resource utilization requirements. The existing differential feedback mechanism cannot reconstruct sub-band CQIs at the BS exactly. In this paper, existing differential feedback mechanism for link adaptation is first investigated using analytical and simulation models to verify its limitations in reconstructing the sub-band CQIs and to study its impact on URLLC reliability and resource utilization efficiency. Then a cognitive link adaptation using a controlled differential feedback scheme for sub-band CQIs is proposed based on the investigations. Extensive simulation results are provided to show the superior performance of the proposed cognitive solution and to illustrate the theoretical analysis.

Design of Two-Step Random Access Procedure for URLLC Applications.

The International Telecommunication Union has required that the control plane (C-plane) latency in the fifth generation (5G) ultra-reliable low-latency communication (URLLC) application scenarios should not exceed 20 ms and encouraged technical innovation to further reduce it to less than 10 ms. However, the average C-plane latency in the fourth generation (4G) Long Term Evolution-Advanced (LTE-A) system is 80 ms. Such a high latency is because of the execution of the contention-based random access procedure (RAP). In this paper, we simplify the conventional contention-based RAP from 4 to 2 steps. Furthermore, utilization of demodulation reference signal for representing the UE ID and reservation of preambles for URLLC users significantly reduces the proposed 2-step RAP latency. From the perspectives of fixing the number of URLLC users and fixing the number of preambles reserved for URLLC users, simulation results show the percentage of successes for the 2-step RAP is 83.81% and 71.83% higher than that of the 4-step RAP, respectively. Consequently, the 10 ms latency requirement of the 5G URLLC is achieved.

Quantum Learning Based Nonrandom Superimposed Coding for Secure Wireless Access in 5G URLLC

Secure wireless access in ultra-reliable low-latency communications (URLLC), which is a critical aspect of 5G security, has become increasingly important due to its potential support of grant-free configuration. In grant-free URLLC, precise allocation of different pilot resources to different users that share the same time-frequency resource is essential for the next generation NodeB (gNB) to exactly identify those users under access collision and to maintain precise channel estimation required for reliable data transmission. However, this process easily suffers from attacks on pilots. We in this article propose a quantum learning based nonrandom superimposed coding method to encode and decode pilots on multidimensional resources, such that the uncertainty of attacks can be learned quickly and eliminated precisely. Particularly, multiuser pilots for uplink access are encoded as distinguishable subcarrier activation patterns (SAPs) and gNB decodes pilots of interest from observed SAPs, a superposition of SAPs from access users, by joint design of attack mode detection and user activity detection though a quantum learning network (QLN). We found that the uncertainty lies in the identification process of codeword digits from the attacker, which can be always modelled as a black-box model, resolved by a quantum learning algorithm and quantum circuit. Novel analytical closed-form expressions of failure probability are derived to characterize the reliability of this URLLC system with short packet transmission. Simulations how that our method can bring ultra-high reliability and low latency despite attacks on pilots.

Multi-Gigabit CO-OFDM System over SMF and MMF Links for 5G URLLC Backhaul Network

The 5G cellular network aims at providing three major services: Massive machine-type communication (mMTC), ultra-reliable low-latency communications (URLLC), and enhanced-mobile-broadband (eMBB). Among these services, the URLLC and eMBB require strict end-to-end latency of 1 ms while maintaining 99.999% reliability, and availability of extremely high data rates for the users, respectively. One of the critical challenges in meeting these requirements is to upgrade the existing optical fiber backhaul network interconnecting the base stations with a multigigabit capacity, low latency and very high reliability system. To address this issue, we have numerically analyzed 100 Gbit/s coherent optical orthogonal frequency division multiplexing (CO-OFDM) transmission performance over 400 km single-mode fiber (SMF) and 100 km of multi-mode fiber (MMF) links. The system is simulated over optically repeated and non-repeated SMF and MMF links. Coherent transmission is used, and the system is analyzed in a linear and non-linear regime. The system performance is quantified by bit error ratio (BER). Spectrally efficient and optimal transmission performance is achieved for 400 km SMF and 100 km MMF link. The results designate that MMF links can be employed beyond short reach applications by using them in the existing SMF infrastructure for long haul transmission. In particular, the proposed CO-OFDM system can be efficiently employed in 5G backhaul network. The multi-gigabit capacity and lower BER of the proposed system makes it a suitable candidate especially for the eMBB and URLLC requirements for 5G backhaul network.

On the Multiplexing of Data and Metadata for Ultra-Reliable Low-Latency Communications in 5G

This paper addresses the problem of downlink radio resource management for ultra-reliable low-latency communications (URLLC) in fifth generation (5G) systems. To support low-latency communications, we study performance of two multiplexing schemes namely in-resource control signalling and joint encoding of data and metadata . In the former, the metadata and data are separately encoded and the metadata is sent at the beginning of transmission time prior to the data. Thus, it benefits from a low-complexity receiver structure to decode the data block. The latter takes advantages of transmitting a larger blocklength to enhance the reliability and improve spectrum efficiency by jointly encoding data and metadata as a single codeword. Dealing with small URLLC payloads, the overhead and error of sending metadata are not negligible and have a significant impact on the system performance in terms of resource usage the reliability of transmission. For each scheme, we derive expressions for the outage probability and resource usage by taking into account impacts of the finite blocklength payloads, overhead and error of sending metadata, and probability of error in uplink feedback channel. We propose a novel framework for joint data and metadata link adaptation to minimize the average number of allocated resources, while ensuring the stringent URLLC quality of service requirements. An optimization problem is formulated for each scheme that is mixed-integer non-convex problem, difficult to solve in polynomial time. Solutions based on successive convex optimization are proposed. Numerical evaluations show that the proposed algorithms perform close to the optimal solution and demonstrate remarkable gains of up to $\mathbf {27\%}$ improvement in resource usage. Finally, we present sensitivity analysis of the results for various network parameters.

5G URLLC: A Case Study on Low-Latency Intrusion Prevention

5G introduces different communication types to support novel applications, e.g., industrial control, depending on ultra-reliable, low-latency communication (URLLC) to provide their service. To realize this type of communication, network operators offer virtual end-to-end networks, called network slices, to their customers, and service level agreements of the operators promise a certain quality of service for the provided network slices. The main challenge is the creation of network slices that adhere to these strict requirements despite virtualized resources shared across different network slices. In this article, we analyze the latency performance of typical virtualized network functions. Based on these results, we derive guidelines to lower latency and propose a system architecture for hosting low-latency network functions. We measure the latency performance of a security network function, an intrusion prevention system based on Snort 3, and demonstrate that URLLC-compliant latency performance is achievable. Our entire architecture relies on off-the-shelf hardware and widely adopted software components, making our findings highly applicable to situations where low latency is crucial. All artifacts used in this article, the investigated software, the pcap traces, and the experiments scripts are publicly available at https://gallenmu. github.io/low-latency/.

Design and performance evaluation of contention-based transmission schemes for URLLC services

We investigate in this paper uplink transmission schemes for 5G Ultra-Reliable Low Latency Communications (URLLC) traffic. The URLLC class of services has been defined for applications requiring extremely stringent latency and reliability. We show that, in systems with episodic traffic and many users compared with the number of transmission resources, randomly transmitting multiple copies of a packet allows to meet the URLLC requirements. We first develop an analytical model for the packet loss rate for a contention based multiple transmission scheme where replica positions are assigned randomly and show that it allows to meet the performance requirements of URLLC for small enough user activity rate. We then propose an advanced replication scheme where positions for the different replicas are pre-allocated to users so that users have pairwise-distinct positions. We show that this advanced scheme achieves very high reliability with low resource consumption.

Immersive Interconnected Virtual and Augmented Reality: A 5G and IoT Perspective

Despite remarkable advances, current augmented and virtual reality (AR/VR) applications are a largely individual and local experience. Interconnected AR/VR, where participants can virtually interact across vast distances, remains a distant dream. The great barrier that stands between current technology and such applications is the stringent end-to-end latency requirement, which should not exceed 20 ms in order to avoid motion sickness and other discomforts. Bringing AR/VR to the next level to enable immersive interconnected AR/VR will require significant advances towards 5G ultra-reliable low-latency communication (URLLC) and a Tactile Internet of Things (IoT). In this article, we articulate the technical challenges to enable a future AR/VR end-to-end architecture, that combines 5G URLLC and Tactile IoT technology to support this next generation of interconnected AR/VR applications. Through the use of IoT sensors and actuators, AR/VR applications will be aware of the environmental and user context, supporting human-centric adaptations of the application logic, and lifelike interactions with the virtual environment. We present potential use cases and the required technological building blocks. For each of them, we delve into the current state of the art and challenges that need to be addressed before the dream of remote AR/VR interaction can become reality.

A Reliability and latency-aware routing framework for 5G transport infrastructures

The 5G technology is providing totally new opportunities to mobile communications and their related applications, fostering the creation of service ecosystems and business models that will significantly revolutionize our daily life. With its massive scalability, resiliency and time-sensitive performance demands it will significantly increase the footprint of the underlying transport infrastructure by requiring new control plane facilities capable of supporting the specific needs characterizing end-to-end connections between mobile devices and their targets. Such facilities, built on top of an optical backhaul/fronthaul layer must rely on new routing mechanisms able to meet 5G Ultra-Reliable Low-Latency Communication requirements. Accordingly, this work presents a novel multi-objective distributed online routing scheme for converged fiber-radio transport infrastructures. Such scheme is able to guarantee the 5G reliability and delay optimization needs, while simultaneously taking into account the more traditional network engineering objectives, aiming at satisfying the maximum number of communication requests by taking the best from the already made infrastructural investments. Its effectiveness has been demonstrated through extensive simulation experiments that resulted in quite promising outcomes, enforcing confidence in future industrial developments.

5G-Enabled Fault Detection and Diagnostics: How Do We Achieve Efficiency?

The 5th-generation wireless networks (5G) technologies and mobile edge computing (MEC) provide great promises of enabling new capabilities for the industrial Internet of Things. However, the solutions enabled by the 5G ultra-reliable low-latency communication (URLLC) paradigm come with challenges, where URLLC alone does not necessarily guarantee the efficient execution of time-critical fault detection and diagnostics (FDD) applications. Based on the Tennessee Eastman Process model, we propose the concept of the communication-edge-computing (CEC) loop and a system model for evaluating the efficiency of FDD applications. We then formulate an optimization problem for achieving the defined CEC efficiency and discuss some typical solutions to the generic CEC-based FDD services, and propose a new uplink-based communication protocol called "ReFlexUp". From the performance analysis and numerical results, the proposed ReFlexUp protocol shows its effectiveness compared to the typical protocols such as Selective Repeat ARQ, HARQ, and "Occupy CoW" in terms of the key metrics such as latency, reliability, and efficiency. These results are further convinced from the mmWave-based simulations in a typical 5G MEC-based implementation.

5G Ultra-Reliable Low-Latency Communication Implementation Challenges and Operational Issues with IoT Devices

To meet the diverse industrial and market demands, the International Telecommunication Union (ITU) has classified the fifth-generation (5G) into ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). Researchers conducted studies to achieve the implementation of the mentioned distributions efficiently, within the available spectrum. This paper aims to highlight the importance of URLLC in accordance with the approaching era of technology and industry requirements. While highlighting a few implementation issues of URLLC, concerns for the Internet of things (IoT) devices that depend on the low latency and reliable communications of URLLC are also addressed. In this paper, the recent progress of 3rd Generation Partnership Project (3GPP) standardization and the implementation of URLLC are included. Finally, the research areas that are open for further investigation in URLLC implementation are highlighted, and efficient implementation of URLLC is discussed.