Ultra-high Reliability Research Articles

Secure Triggering Frame-Based Dynamic Power Saving Mechanism against Battery Draining Attack in Wi-Fi-Enabled Sensor Networks.

Wireless local area networks (WLANs) have recently evolved into technologies featuring extremely high throughput and ultra-high reliability. As WLANs are predominantly utilized in Internet of Things (IoT) and Wi-Fi-enabled sensor applications powered by coin cell batteries, these high-efficiency, high-performance technologies often cause significant battery depletion. The introduction of the trigger frame-based uplink transmission method, designed to enhance network throughput, lacks adequate security measures, enabling attackers to manipulate trigger frames. Devices receiving such frames must respond immediately; however, if a device receives a fake trigger frame, it fails to enter sleep mode, continuously sending response signals and thereby increasing power consumption. This problem is specifically acute in next-generation devices that support multi-link operation (MLO), capable of simultaneous transmission and reception across multiple links, rendering them more susceptible to battery draining attacks than conventional single-link devices. To address this, this paper introduces a Secure Triggering Frame-Based Dynamic Power Saving Mechanism (STF-DPSM) specifically designed for multi-link environments. Experimental results indicate that even in a multi-link environment with only two links, the STF-DPSM improves energy efficiency by an average of approximately 55.69% over conventional methods and reduces delay times by an average of approximately 44.7% compared with methods that consistently utilize encryption/decryption and integrity checks.

A Lean Networking Framework (LeaNet): Potential Technical Space and Approaches for Latency Sensitive Mobile Services

With the development of mobile services such as the Internet of vehicles, industrial Internet, and holographic communication, ultra-low latency, ultra-high reliability, and pervasive mobility have become common indicators of the comprehensive interconnection between human-machine-things. These common indicators are the foundations to expand the application scenarios of 5G communication technologies and are also the key to achieving the 6G vision. This paper summarizes the technologies in various layers of low-latency mobile networks from a panoramic perspective and highlights the limitations of previous works in terms of mobile network architecture, virtualization technology, and service function chaining (SFC) deployment. Also, the potential techniques space from these three aspects is analyzed. Based on this, a technical framework, named lean networking (LeaNet), is proposed in this paper to reduce latency for network services through global optimization. The compact architecture eliminates triangular routing, thus significantly simplifying the network architecture and reducing both link and node latency. Meanwhile, the network functions virtualization with real-time performance provides a feasible solution to hybrid deployment of multi-scenario and diversified services, especially for latency-sensitive applications. Besides, the framework for intelligent and closed-loop SFC deployment with low latency and high resource efficiency is established and analyzed comprehensively. Simulation studies verify that LeaNet is superior in reducing latency over typical 5G core networks.

Achieving Ultra-High Reliability for Haptic Communications in 6G Mobile Networks

Achieving Ultra-High Reliability for Haptic Communications in 6G Mobile Networks

Computational-Intelligence-Based Scheduling with Edge Computing in Cyber-Physical Production Systems.

Real-time performance and reliability are two critical indicators in cyber-physical production systems (CPPS). To meet strict requirements in terms of these indicators, it is necessary to solve complex job-shop scheduling problems (JSPs) and reserve considerable redundant resources for unexpected jobs before production. However, traditional job-shop methods are difficult to apply under dynamic conditions due to the uncertain time cost of transmission and computation. Edge computing offers an efficient solution to this issue. By deploying edge servers around the equipment, smart factories can achieve localized decisions based on computational intelligence (CI) methods offloaded from the cloud. Most works on edge computing have studied task offloading and dispatching scheduling based on CI. However, few of the existing methods can be used for behavior-level control due to the corresponding requirements for ultralow latency (10 ms) and ultrahigh reliability (99.9999% in wireless transmission), especially when unexpected computing jobs arise. Therefore, this paper proposes a dynamic resource prediction scheduling (DRPS) method based on CI to achieve real-time localized behavior-level control. The proposed DRPS method primarily focuses on the schedulability of unexpected computing jobs, and its core ideas are (1) to predict job arrival times based on a backpropagation neural network and (2) to perform real-time migration in the form of human-computer interaction based on the results of resource analysis. An experimental comparison with existing schemes shows that our DRPS method improves the acceptance ratio by 25.9% compared to the earliest deadline first scheme.

Secure short-packet transmission in uplink massive MU-MIMO assisted URLLC under imperfect CSI

Ultra-reliable and low-latency communication (URLLC) is still in the early stage of research due to its two strict and conflicting requirements, i.e., ultra-low latency and ultra-high reliability, and its impact on security performance is still unclear. Specifically, short-packet communication is expected to meet the delay requirement of URLLC, while the degradation of reliability caused by it makes traditional physical-layer security metrics not applicable. In this paper, we investigate the secure short-packet transmission in uplink massive multiuser multiple-input-multiple-output (MU-MIMO) system under imperfect channel state information (CSI). We propose an artificial noise scheme to improve the security performance of the system and use the system average secrecy throughput (AST) as the analysis metric. We derive the approximate closed-form expression of the system AST and further analyze the system asymptotic performance in two regimes. Furthermore, a one-dimensional search method is used to optimize the maximum system AST for a given pilot length. Numerical results verify the correctness of theoretical analysis, and show that there are some parameters that affect the tradeoff between security and latency. Moreover, appropriately increasing the number of antennas at the base station (BS) and transmission power at user devices (UDs) can increase the system AST to achieve the required threshold.

Dynamic extended sigmoid-based scheduling with virtualized RB allocation for maximizing frequency numerology efficiency in 5G/B5G NR networks

New trends of extremely ultra-low delay, ultra-high reliability, long-distance high-moving, etc., are strongly required for achieving Emergency resecure, Active Safe Driving (ASD), IoV communications, LEO communications, etc. Thus, 3GPP 5 G/B5G specifies flexible numerology technology providing different frequency SCS modes with different slot-times for diverse types of flows requiring different 5QIs in terms of delay, data rate, jitter, loss probability, and reliability. Although based on the frequency numerology, 3GPP Release 17 specifies three types of RB allocations, i.e., Types 0, 1, and dynamic switching allocations for UL access, such static and consecutive RB allocations result in inefficient numerology and frequency spectrum efficiency. As a result, typical critical issues exhibit in B5G NR, including high mutual exclusion (MX) of numerology, RB state independency flow scheduling, and static RB allocations suffering from dynamic flowing traffic. Thus, this paper proposes the Extended Sigmoid-based Scheduling with a Virtualized RB Allocation (SSA) consisting of two phases. Phase 1 proposes an Extended Sigmoid-based Cost-based Flow Scheduling (SCFS) algorithm to dynamically differentiate flow priorities. Phase 2 proposes a dynamic Virtualized RB pre-Allocation (VRBA) mechanism to maximize radio RB utilization and minimize mutual exclusion in 5 G frequency numerology. Numerical results indicate that the proposed SSA outperforms the compared approaches in network delay, jitter, resource utilization, network reward, and net-profit. Consequently, this paper achieves several objectives and contributions: 1) analyzing the QoS requirements of different applications with limited frequency spectrum, 2) proposing vRB state-related dynamic flow scheduling algorithm to maximize network efficiency, 3) minimizing numerology MX for vRB allocation, and 4) proposing adaptive cost-reward-based scheduling.

Ultra reliability and massive connectivity provision in integrated internet of military things (IoMT) based on tactical datalink

One of the major challenges arising in internet of military things (IoMT) is accommodating massive connectivity while providing guaranteed quality of service (QoS) in terms of ultra-high reliability. In this regard, this paper presents a class of code-domain nonorthogonal multiple accesses (NOMAs) for uplink ultra reliable networking of massive IoMT based on tactical datalink such as Link-16 and joint tactical information distribution system (JTIDS). In the considered scenario, a satellite equipped with Nr antennas servers K devices including vehicles, drones, ships, sensors, handset radios, etc. Nonorthogonal coded modulation, a special form of multiple input multiple output (MIMO)-NOMA is proposed. The discussion starts with evaluating the output signal to interference-plus-noise (SINR) of receiver filter, leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered. The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved. The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying (MSK) and Gaussian MSK (GMSK), two pivotal modulation formats in IoMT standards such as Link-16 and JITDS. Numerical results show that near capacity performance is offered. Fortunately, the performance is obtained using simple forward error corrections (FECs) of higher coding rate than existing schemes do, while the transmit power is reduced by 6 dB. The proposed design finds wide applications not only in IoMT but also in deep space communications, where ultra reliability and massive connectivity is a keen concern.

A Novel Adaptive UE Aggregation-Based Transmission Scheme Design for a Hybrid Network with Multi-Connectivity

With the progress of the eras and the development of science and technology, the requirements of device-to-device (D2D) connectivity increased rapidly. As one important service in future systems, ultra-reliable low-latency communication (URLLC) has attracted attention in many applications, especially in the Internet of Things (IoT), smart cities, and other scenarios due to its characteristics of ultra-low latency and ultra-high reliability. However, in order to achieve the requirement of ultra-low latency, energy consumption often increases significantly. The optimization of energy consumption and the latency of the system in the communication field are often in conflict with each other. In this paper, in order to optimize the energy consumption and the latency jointly under different scenarios, and since the detailed requirements for latency and reliability are diverse in different services, we propose an adaptive UE aggregation (AUA)-based transmission scheme that explores the diversity gain of multiple simultaneous paths to reduce the overall latency of data transmission, wherein multiple paths correspond to multiple coordination nodes. Furthermore, it could provide the feasibility of link adaptation by adjusting the path number according to the real transmission environment. Then, unnecessary energy waste could be avoided. To evaluate the performance, the energy-delay product (EDP) is proposed for the latency and energy comparison. The provided simulation results align with the numerical data. Through the analysis, it can be proven that the proposed scheme can achieve a joint optimization of latency and energy consumption to meet different types of URLLC services.

Quantum Learning on Structured Code With Computing Traps for Secure URLLC in Industrial IoT Scenarios

Resilient and secure ultra-reliable low-latency communications (URLLC) over radio interface is expected to play a crucial role in next generation Industrial IoT scenarios. However, attacking wireless pilot signals has been a potential easy way to interrupt URLLC services. In this work, we propose a random structured code to encode and decode pilot signals on multidimensional physical resources, and also design a quantum learning framework to make this code secure and reliable. Specifically, the code suggests using random encoding with little structures to disperse the effect of attacks. We find that the decoding process can be modeled as a computing trap if the group spatial channel features are employed. The security problem is therefore transformed as a random computing with redundancy. We employ a quantum algorithm to learn the computing trap model such that the computing redundancy can be removed quickly while the dispersed attack can be eliminated. In this respect, we can prove the existence of the quantum black-box model corresponding to the computing trap, and derive a precise expression of computing performance. Based on the result, we can formulate novel analytical closed-form expressions of system failure probability to characterize the reliability of the URLLC. Numerical results show that the proposed system can maintain ultra-high reliability and low latency against attacks on wireless pilots.

Design of Multi-User Noncoherent Massive SIMO Systems for Scalable URLLC.

This paper develops and optimizes a non-orthogonal and noncoherent multi-user massive single-input multiple-output (SIMO) framework, with the objective of enabling scalable ultra-reliable low-latency communications (sURLLC) in Beyond-5G (B5G)/6G wireless communication systems. In this framework, the huge diversity gain associated with the large-scale antenna array in the massive SIMO system is leveraged to ensure ultra-high reliability. To reduce the overhead and latency induced by the channel estimation process, we advocate for the noncoherent communication technique, which does not need the knowledge of instantaneous channel state information (CSI) but only relies on large-scale fading coefficients for message decoding. To boost the scalability of noncoherent massive SIMO systems, we enable the non-orthogonal channel access of multiple users by devising a new differential modulation scheme to ensure that each transmitted signal matrix can be uniquely determined in the noise-free case and be reliably estimated in noisy cases when the antenna array size is scaled up. The key idea is to make the transmitted signals from multiple geographically separated users be superimposed properly over the air, such that when the sum signal is correctly detected, the signal sent by each individual user can be uniquely determined. To further enhance the average error performance when the array antenna number is large, we propose a max-min Kullback-Leibler (KL) divergence-based design by jointly optimizing the transmitted powers of all users and the sub-constellation assignments among them. The simulation results show that the proposed design significantly outperforms the existing max-min Euclidean distance-based counterpart in terms of error performance. Moreover, our proposed approach also has a better error performance compared to the conventional coherent zero-forcing (ZF) receiver with orthogonal channel training, particularly for cell-edge users.

Towards Critical Industrial Wireless Control: Prototype Implementation and Experimental Evaluation on URLLC

Ultra reliable low latency communication (URLLC) is a promising technology to enable critical industrial wireless control, such as tactile sensing and motion control. This article presents a novel software-defined URLLC prototype and establishes a human-in-loop robotic teleoperation platform for experimental evaluations. First, by studying the control and communication requirements of robotic teleoperation, the key challenges for URLLC-based industrial wireless control are analyzed. Then, the prototype development including protocol stack and hardware architecture design is introduced in detail, and extensive experiments are performed to evaluate the communication latency and control transparency for robotic teleoperation. Experimental results show that the prototype can realize millisecond-level latency with ultra-high reliability, and support wireless teleoperation with similar transparency as wired teleoperation. Finally, challenges and future research issues towards 6G are discussed.

Enhancing High-Temperature Energy Storage Performance of PEI-Based Dielectrics by Incorporating ZIF-67 with a Narrow Bandgap.

Polymer dielectrics are crucial for use in electrostatic capacitors, owing to their high voltage resistance, high energy storage density, and ultrahigh reliability. Furthermore, high-temperature-resistant polymer dielectrics are applied in various emerging fields. Herein, poly(ether imide) (PEI)-based polymer dielectrics prepared by adding a low loading of dimethylimidazolium cobalt (ZIF-67) with a narrow bandgaps are investigated. The results show that the composites exhibit considerably increased Young's modulus, suppressed conductivity loss, and improved breakdown strength compared with pure PEI. Consequently, a stable energy storage performance is realized for ZIF-67/PEI composites. Particularly, at 150 °C, 1 wt % ZIF-67/PEI composite affords an excellent energy storage density of 4.59 J/cm3 with a discharge energy efficiency of 80.6%, exhibiting a considerable increase compared with the values obtained for PEI (2.58 J/cm3 with a discharge energy efficiency of 68.8%). The results of this study reveal a feasible pathway to design polymer dielectrics with the potential for use in capacitive applications in harsh environments.

Robust Resource Control Based on AP Selection in 6G-Enabled IoT Networks.

The diverse application vertices of internet-of-things (IoT) including internet of vehicles (IoV), industrial IoT (IIoT) and internet of drones things (IoDT) involve intelligent communication between the massive number of objects around us. This digital transformation strives for seamless data flow, uninterrupted communication capabilities, low latency and ultra-high reliability. The limited capabilities of fifth generation (5G) technology have given way to sixth generation (6G) wireless technology. This paper presents a dynamic cell-free framework for a 6G-enabled IoT network. A number of access points (APs) are distributed over a given geographical area to serve a large number of user nodes. A pilot-based AP selection (PBAS) algorithm is proposed, which offers robust resource control through AP selection based on pilots. Selecting a subset of APs against all APs for each user node results in improved performance. In this paper, the performance of the proposed transmission model is evaluated for the achieved data rate and spectral efficiency using the proposed algorithm. It is shown that the proposed PBAS algorithm improves the spectral efficiency by 22% at the cell-edge and 1.5% at the cell-center. A comparison of the different combining techniques used at different user locations is also provided, along with the mathematical formulations. Finally, the proposed model is compared with two other transmission models for performance evaluation. It is observed that the spectral efficiency achieved by an edge node with the proposed scheme is 5.3676 bits/s/Hz, compared to 0.756 bits/s/Hz and 1.0501 bits/s/Hz, attained with transmission schemes 1 and 2, respectively.

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol

The Tactile Internet (TI) can be regarded as the next evolution in the world of communication. With its envisioned purpose and potential in shaping up the economy, industry and society, this paradigm aims to bring a new dimension to life by enabling humans to interact with machines remotely and in real-time with haptic and kinesthetic feedback. However, to translate this into reality, Tactile Internet will need to meet the stringent requirements of extremely low latency in conjunction with ultra-high reliability, availability, and security. This poses a challenge on the available communication systems to achieve a round-trip delay within 1 to 10 milliseconds time bound that enables the timely delivery of critical tactile and haptic sensations.
 This paper aims to evaluate the Real-Time Transport Protocol (RTP) through an emulation framework. It integrates containerization using Linux-based Docker Containers with NS-3 Network Simulator to conceptualize a haptic teleoperation system. The framework is then used to test the protocol’s feasibility for delivering texture haptic data between master and slave domains in accordance with the end-to-end delay requirements specified by IEEE 1918.1 standards. The results have shown that the timely provision of haptic data is achievable by obtaining an average round-trip delay of 17.8493 ms from the emulation experiment. As such, the results satisfy the expected IEEE 1918.1 standards constraints for medium-dynamic environment use cases.

Efficient Radio Resource Management for Future 6G Mobile Networks: A Cell-Less Approach

Existing mobile communication systems are unable to support ultra high system capacity and high reliability for the edge users of future 6G systems, which are envisioned to guarantee the desired quality of experience. Recently, cell-less radio access networks (RAN) are exploited to boost the system capacity. Therefore, in this letter we propose a cell-less networking approach with an efficient radio resource optimization mechanism to improve the system capacity of the future 6G networks. The simulation results illustrate that the proposed cell-less NG-RAN design provides significant system capacity improvement over the legacy cellular solutions.

Suitability of SDN and MEC to facilitate digital twin communication over LTE-A

Haptic is the modality that complements traditional multimedia, i.e., audiovisual, to evolve the next wave of innovation at which the Internet data stream can be exchanged to enable remote skills and control applications. This will require ultra-low latency and ultra-high reliability to evolve the mobile experience into the era of Digital Twin and Tactile Internet. While the 5th generation of mobile networks is not yet widely deployed, Long-Term Evolution (LTE-A) latency remains much higher than the 1 ms requirement for the Tactile Internet and therefore the Digital Twin. This work investigates an interesting solution based on the incorporation of Software-defined networking (SDN) and Multi-access Mobile Edge Computing (MEC) technologies in an LTE-A network, to deliver future multimedia applications over the Tactile Internet while overcoming the QoS challenges. Several network scenarios were designed and simulated using Riverbed modeler and the performance was evaluated using several time-related Key Performance Indicators (KPIs) such as throughput, End-2-End (E2E) delay, and jitter. The best scenario possible is clearly the one integrating MEC and SDN approaches, where the overall delay, jitter, and throughput for haptics- attained 2 ms, 0.01 ms, and 1000 packets per second. The results obtained give clear evidence that the integration of, both SDN and MEC, in LTE-A indicates performance improvement, and fulfills the standard requirements in terms of the above KPIs, for realizing a Digital Twin/Tactile Internet-based system.

Millimeter-wave channel modeling in a VANETs using coding techniques.

The Vehicular ad-Hoc Network (VANET) is envisioned to ensure wireless transmission with ultra-high reliability. In the presence of fading and mobility of vehicles, error-free information between Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) requires extensive investigation. The current literature lacks in designing an ultra-reliable comprehensive tractable model for VANET using millimeter wave. Ultra-reliable communication is needed to support autonomous vehicular communication. This article aims to provide a comprehensive tractable model for VANET over millimeter waves using Space-Time-Block-Coding (STBC) concatenated with Reed Solomon (RS) coding. The designed model provides the fastest way of designing and analyzing VANET networks on 60 GHz. By using the derived BER expressions and Reed Solomon coded doppler expression ultra-reliable vehicular networks can be build meeting the demands of massive growing volume of traffic. The performance of the model is compared with previous BER computational techniques and existing VANET communication systems, i.e., IEEE 802.11bd and 3rd generation partnership project vehicle to everything (3GPP V2X). The findings show that our proposed approach outperforms IEEE 802.11bd and the results are comparable with V2X NR. Packet Error Rate (PER), Packet Reception Ratio (PRR) and throughput are used as performance metrics. We have also evaluated the model on higher velocities of vehicles. Further, the simulation and numerical findings show that the proposed system surpass the existing BER results comprising of various modulation and coding techniques. The simulation results are verified by the numerical results there-by, showing the accuracy of our derived expressions.

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications

Developing radio access technologies that enable reliable and low-latency vehicular communications have become of the utmost importance with the rise of interest in autonomous vehicles. The Third Generation Partnership Project (3GPP) has developed Vehicle to Everything (V2X) specifications based on the 5G New Radio Air Interface (NR-V2X) to support connected and automated driving use cases, with strict requirements to fulfill the constantly evolving vehicular applications, communication, and service demands of connected vehicles, such as ultra-low latency and ultra-high reliability. This paper presents an analytical model for evaluating the performance of NR-V2X communications, with particular reference to the sensing-based semi-persistent scheduling operation defined in the NR-V2X Mode 2, in comparison with legacy sidelink V2X over LTE, specified as LTE-V2X Mode 4. We consider a vehicle platooning scenario and evaluate the impact of multiple access interference on the packet success probability, by varying the available resources, the number of interfering vehicles, and their relative positions. The average packet success probability is determined analytically for LTE-V2X and NR-V2X, taking into account the different physical layer specifications, and the Moment Matching Approximation (MMA) is used to approximate the statistics of the signal-to-interference-plus-noise ratio (SINR) under the assumption of a Nakagami-lognormal composite channel model. The analytical approximation is validated against extensive Matlab simulations that a show good accuracy. The results confirm a boost in performance with NR-V2X against LTE-V2X, particularly for high inter-vehicle distance and a large number of vehicles, providing a concise yet accurate modeling rationale for planning and adaptation of the configuration and parameter setup of vehicle platoons, without having to resort to extensive computer simulation or experimental measurements.

Data-Driven Spectrum Partition for Multiplexing URLLC and eMBB

Multiplexing ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) are critical in the next generation mobile network. URLLC requires ultra-high reliability and extremely low latency, whereas eMBB demands high data rates. Thus, the coexistence system of URLLC and eMBB faces the challenge of sharing the spectrum efficiently and effectively. In this study, we comprehensively investigate the state of the art spectrum partition methods in combined URLLC and eMBB services. We formulate a joint optimization problem for maximizing the eMBB throughput and guaranteeing the URLLC performance. For the eMBB and URLLC multiplexing system, a full separative spectrum partition scheme based on data-driven genetic algorithm-based spectrum partition (DDGSP) is proposed. Our simulation results demonstrate that the proposed DDGSP can make the URLLC and eMBB coexistence system outperform the state-of-the-art methods in terms of the error rate and computational efficiency.

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.