Search

With the fourth revolution of healthcare, i.e., Healthcare 4.0, collaborative robotics is spilling out from traditional manufacturing and will blend into human living or working environments to deliver care services, especially telehealthcare. Because of the frequent and seamless interaction between robots and care recipients, it poses several challenges that require careful consideration: 1) the ability of the human to collaborate with the robots in a natural manner; and 2) the safety of the human collaborating with the robot. In this regard, we have proposed a proximity sensing solution based on the self-capacitive technology to provide an extended sense of touch for collaborative robots, allowing approach and contact measurement to enhance safe and natural human-robot collaboration. The modular design of our solution enables it to scale up to form a large-area sensing system. The sensing solution is proposed to work in two operation modes: the interaction mode and the safety mode. In the interaction mode, utilizing the ability of the sensor to localize the point of action, gesture command is used for robot manipulation. In the safety mode, the sensor enables the robot to actively avoid obstacles., QC 20220110

Wireless communication is evolving to support critical control in automation systems. The fifth-generation (5G) mobile network air interface New Radio adopts a scalable numerology and mini-slot transmission for short packets that make it potentially suitable for critical control systems. The reliable minimum cycle time is an important indicator for industrial communication techniques but has not yet been investigated within 5G. To address such a question, this article considers 5G-based industrial networks and uses the delay optimization based on data-driven channel characterization (CCDO) approach to propose a method to evaluate the reliable minimum cycle time of 5G. Numerical results in three representative industrial environments indicate that following the CCDO approach, 5G-based industrial networks can achieve, in real-world scenario, millisecond-level minimum cycle time to support several hundred nodes with reliability higher than 99.9999%., QC 20210831

Turbo codes are a family of near Shannon limit error correction coding schemes that usually are adopted for wireless data transmission. To reduce the power dissipation of a long-term evolution (LTE) advanced turbo decoder, in this paper, we propose a reverse calculation based low memory turbo decoder architecture by partitioning the trellis diagram and simplifying the max* operator. The designed forward state metrics calculation architecture is merged with two classical decoding schemes. Through field programmable gate array (FPGA) hardware implementation, the state metrics cache (SMC) capacity is reduced by 65%, the power dissipation of the reverse calculation architecture is significantly reduced for all tested clock frequencies, and the decoding performance is not affected as compared with classical decoding schemes. The proposed reverse calculation architecture is an effective technique to achieve better decoding performance for power-constrained applications., QC 20210624

Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance., Funding: Swedish Innovation Agency, VinnovaVinnova

Wireless communication is gaining popularity in the industry for its simple deployment, mobility, and low cost. Ultralow latency and high reliability requirements of mission-critical industrial applications are highly demanding for wireless communication, and the indoor industrial environment is hostile to wireless communication due to the richness of reflection and obstacles. Assessing the effect of the industrial environment on the reliability and latency of wireless communication is a crucial task, yet it is challenging to accurately model the wireless channel in various industrial sites. In this article, based on the comprehensive channel measurement results from the National Institute of Standards and Technology at 2.245 and 5.4 GHz, we quantify the reliability degradation of wireless communication in multipath fading channels. A delay optimization based on the channel characterization is then proposed to minimize packet transmission times of a cyclic prefix orthogonal frequency division multiplexing system under a reliability constraint at the physical layer. When the transmission bandwidth is abundant and the payload is short, the minimum transmission time is found to be restricted by the optimal cyclic prefix duration, which is correlated with the communication distance. Results further reveal that using relays may, in some cases, reduce end-to-end latency in industrial sites, as achievable minimum transmission time significantly decreases at short communication ranges., QC 20200717

Powered by the technologies that have originated from manufacturing, the fourth revolution of healthcare technologies is happening (Healthcare 4.0). As an example of such revolution, new generation homecare robotic systems (HRS) based on the cyber-physical systems (CPS) with higher speed and more intelligent execution are emerging. In this article, the new visions and features of the CPS-based HRS are proposed. The latest progress in related enabling technologies is reviewed, including artificial intelligence, sensing fundamentals, materials and machines, cloud computing and communication, as well as motion capture and mapping. Finally, the future perspectives of the CPS-based HRS and the technical challenges faced in each technical area are discussed.

Powered by the technologies that have originated from manufacturing, the fourth revolution of healthcare technologies is happening (Healthcare 4.0). As an example of such revolution, new generation homecare robotic systems (HRS) based on the cyber-physical systems (CPS) with higher speed and more intelligent execution are emerging. In this article, the new visions and features of the CPS-based HRS are proposed. The latest progress in related enabling technologies is reviewed, including artificial intelligence, sensing fundamentals, materials and machines, cloud computing and communication, as well as motion capture and mapping. Finally, the future perspectives of the CPS-based HRS and the technical challenges faced in each technical area are discussed.

QC 20200316

Trealize the Industry 4.0 vision and enable mobile connectivity and flexible deployment in harsh industrial environments, wireless communication is essential. But before wireless communications technology can be widely deployed for critical control applications, first it must be assessed, and that requires a comprehensive characterization of the wireless channel. This can be done by analyzing large amounts of wireless data collected from different industrial environments. In this article, we discuss the possibilities offered by a recently published industrial wireless data set. This data set is more exhaustive than measurements previously reported. We show two cases of how those data have been applied to improve latency performance and to investigate the feasibility of physical-layer security techniques for wireless communication in industrial environments., QC 20190426

Ultra-high reliable and low-latency communication (URLLC)is envisaged to support emerging applications with strict latency and reliability requirements. Critical industrial control is among the most important URLLC applications where the stringent requirements make the deployment of wireless networks critical, especially as far as latency is concerned. Since the amount of data exchanged in critical industrial communications is generally small, an effective way to reduce the latency is to minimize the packet's synchronization overhead, starting from the physical layer (PHY). This paper proposes to use a short one-symbol PHY preamble for critical wireless industrial communications, reducing significantly the transmission latency with respect to other wireless standards. Dedicated packet detection and synchronization algorithms are discussed, analyzed, and tuned to ensure that the required reliability level is achieved with such extremely short preamble. Theoretical analysis, simulations, and experiments show that detection error rates smaller than 10(-6) can be achieved with the proposed preamble while minimizing the latencies., QC 20190410

Wireless communication for industrial applications of fers multiple advantages over traditional wired communicat ion, such a s reduced installation and maintenance costs, increased flexibility, and better suitability for harsh conditions and mobile environments. However, many industrial applications feature high-performance requirements for latency and reliability, challenges which are difficult are to meet over the wireless channel. Currently available wireless technologies struggle to achieve these requirements, leaving a gap between industry demands and state-of-the-art performance. To close this gap, traditional solutions that rely on general-purpose chipsets could be replaced with dedicated solutions for industrial applications. In this article, we discuss the feasibility of designing an industrial wireless solution based on software-defined radio (SDR), the obtained results, and the role of softwarization in the future of industrial communication., QC 20200427

Wireless industrial cyber-physical systems are increasingly popular in critical manufacturing processes. These kinds of systems, besides high performance, require strong security and are constrained by low computational capabilities. Physical layer authentication (PHY-AUC) is a promising solution to meet these requirements. However, the existing threshold-based PHY-AUC methods only perform ideally in stationary scenarios. To improve the performance of PHY-AUC in mobile scenarios, this article proposes a novel threshold-free PHY-AUC method based on machine learning (ML), which replaces the traditional threshold-based decision-making with more adaptive classification based on ML. This article adopts channel matrices estimated by the wireless nodes as the authentication input and investigates the optimal dimension of the channel matrices to further improve the authentication accuracy without increasing too much computational burden. Extensive simulations are conducted based on a real industrial dataset, with the aim of tuning the authentication performance, then further field validations are performed in an industrial factory. The results from both the simulations and validations show that the proposed method significantly improves the authentication accuracy., QC 20200116

As one of the key enabling technologies of emerging smart societies and industries (i.e., industry 4.0), the Internet of Things (IoT) has evolved significantly in both technologies and applications. It is estimated that more than 25 billion devices will be connected by wireless IoT networks by 2020. In addition to ubiquitous connectivity, many envisioned applications of IoT, such as industrial automation, vehicle-to-everything (V2X) networks, smart grids, and remote surgery, will have stringent transmission latency and reliability requirements, which may not be supported by existing systems. Thus, there is an urgent need for rethinking the entire communication protocol stack for wireless IoT networks. In this tutorial paper, we review the various application scenarios, fundamental performance limits, and potential technical solutions for high-reliability and lowlatency (HRLL) wireless IoT networks. We discuss physical, MAC (medium access control), and network layers of wireless IoT networks, which all have significant impacts on latency and reliability. For the physical layer, we discuss the fundamental information-theoretic limits for HRLL communications, and then we also introduce a frame structure and preamble design for HRLL communications. Then practical channel codes with finite block length are reviewed. For the MAC layer, we first discuss optimized spectrum and power resource management schemes and then recently proposed grant-free schemes are discussed. For the network layer, we discuss the optimized network structure (traffic dispersion and network densification), the optimal traffic allocation schemes and network coding schemes to minimize latency., QC 20200103

In Industrial Internet of Things (IIoTs), data generated during manufacturing are collected by sensors and need be processed timely. The direction of data transmissions from sensors to processing centers (fog nodes) is often called uplink transmission. In this paper, the cases with single and multiple distributed fog nodes, which are also referred to as centralized and distributed models, are studied. Two distributed schemes based on batched sparse (BATS) codes are proposed separately for the uplink of these two models. The expected rank and the recovery probability of the information from sensors at fog node(s) are derived. Comparison results show that by using the proposed BATS-based schemes, improved transmission reliability can be achieved compared to the XOR-based network coding (NC) scheme., QC 20190910

QC 20200103

Industry 4.0 is the emerging trend of the industrial automation. Millimeter-wave (mmWave) communication is a prominent technology for wireless networks to support the Industry 4.0 requirements. The availability of tractable accurate interference models would greatly facilitate performance analysis and protocol development for these networks. In this paper, we investigate the accuracy of an interference model that assumes impenetrable obstacles and neglects the sidelobes. We quantify the error of such a model in terms of statistical distribution of the signal to noise plus interference ratio and of the user rate for outdoor mmWave networks under different carrier frequencies and antenna array settings. The results show that assuming impenetrable obstacle comes at almost no accuracy penalty, and the accuracy of neglecting antenna sidelobes can be guaranteed with sufficiently large number of antenna elements. The comprehensive discussions of this paper provide useful insights for the performance analysis and protocol design of outdoor mmWave networks., QC 20180319

Wireless networks are undergoing a transition from connecting people to connecting things, which will allow human interaction with the physical world in a real-time fashion, for example, Tactile Internet, industrial automation, self-driving vehicles, and remote surgery. Therefore, future wireless networks need to support real-time control since it is the essential function enabling such emerging applications. In this article, some fundamental design capabilities needed to realize real-time control in future wireless networks are discussed, with primary emphasis given to communication-control because both communication and control systems have strong dynamics and interdependencies, and they tightly interact with each other. A case study is provided to demonstrate the necessity of such co-design., QC 20190412

Proximity-based service (ProSe) provides direct communications among smart sensor nodes in proximity which aims at reserving resource consumption and alleviating the load in base stations, which is a promising solution for smart sensor systems that possess limited computing and energy resources. During the ProSe direct communications, most of the prior art security methods are usually provided by the ProSe function and are based on complex cryptography. However, despite the computing complexity, it is difficult for cryptographic methods to detect clone attack which is a common kind of attack in sensor systems. Clone nodes feature different physical positions but claim colliding IDs with captured nodes. Thus, clone nodes can be detected by spatial differences, in particular, by the surveillance of physical layer channel state information (CSI). However, CSI is not absolute static due to the random noise in wireless propagation environment. Accordingly, the detection accuracy varies with the stability of CSI. To address this challenge, we take the first attempt to introduce physical layer reputation and then elaborate the physical layer reputation based clone detection protocol to detect clone attack in multiple scenarios. The proposed protocol significantly improves the detection rate and false alarm rate and it is validated both by simulations and realizations., QC 20190301

Proximity service (ProSe), using the geographic location and device information by considering the proximity of mobile devices, enriches the services we use to interact with people and things around us. ProSe has been used in mobile social networks in proximity and also in smart home and building automation (Google Home). To enable ProSe in smart home, reliable and stable network protocols and communication infrastructures are needed. Thread is a new wireless protocol aiming at smart home and building automation (BA), which supports mesh networks and native Internet protocol connectivity. The latency of Thread should be carefully studied when used in user-friendly and safety-critical ProSe in smart home and BA. In this paper, a system level model of latency in the Thread mesh network is presented. The accumulated latency consists of different kinds of delay from the application layer to the physical layer. A Markov chain model is used to derive the probability distribution of the medium access control service time. The system level model is experimentally validated in a multi-hop Thread mesh network. The outcomes show that the system model results match well with the experimental results. Finally, based on an analytical model, a software tool is developed to estimate the latency of the Thread mesh network, providing developers more network information to develop user-friendly and safety-critical ProSe in smart home and BA., QC 20190301

Internet of Things (IoT) has been found pervasive use cases and become a driving force to constitute a digital society. The ultimate goal of IoT is data and the intelligence generated from data. With the progress in public cloud computing technologies, more and more data can be stored, processed and analyzed in cloud to release the power of IoT. However, due to the heterogeneity of hardware and communication protocols in the IoT world, the interoperability and compatibility among different link layer protocols, sub-systems, and back-end services have become a significant challenge to IoT practices. This challenge cannot be addressed by public cloud suppliers since their efforts are mainly put into software and platform services but can hardly be extended to end devices. In this paper, we propose a data-centric IoT framework that incorporates three promising protocols with fundamental security schemes, i.e., WiFi, Thread, and LoRaWAN, to cater to massive IoT and broadband IoT use cases in local, personal, and wide area networks. By taking advantages of the Azure cloud infrastructure, the framework features a unified device management model and data model to conquer the interoperability challenge. We also provide implementation and a case study to validate the framework for practical applications., Funding agencies: Swedish Environmental Protection Agency; Norrkoping Fund for Research and Development, Sweden

A booming global economy and demand for customized products has led to a buyers’ market outweighing a sellers’ market in the manufacturing industry. This means that a deeper conversion towards manufacturing structures to handle the increasing production complexity should be studied. With an increased adoption of the Internet of Things (IoT) and Cyber-Physical Systems (CPS), realization of smart factory will become possible. The smart factory can provide a solution for handling the complexity through the establishment of intelligent products and production processes.

This paper considers an Industrial Internet of Thing (IIoT) system with a source monitoring a dynamic process with randomly generated status updates. The status updates are sent to an designated destination in a real-time manner over an unreliable link. The source is subject to a practical constraint of limited average transmission power. Thus, the system should carefully schedule when to transmit a fresh status update or retransmit the stale one. To characterize the performance of timely status update, we adopt a recent concept, Age of Information (AoI), as the performance metric. We aim to minimize the long-term average AoI under the limited average transmission power at the source, by formulating a constrained Markov Decision Process (CMDP) problem. To address the formulated CMDP, we recast it into an unconstrained Markov Decision Process (MDP) through Lagrangian relaxation. We prove the existence of optimal stationary policy of the original CMDP, which is a randomized mixture of two deterministic stationary policies of the unconstrained MDP. We also explore the characteristics of the problem to reduce the action space of each state to significantly reduce the computation complexity. We further prove the threshold structure of the optimal deterministic policy for the unconstrained MDP. Simulation results show the proposed optimal policy achieves lower average AoI compared with random policy, especially when the system suffers from stricter resource constraint. Besides, the influence of status generation probability and transmission failure rate on optimal policy and the resultant average AoI as well as the impact of average transmission power on the minimal average AoI are unveiled.