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5G-Enabled Autonomous Driving Demonstration with a V2X Scenario-in-the-Loop Approach
(Sensors (Basel), 2020) Szalay, Z.; Ficzere, D.; Tihanyi, V.; Magyar, F.; Soós, G.; Varga, P.
Autonomous vehicles are at the forefront of interest due to the expectations of changing transportation for the better. In order to make better decisions on the road, vehicles use information from various sources: their own sensors, messages arriving from surrounding vehicles and objects, as well as from centralized entities-including their own Digital Twin. Certain decisions require the information to arrive with low latency and some of this information (such as video) requires broadband communication. Furthermore, the vehicles can populate an area, so they can represent mass communication endpoints that still need low latency and massive broadband. The mobility of the vehicles obviously requires the complete coverage of the roads with reliable wireless communication technologies fulfilling the previously mentioned needs. The fifth generation of cellular mobile technologies, 5G, addresses these requirements. The current paper presents real-life scenarios-on the M86 highway and the ZalaZONE proving ground in Hungary-for the demonstration of vehicular communication with 5G support, where the cars exchange sensor and control information with each other, their environment, and their Digital Twins. The demonstrations were carried out through the Scenario-in-the-Loop (SciL) methodology, where some of the actionable triggers were not physically present around the vehicles, but sensed or simulated around their Digital Twin. The measurements around the demonstrations aim to reveal the feasibility of the 5G Non-Standalone Architecture for certain communication scenarios, and they mainly aim to reveal the current latency and throughput limitations under real-life conditions.
A 5G-powered robot-assisted teleultrasound diagnostic system in an intensive care unit
(Crit Care, 2021) Duan, S.; Liu, L.; Chen, Y.; Yang, L.; Zhang, Y.; Wang, S.; Hao, L.; Zhang, L.
"BACKGROUND: Teleultrasound provides an effective solution to problems that arise from limited medical resources, a lack of local expertise, and scenarios where the risk of infection is high. This study aims to explore the feasibility of the application of a 5G-powered robot-assisted teleultrasound diagnostic system in an intensive care unit. METHODS: In this study, the robot-assisted teleultrasound diagnostic system MGIUS-R3 was used. Using 5G network technology, the doctor manipulates the robotic arm to perform teleultrasound examination. The doctor can adjust parameters via the teleultrasound control panel, and real-time transmission of audio, video and ultrasound images can facilitate simultaneous communication between both parties. All patients underwent robot-assisted teleultrasound examination and bedside ultrasound examination of the liver, gallbladder, pancreas, spleen, kidney, as well as assessment for pleural effusion and abdominal effusion. We evaluated the feasibility of the application of the robot-assisted teleultrasound diagnosis system in the intensive care unit in terms of consultation duration, image quality, and safety. We also compared diagnostic consistency and differences. RESULTS: Apart from one patient who was excluded due to severe intestinal gas interference and poor image quality, a total of 32 patients were included in this study. Every patient completed all relevant examinations. Among them, 20 patients were male"," 12 were female. The average age of the patients was 61 � 20 years. The average duration of teleultrasound diagnosis was 17 � 7 min. Of the 32 patients, 26 had positive results, 6 had negative results, and 5 had inconsistent diagnoses. The overall diagnostic results were basically the same, and there were no differences in diagnostic levels between the two. The overall average image quality score was 4.73 points, which represented a high-quality image. After robot-assisted teleultrasound examination, no significant changes were observed in the vital signs of patients as compared to before examination, and no examination-related complications were found. CONCLUSION: The 5G-powered robot-assisted teleultrasound diagnostic system was associated with the benefits of clear images, simple operation, relatively high levels of consistency in terms of diagnostic results, higher levels of safety, and has considerable application value in the intensive care unit."
Deep Learning-Based Cell-Level and Beam-Level Mobility Management System
(Sensors (Basel), 2020) Klus, R.; Klus, L.; Solomitckii, D.; Talvitie, J.; Valkama, M.
The deployment with beamforming-capable base stations in 5G New Radio (NR) requires an efficient mobility management system to reliably operate with minimum effort and interruption. In this work, we propose two artificial neural network models to optimize the cell-level and beam-level mobility management. Both models consist of convolutional, as well as dense, layer blocks. Based on current and past received power measurements, as well as positioning information, they choose the optimum serving cell and serving beam, respectively. The obtained results show that the proposed cell-level mobility model is able to sustain a strong serving cell and reduce the number of handovers by up to 94.4% compared to the benchmark solution when the uncertainty (representing shadowing, interference, etc.) is introduced to the received signal strength measurements. The proposed beam-level mobility management model is able to proactively choose and sustain the strongest serving beam, even when high uncertainty is introduced to the measurements.
Design and Experimental Analysis of Multiband Frequency Reconfigurable Antenna for 5G and Sub-6 GHz Wireless Communication
(Micromachines (Basel), 2020) Dildar, H.; Althobiani, F.; Ahmad, I.; Khan, W. U. R.; Ullah, S.; Mufti, N.; Muhammad, F.; Irfan, M.; Glowacz, A.
A low-profile frequency reconfigurable monopole antenna operating in the microwave frequency band is presented in this paper. The proposed structure is printed on Flame Retardant-4 (FR-4) substrate having relative permittivity of 4.3 and tangent loss of 0.025. Four pin diode switches are inserted between radiating patches for switching the various operating modes of an antenna. The proposed antenna operates in five modes, covering nine different bands by operating at single bands of 5 and 3.5 GHz in Mode 1 and Mode 2, dual bands (i.e., 2.6 and 6.5 GHz, 2.1 and 5.6 GHz) in Mode 3 and 4 and triple bands in Mode 5 (i.e., 1.8, 4.8, and 6.4 GHz). The Voltage Standing Waves Ratio (VSWR) of the presented antenna is less than 1.5 for all the operating bands. The efficiency of the designed antenna is 84 % and gain ranges from 1.2 to 3.6 dBi, respectively, at corresponding resonant frequencies. The achieve bandwidths at respective frequencies ranges from 10.5 to 28%. The proposed structure is modeled in Computer Simulation Technology microwave studio (CST MWS) and the simulated results are experimentally validated. Due to its reasonably small size and support for multiple wireless standards, the proposed antenna can be used in modern handheld fifth generation (5G) devices as well as Internet of Things (IoT) enabled systems in smart cities.
Health Council of the Netherlands and evaluation of the fifth generation, 5G, for wireless communication and cancer risks
(World J Clin Oncol, 2021) Hardell, L.
Currently the fifth generation, 5G, for wireless communication is about to be rolled out worldwide. Many persons are concerned about potential health risks from radiofrequency radiation. In September 2017, a letter was sent to the European Union asking for a moratorium on the deployment until scientific evaluation has been made on potential health risks (http://www.5Gappeal.eu). This appeal has had little success. The Health Council of the Netherlands released on September 2, 2020 their evaluation on 5G and health. It was largely based on a World Health Organization draft and report by the Swedish Radiation Safety Authority, both criticized for not being impartial. The guidelines by the International Commission on Non-Ionizing Radiation Protection were recommended to be used, although they have been considered to be insufficient to protect against health hazards (http://www.emfscientist.org). The Health Council Committee recommended not to use the 26 GHz frequency band until health risks have been studied. For lower frequencies, the International Commission on Non-Ionizing Radiation Protection guidelines were recommended. The conclusion that there is no reason to stop the use of lower frequencies for 5G is not justified by current evidence on cancer risks as commented in this article. A moratorium is urgently needed on the implementation of 5G for wireless communication.
The impact of 5G on the evolution of intelligent automation and industry digitization
(J Ambient Intell Humaniz Comput, 2021) Attaran, M.
"The mobile industry is developing and preparing to deploy the fifth-generation (5G) networks. The evolving 5G networks are becoming more readily available as a significant driver of the growth of IoT and other intelligent automation applications. 5G's lightning-fast connection and low-latency are needed for advances in intelligent automation-the Internet of Things (IoT), Artificial Intelligence (AI), driverless cars, digital reality, blockchain, and future breakthroughs we haven't even thought of yet. The advent of 5G is more than just a generational step"," it opens a new world of possibilities for every tech industry. The purpose of this paper is to do a literature review and explore how 5G can enable or streamline intelligent automation in different industries. This paper reviews the evolution and development of various generations of mobile wireless technology underscores the importance of 5G revolutionary networks, reviews its key enabling technologies, examines its trends and challenges, explores its applications in different manufacturing industries, and highlights its role in shaping the age of unlimited connectivity, intelligent automation, and industry digitization."
Implementation of a Multi-Gbit/s and GFDM-based Optical-Wireless 5G Network
(Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 2018) Borges, R. M.; Marins, T. R. R.; Cunha, M. S. B.; Spadoti, D. H.; Mendes, L. L.; Cerqueira S. Jr, Arismar
"We report the implementation of an optical-wireless 5G network based on generalized frequency division multiplexing (GFDM) and multi-Gbit/s communication. Dual-drive Mach-Zehnder modulator was employed, enabling simultaneously RF signals transport using two 5G candidate bands, namely: 26 GHz band for providing a femtocell with 2 Gbit/s throughput"," 700 MHz band for enabling rural access applying a supercell. A vector signal generator provides the broadband 26 GHz signal. The Brazilian GFDM-based 5G transceiver generates the lower-frequency signal, with the advantage of low out-of-band emission. An experimental digital performance analysis illustrates the suitability of the proposed solution to address 5G requirements."
An Overview of Machine Learning and 5G for People with Disabilities
(Sensors (Basel), 2021) Domingo, M. C.
Currently, over a billion people, including children (or about 15% of the world's population), are estimated to be living with disability, and this figure is going to increase to beyond two billion by 2050. People with disabilities generally experience poorer levels of health, fewer achievements in education, fewer economic opportunities, and higher rates of poverty. Artificial intelligence and 5G can make major contributions towards the assistance of people with disabilities, so they can achieve a good quality of life. In this paper, an overview of machine learning and 5G for people with disabilities is provided. For this purpose, the proposed 5G network slicing architecture for disabled people is introduced. Different application scenarios and their main benefits are considered to illustrate the interaction of machine learning and 5G. Critical challenges have been identified and addressed.
Public Perception of the Fifth Generation of Cellular Networks (5G) on Social Media
(Front Big Data, 2021) Dashtipour, K.; Taylor, W.; Ansari, S.; Gogate, M.; Zahid, A.; Sambo, Y.; Hussain, A.; Abbasi, Q. H.; Imran, M. A.
With the advancement of social media networks, there are lots of unlabeled reviews available online, therefore it is necessarily to develop automatic tools to classify these types of reviews. To utilize these reviews for user perception, there is a need for automated tools that can process online user data. In this paper, a sentiment analysis framework has been proposed to identify people's perception towards mobile networks. The proposed framework consists of three basic steps: preprocessing, feature selection, and applying different machine learning algorithms. The performance of the framework has taken into account different feature combinations. The simulation results show that the best performance is by integrating unigram, bigram, and trigram features.
Supply chain security evaluation model and index system based on a 5G information system
(Neural Comput Appl, 2021) Zhao, J.; Li, Y.
"Currently, the supply chain management model has been widely adopted worldwide. Internationally renowned companies such as IBM and Walmart have made significant achievements in supply chain management and have played a greater role in promoting the growth of their interests. However, while they are enjoying their own interests, they are also facing various risks in the supply chain. From the perspective of systems engineering, this paper uses complex network theory as a research tool to study supply chain networks and systematically study the important issues of supply chain network risks. This paper analyzes the new characteristics of the relationship between enterprises and suppliers in the supply chain and which indicators should be selected as the basis for evaluating suppliers from the perspective of cooperation and development, which more comprehensively reflects the characteristics of the new enterprise-supplier relationship in the supply chain environment. This highlights the evaluation of the supplier's cooperation ability and development ability. Aiming at the problem of supply chain network system identification and integrated evaluation, a supply chain security evaluation model and index system research framework model are proposed, and the intercompany business risk and supply chain in supply chain network evaluation are introduced. As a model for evaluating transition parameters, the study of supply chain risk propagation introduces the theory of dynamic propagation in complex networks, the law of evolution, and the supplier's dynamic supply chain risk model. The experimental results of this paper show that when the global reputation value is 0.5 and the local reputation value is 0.8 and 0.7, the trust degree changes with the change of the confidence factor"," when the value of the confidence factor decreases, the degree of trust converges more and more to the global reputation and vice versa. It can be seen that this model has high feasibility."
Target Recognition of Industrial Robots Using Machine Vision in 5G Environment
(Front Neurorobot, 2021) Jin, Z.; Liu, L.; Gong, D.; Li, L.
"The purpose is to solve the problems of large positioning errors, low recognition speed, and low object recognition accuracy in industrial robot detection in a 5G environment. The convolutional neural network (CNN) model in the deep learning (DL) algorithm is adopted for image convolution, pooling, and target classification, optimizing the industrial robot visual recognition system in the improved method. With the bottled objects as the targets, the improved Fast-RCNN target detection model's algorithm is verified"," with the small-size bottled objects in a complex environment as the targets, the improved VGG-16 classification network on the Hyper-Column scheme is verified. Finally, the algorithm constructed by the simulation analysis is compared with other advanced CNN algorithms. The results show that both the Fast RCN algorithm and the improved VGG-16 classification network based on the Hyper-Column scheme can position and recognize the targets with a recognition accuracy rate of 82.34%, significantly better than other advanced neural network algorithms. Therefore, the improved VGG-16 classification network based on the Hyper-Column scheme has good accuracy and effectiveness for target recognition and positioning, providing an experimental reference for industrial robots' application and development."
The Use of 3D Printing Technology for Manufacturing Metal Antennas in the 5G/IoT Context
(Sensors (Basel), 2021) Helena, D.; Ramos, A.; Varum, T.; Matos, J. N.
With the rise of 5G, Internet of Things (IoT), and networks operating in the mmWave frequencies, a huge growth of connected sensors will be a reality, and high gain antennas will be desired to compensate for the propagation issues, and with low cost, characteristics inherent to metallic radiating structures. 3D printing technology is a possible solution in this way, as it can print an object with high precision at a reduced cost. This paper presents different methods to fabricate typical metal antennas using 3D printing technology. These techniques were applied as an example to pyramidal horn antennas designed for a central frequency of 28 GHz. Two techniques were used to metallize a structure that was printed with polylactic acid (PLA), one with copper tape and other with a conductive spray-paint. A third method consists of printing an antenna completely using a conductive filament. All prototypes combine good results with low production cost. The antenna printed with the conductive filament achieved a better gain than the other structures and showed a larger bandwidth. The analysis recognizes the vast potential of these 3D-printed structures for IoT applications, as an alternative to producing conventional commercial antennas.

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