5G Technology Research Articles

Measuring the radiation hardness of terahertz devices for space applications

AbstractThe application of terahertz technology in space is frontier for the development of 6G technologies. Terahertz transceiver devices based on gallium arsenide Schottky barrier diodes (GaAs SBDs) have the characteristics of small size, light weight and low power consumption, making them suitable for application on spacecraft. However, there is currently a lack of experimental assessments on their space adaptability. Here, we study the radiation hardness of terahertz devices to determine their adaptability in complex space environments. We exposed GaAs SBDs and terahertz multipliers as typical terahertz devices to gamma rays and protons. The experimental results showed that the terahertz devices exhibited good tolerance to protons, but prolonged exposure to gamma rays could significantly increase the leakage current of the GaAs SBDs and alter its C-V characteristics, leading to the failure of the terahertz multiplier. Nevertheless, the terahertz devices maintained a good level of radiation hardness, making them highly suitable for use in Low Earth Orbit (LEO) satellites. The comparison between the results of proton and gamma ray tests indicated that the terahertz devices exhibited high inherent radiation hardness against displacement damage but were more sensitive to ionization damage, requiring higher shielding requirements.

Solving blockage problem of the 5G mmWaves Wireless Communications using Jellyfish Search Optimizer

The 5G technologies are aimed to support a variety of vertically connected applications with heterogeneous devices and machines with significant improvements in terms of higher quality of service, increased network capacity and improved system throughput. However, 5G systems still face a number of challenges mentioned by researchers and organizations, and among these challenges, we highlight that millimeter wave links are very susceptible to blockage. If the line-of-sight communication path is blocked, reflexive path communication can help maintain communication. The shortest route was to take an alternate route when the first route was blocked. Among the proposed solutions to the blocking problem is an algorithm to distribute the power between different mmWave communication paths in order to overcome the masses of links under randomly distributed obstacles. The problem has been resolved with an exact method. In this article, we have optimized all the results of this exact method by applying a powerful metaheuristic technique called jellyfish search optimizer to maximize the overall capacity of the path between two nodes. The results showed that our approach procures an improvements exceed 100% over the results of the exact method.

The Impact of 5G and Data Science on Digital Marketing: An Analytical Review and Research Agenda

Objective: This study aims to evaluate the impact of 5G technology across various sectors, focusing on its applications in smart cities, digital marketing, and industrial use cases, with the goal of understanding how 5G enhances connectivity, efficiency, and user experience. Theoretical Framework: The research is based on theories of digital transformation and emerging technologies, highlighting the role of artificial intelligence and advanced connectivity in the evolution of urban, commercial, and industrial systems. Method: A systematic literature review (SLR) was conducted, analyzing studies published from 1996 to 2023. The research utilized social network analysis, content analysis, and business case analysis to gain a comprehensive understanding of the effects of 5G. Results and Discussion: The findings reveal that 5G technology significantly improves connectivity, operational efficiency, and user experience, facilitating real-time communication and advanced resource management. The discussion contextualizes these findings within the theoretical framework, highlighting the benefits and challenges of 5G. Implications of the Research: The study emphasizes implications for digital infrastructure and services, suggesting the need for strategic investments and policies to fully leverage the potential of 5G. Originality/Value: This study provides an integrated and novel view of 5G, distinguishing itself from previous research by offering a holistic perspective on advanced applications.

A Survey on Emerging Trends and Applications of 5G and 6G to Healthcare Environments

A delay, interruption, or failure in the wireless connection has a significant impact on the performance of wirelessly connected medical equipment. Researchers presented the fastest technological innovations and industrial changes to address these problems and improve the applications of information and communication technology. The development of the 6G communication infrastructure was greatly aided by the use of Block-chain technology, artificial intelligence (AI), virtual reality (VR), and the Internet of Things (IoT). In this paper, we comprehensively discuss 6G technologies enhancement, its fundamental architecture, difficulties, and other issues associated with it. In addition, the outcomes of our research help make 6G technology more applicable to real-world medical environments. The most important thing that this study has contributed is an explanation of the path that future research will take and the current state of the art. This study might serve as a jumping-off point for future researchers in the academic world who are interested in investigating the possibilities of 6G technological developments.

Quantum-assisted federated intelligent diagnosis algorithm with variational training supported by 5G networks

In the realm of intelligent healthcare, there is a growing ambition to reshape medical services through the integration of artificial intelligence (AI). However, conventional machine learning faces inherent challenges such as privacy issues, delayed updates, and protracted training times, particularly due to the hesitance of medical institutions to directly share sensitive data, with possible noises. In response to these concerns, a Quantum-Assisted Federated Intelligent Diagnosis Algorithm (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}-QuAFIDA) is proposed, applied into real medical data. Leveraging the capabilities of the 5G mobile network, this approach works the connection between Internet of Medical Things (IoMT) devices through the 5G, synchronizing training and updating the server model without disrupting their real-world applications. In our quest to safeguard patient data and enhance training efficiency, our study employs an innovative heuristic approach marked by a nested loop structure. Specifically, the inner loop is dedicated to training the beta-variational quantum eigensolver (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}-VQE) to approximate the expectation values of the proposed algorithm; the outer loop trains the β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}-QuAFIDA to reduce the relative entropy towards the target. This approach involves a balance between privacy considerations and the urgency of training. Results demonstrate that representations with low-rank attained through β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}-QuAFIDA offer an effective approach for acquiring low-rank states. This research signifies a step forward in the synergy between AI and 5G technologies, presenting a novel avenue for the advancement of intelligent healthcare.

An active two-stage class-J power amplifier design for smart grid’s 5G wireless networks

<span>The wireless communication networks in the smart grid’s advanced metering infrastructure (AMI) applications need 5G technology to support large data transmission efficiently. As the 5G wireless communication network’s overall bandwidth (BW) and efficiency depend on its power amplifier (PA), in this work, a two-stage class-J power amplifier’s design methodology that operates at 3.5 GHz centre frequency by utilizing the CGH40010F model gallium nitride (GaN) transistor is presented. The proposed design methodology involves proper designing of input, output, and interstage matching networks to achieve class-J operation with improved power gain over desired BW using the advanced design system (ADS) electronic design automation (EDA) tool and estimating its integration feasibility through active element-based design approach using the Mentor Graphics EDA tool. The proposed PA provides 54% drain efficiency (D.E), 53% power added efficiency (PAE) with a small signal gain of 27 dB at 3.5 GHz and 41 dBm power output with 21 dB of improved power gain across a BW of around 400 MHz using 28 V power supply into 50 Ω load. By replacing the two-stage PA's passive elements with active elements, its layout size is estimated to be (15.5×29.2) μm2 . The results of the proposed PA exhibit its integration feasibility and suitability for the smart grid’s 5G wireless networks.</span>

Automating 5G network slice management for industrial applications

The transition to Industry 4.0 introduces new use cases with unique communication requirements, demanding wireless technologies capable of dynamically adjusting their performance to meet various demands. Leveraging network slicing, 5G technology offers the flexibility to support such use cases. However, the usage and deployment of network slices in networks are complex tasks. To increase the adoption of 5G, there is a need for mechanisms that automate the deployment and management of network slices. This paper introduces a design for a network slice manager capable of such mechanisms in 5G networks. This design adheres to related standards, facilitating interoperability with other software, while also considering the capabilities and limitations of the technology. The proposed design can provision custom slices tailored to meet the unique requirements of verticals, offering communication performance across the spectrum of the three primary 5G services (eMBB, URLLC, and mMTC/mIoT). To access the proposed design, a Proof-of-Concept (PoC) prototype was developed and evaluated. The evaluation results demonstrate the flexibility of the proposed solution for deploying slices adjusted to the vertical use cases. Additionally, the slices generated by the PoC maintain a high TRL (Technology Readiness Level) equivalent to that of the commercial-graded network used.

Advanced Beamforming and Multi‐Access Edge Computing: Empowering Ultra‐Reliable and Low‐Latency Applications in 6G Networks

ABSTRACT6G technology is expected to transform communications by allowing the Internet of Everything, representing a huge advance in 2030. While B5G has not yet been established, various nations are actively working on 5G, but certain research groups are presently devoting their attention to the creation of 6G technologies. The upcoming 6G networks promise higher quality of service (QoS) features, including virtual reality and holographic communications. Multi‐Access Edge Computing (MEC) and, in particular, the offloading idea are key components of 6G innovation that enable resource‐intensive application design. If the wireless link used for computational offloading is inefficient, MEC's true potential can be impeded. Intelligent beamforming and MEC have garnered attention recently. Systematically optimizing the wireless communication environment, these developments improve connectivity between user equipment (UE) and base station (BS). By increasing the electrical charge of the reflectable signal, intelligent beamforming increases the range and efficacy of Back Communication. Particularly, this study assesses how well the MEC structure performs in urban microcellular settings when intelligent beamforming is used in communications. It has been demonstrated that the use of Intelligent Reflecting Surfaces (IRS) greatly reduces spectrum and energy usage. This study's results are implemented in Python software. Our suggested strategy shows better latency compared to other optimization methods and shorter task completion times than traditional methods. When compared to conventional techniques, the suggested MEC‐enabled network showcasing lower latency (4.9 ms) and efficient network congestion management and task completion time (30 ms) demonstrates a significant performance. These results highlight how intelligent beamforming and MEC have a lot of potential to shape the architecture of 6G networks in the future.

Using 5G Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System

ABSTRACTThe introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing resource usage, managing mobility, ensuring cost‐efficiency, managing interference, and maximizing spectral efficiency. The fast advancement of artificial intelligence (AI) in several domains yields improved performance in contrast to traditional methods. Hence, including AI in 5G standards would enhance performance by catering to diverse end‐user applications. Initially, we provide an overview of concepts such as Industry 4.0, the 5G standard, and recent developments in the sphere of wireless communications in the future. The goal is to use 5G technology to look at current research problems. We present a new architecture for Industry 4.0 and 5G‐compliant smart healthcare systems. We develop and run the proposed model to investigate the current 5G methods using the Network Simulator (NS2). The results of the simulation show that 5G resource management and interference management approaches already in use face challenges including performance trade‐offs.

Reconfigurable Intelligent Surface (RIS)-Assisted Non-Terrestrial Network (NTN)-Based 6G Communications: A Contemporary Survey

This article examines the transformative potential of integrating reconfigurable intelligent surfaces (RISs) into sixth-generation (6G) wireless non-terrestrial networks (NTNs). The focus is on the RIS’s capability to address diverse user requirements, including secure data transmission, power efficiency, extended coverage, and enhanced data rates. The paper delves into the synergy between RISs and NTNs, emphasizing key components like multiple-input multiple-output (MIMO) systems and advanced radio communications. Additionally, it highlights the crucial role of artificial intelligence (AI) and machine learning (ML) in optimizing RIS-based beamforming to solve scientific and engineering challenges while ensuring energy efficiency and sustainability in NTN operations. By positioning RISs as a key enabler in shaping the future of wireless communication systems, this research underscores their significance in unlocking the full potential of NTNs and advancing next-generation wireless communications. This paper contributes valuable insights and projections for future research directions, highlighting RISs’ potential to revolutionize NTNs for 6G technologies.

A Hybrid Machine Learning‐Based Data‐Centric Cybersecurity Detection in the 5G‐Enabled IoT

ABSTRACTBy increasing smart objects as high‐potential computing devices and 5G technology, the Internet of Things (IoT) has emerging technology to provide a data‐centric infrastructure for detecting safe device‐to‐device communications by supporting security and privacy issues. As a 5G‐enabled communication technology, vehicle‐to‐vehicle (V2V) communication provides a wireless exchange information connection between smart vehicles, intelligent devices, and a cloud‐edge computing environment. This connection should be established with a safe and secured run‐time protection system to avoid many critical anomalies and misbehavior problems. Detecting run‐time malicious transformations with data‐centric misbehaving reactions is a main challenge for autonomous vehicle communications with 5G‐enabled communication technology. This paper provides a hybrid genetic algorithm‐based ensemble bagged trees (GA‐EBT) algorithm for a data‐centric misbehavior detection approach to support the V2V communications against malicious and misbehavior transactions. In this hybrid algorithm, GA provides a beneficial performance on the training accuracy factor based on a single‐objective fitness function and EBT supports a high‐degree prediction and training process using multiple decision tree models with bootstrapped samples of the training data. For the evaluation of the proposed algorithm, four real test cases are applied for messaging injection attacks in the V2V environments in comparison to the state‐of‐the‐art machine learning algorithms. The experimental results show that the proposed hybrid approach can achieve an optimal high rate accuracy factor of 99.999, precision and recall factors of 100%, and an F1‐Score factor of 100% to detect unexpected cyber‐attacks for the V2V communications in the IoT environment.

Research on Remote eSIM Provisioning Management Technology for 5G Terminal

The use of eSIM in mobile terminals such as the Internet of Vehicles has become the general trend, and more and more enterprises have put forward clear requirements for the remote provisioning of eSIM. This paper aims to combine 5G technology to analyze remote eSIM provisioning management technology for terminal, and combine algorithm improvement to improve remote eSIM information management and control effects. Moreover, this paper describes in detail the three-layer communication structure in the communication model, the design of edge gateway nodes, and the query mechanism for cloud center request names and data resources. In addition, this paper uses experiments to evaluate the connectivity of the eSIM three-layer communication model and the characteristics of the NDN network. Through experimental research, it can be seen that the remote eSIM provisioning management model proposed in this paper has certain advantages when applied to the Internet of Vehicles compared with the existing remote provisioning management technologies for the Internet of Vehicles. This article takes the Internet of Vehicles as an example to conduct research. At the same time, its support for mobility can be well applied to the Internet of Vehicles to meet the mobility of terminal vehicles. Therefore, it can provide some reference in the subsequent development of Internet of Vehicles technology.

Przykłady wdrożeń i przyszłość AI w diagnostyce medycznej

AI is revolutionizing medical diagnostics around the world, innovating in a variety of contexts, from leading US hospitals to facilities in developing countries. Below we present examples of AI implementations in medical diagnostics from different regions, taking into account the effectiveness and results of these solutions and forecasts for the development of this technology. Regarding the future of artificial intelligence in medical diagnostics, the article considered potential innovations such as the development of deep learning algorithms and integration with 5G technologies and the Internet. Attention is paid to the possibilities of further personalization of healthcare and to the challenges related to the need to adapt legal regulations and data management. It also indicates the directions of future research that may contribute to the further development of AI in medical diagnostics and the improvement of the quality of healthcare not only in Poland, but around the world.

Navigating urban congestion: A Comprehensive strategy based on an efficient smart IoT wireless communication for PV powered smart traffic management system.

Egypt faces extreme traffic congestion in its cities, which results in long travel times, large lines of parked cars, and increased safety hazards. Our study suggests a multi-modal approach that combines critical infrastructure improvements with cutting-edge technologies to address the ubiquitous problem of traffic congestion. Assuring vehicles owners of their timely arrival, cutting down on fuel usage, and improving communication using deep learning approach and optimization algorithm within the potential of IoT enabled 5G framework are the main goals. The traffic management system incorporates detection cameras, Raspberry Pi 3 microcontroller, an Android application, cloud connectivity, and traditional traffic lights that are powered using PV modules and batteries to secure the traffic controllers operation in case of grid outage and assure service continuity. The model examines the difficulties associated with Internet of Things (IoT) communication, highlighting possible interference from device-to-device (D2D) devices and cellular user equipment. This all-encompassing strategy aims to reduce fuel consumption, increase road safety and improve traffic efficiency. The model predicts a significant increase in Egypt's urban mobility by utilizing the possibilities of IoT and 5G technologies, which would improve Egypt's towns' livability and efficiency. The goal of this paper is to modernize Egypt's traffic management system and bring it into compliance with global guidelines for intelligent transportation networks.

6G Self‐Evolution Network for IoT Using Rainbow Deep Q‐Network Based on Decision‐Making

ABSTRACTIn recent trends, the development of 6G technology has provided a critical focus on its core network architecture which facilitates the robust foundation for entire network. A solution of self‐evolving networks for 6G is under consideration, in which networks develop their autonomy as a key perspective in the decision‐making process. Till now, various decision‐making mechanisms are identified, such as their key features, individual theoretical analyzes, and customized for 6G networks. To reduce the network load and improve system utilization, a decision‐making based on Rainbow Deep Q‐Network (RDQN) is proposed in this research. This methodology considers distributed decision‐making scenarios in which IoT devices enhance the quality of experience (QoE) with low training. Furthermore, it aims at a community of self‐evolving networks to show the improvements in 6G technologies and accelerates the learning rate. From the result analysis, it evidently displays that proposed RDQN has better training rate than other algorithms and requires fewer rounds of approximately 20 for a high number of episodes (500). Similarly, while evaluating QoE utility value, the proposed RDQN demonstrates a higher value of 100 when the number of target customers is large which outperforms the other existing models. The above results prove that the proposed RDQN is more efficient in IoT traffic monitoring and more suitable for the 6G environment.

Identifying QOS impacts on the 4G LTE and 5G FWA integration using 2300 to 2400 MHz band reallocation for high-speed internet alternative to traditional fiber

Although 5G technology has been in development for a considerable time, significant challenges regarding its effective implementation still need to be addressed. A key issue lies in using frequency and ensuring coexistence with previous technologies that continue to serve existing users because users in many countries' late adoption of new technologies does not always progress smoothly. This research paper aims to evaluate 5G Fixed Wireless Access (FWA) utilizing the 2300 to 2400 MHz spectrum that is usually used in 4G LTE previous technology, positioned as a viable alternative to traditional fiber optic networks, and its impact on technology valuation in spectrum usage to solve high-speed alternative traditional fiber in rural and urban areas. The study focuses on Quality of Service (QoS) related to user experience with a standard wireless access service parameter while analyzing payload growth and revenue generation improvements compared to LTE technologies. Through rigorous trials, our results demonstrate that 5G FWA not only preserves the QoS experienced but significantly enhances it as a feasibility analysis of network productivity by combining 4G and 5G technology in one service area. The implementation trial of 5G FWA resulted in notable increases of 50 % in more than 20 Mbps data throughput, contributing to 27 % substantial growth in payload and revenue in an area using only 4G LTE before 5G FWA was implemented. By providing detailed performance metrics, the trials highlighted the potential for 5G FWA to deliver broadband services more efficiently and cost-effectively, particularly in regions where geographical or economic factors constrain the expansion of fiber optics.

Ta doping effect on microstructure and microwave dielectric properties of CoNb2O6‐based ceramics and mechanism study

AbstractAs communication technology continues to evolve, 5G technology is becoming more mature, and 6G technology is steadily advancing. Microwave equipment is moving toward high frequency, miniaturization, low loss and high temperature stability, and microwave dielectric ceramics have been deeply applied in this field. To elevate the Q × f value of CoNb2O6 system, Ta5+ was introduced into CoNb2O6, and CoNb2‐xTaxO6 (0.0 ≤ x ≤ 0.8) ceramics were prepared by the traditional solid‐phase method. By X‐ray diffraction, it was observed that at x = 0.8, in addition to a single niobium ferrite phase, information of tantalate phase also appeared. Raman spectral detection and group theory analysis indicate that Ag(2) and Ag(3) modes are the dominant Raman vibrations at ≈873 cm−1. Furthermore, the polarization rate affects the εr value, and the bond energy of Nb/Ta‐O and the recovery force characterized by the average deformation of the [Nb/TaO6] octahedron are the key elements influencing the temperature coefficient of the resonance frequency (τf). The internal strain, ordered induced size, and chemical bonding valence of ionic valence states are the key factors that can increase the Q × f value. Moreover, the introduction of ions with lower electronegativity leads to an enhanced electronic compensation of oxygen vacancies, which also reduces the dielectric loss. This paper enriches the theory related to low dielectric loss and shows that CoNb1.8Ta0.2O6 (εr = 21.4832, Q × f = 100723 GHz, τf = ‐61.38 ppm/°C) ceramics with superior microwave dielectric properties are expected to be used in wireless communication devices.

Effects of radiofrequency electromagnetic radiation with a focus on haematology parameters

The use of radiofrequency electromagnetic radiation (RF-EMR) has steadily increased since the 1950s. RF-EMR is used in medicine, industry, household appliances, security and navigation, and especially in wireless elecommunications and animal husbandry. The widespread use of RF-EMR, especially with the introduction of 5G networks, raises concerns about potential adverse effects on human and animal health. The effects and mechanisms of RF-EMR impacts of 5G network frequencies on human and animal health are still unknown orpoorly understood. Current research findings include the biological effects of RF-EMR on genotoxicity, cell proliferation, gene expression, cell signalling, cell membrane function, and the function of immune, ematopoietic, and reproductive systems. Exposure of humans and laboratory animals to RF-EMR emitted from cell phones and many other electronic devices of 4G and older technologies has been shown to have detrimental effects on blood cells and to cause changes in the complete blood count. This depends on the type of organisms exposed, sources,frequency, electric field level and duration of exposure. There is sparse data in the available literature on the effects of RF-EMR on haematology indicators and erythrocyte morphometry in domestic animals. Therefore, the aim of this scientific review is to highlight the effects of RF-EMR on haematology indicators, erythrocyte morphometry, and platelet activation in humans and animals, taking into account the findings on the effects of 5G electromagnetic radiation on these indicators. Considering the ubiquitous electromagnetic pollution, it is important to gain knowledge about the effects of RF-EMR on human and animal health. In addition, it is necessary to determine the effects following in vitro exposure of blood to RF-EMR, especially due to the storage and use of blood and blood products in transfusion medicine.

Advancements and Challenges in Antenna Design and Rectifying Circuits for Radio Frequency Energy Harvesting

The proliferation of smart devices increases the demand for energy-efficient, battery-free technologies essential for sustaining IoT devices in Industry 4.0 and 5G networks, which require zero maintenance and sustainable operation. Integrating radio frequency (RF) energy harvesting with IoT and 5G technologies enables real-time data acquisition, reduces maintenance costs, and enhances productivity, supporting a carbon-free future. This survey reviews the challenges and advancements in RF energy harvesting, focusing on far-field wireless power transfer and powering low-energy devices. It examines miniaturization, circular polarization, fabrication challenges, and efficiency using the metamaterial-inspired antenna, concentrating on improving diode nonlinearity design. This study analyzes key components such as rectifiers, impedance matching networks, and antennas, and evaluates their applications in biomedical and IoT devices. The review concludes with future directions to increase bandwidth, improve power conversion efficiency, and optimize RF energy harvesting system designs.

Microsoft applications of 6G in V2X

Abstract. With the rapid advancement of intelligent transportation systems and autonomous driving technologies, 6G networks, as a key technology for future communications, are set to bring trans-formative changes to V2X (Vehicle-to-Everything) communication. This paper explores the application prospects of 6G in V2X, with a focus on the critical technological support 6G provides to vehicular networks. The high transmission rates and ultra-low latency of 6G will significantly enhance real-time interactions between vehicles and between vehicles and infrastructure, improving traffic safety and efficiency. Additionally, 6G's broad connectivity and flexible network architecture will support a greater number of simultaneous device connections, facilitating the widespread adoption of intelligent transportation systems. However, 6G faces challenges in V2X applications, including security issues, privacy protection, and internet power supply concerns. The paper analyzes these challenges, proposes corresponding solutions, and envisions the future development of 6G technology in the V2X domain.