5G Technology Research Articles

Design and Simulation of Multi Unmanned Boat Cooperative Obstacle Avoidance System Based on 5G Edge Computing

Background:: Compared to single unmanned boat, multi unmanned boats have more flexible mobility and efficient task completion capabilities, which can effectively expand the types of tasks. However, the traditional independent path planning and obstacle avoidance methods of unmanned boats are difficult to meet the requirements of collaborative operation among multiple unmanned boats due to the lack of information exchange. Objective:: According to the actual demand of multi unmanned boats' cooperative operation, a method of multi unmanned boats cooperative obstacle avoidance based on 5G edge computing is proposed to realize the unified planning and scheduling of multi unmanned boats. Methods:: Firstly, 5G technology and Kubeedge edge computing tools are used to build a multi unmanned boat collaborative obstacle avoidance system based on cloud, edge and end collaboration, and the Kubeedge edge computing platform was optimized by optimizing communication strategies, building a highly available Kubeedge cluster, building a Harbor image center, and using Web management interfaces further to improve the reliability and stability of the system. Secondly, the YOLOR-Deepport multi-target recognition and tracking algorithm based on cloud, edge and end collaborative network is used to complete the recognition and tracking tasks of obstacle targets, and a set of EECBS path planning methods based on the Kubedge centralized control platform is designed to plan collision-free and efficient paths for each unmanned boat in realtime. Finally, the effectiveness of the system was verified through simulation experiments. Results:: The experimental results show that compared to the traditional autonomous planning obstacle avoidance method for unmanned boats, the collaborative planning obstacle avoidance method proposed in this paper can exhibit excellent performance in dense and narrow scenarios, with a more reasonable navigation path, a range reduction of 20% - 50%, and higher safety. Conclusion:: The results show that the cooperative obstacle avoidance system based on 5G edge computing designed in the paper is feasible, and it can effectively realize the cooperative path planning and obstacle avoidance of multi unmanned boats.

Exploring high-valence element doping in LLZO electrolytes: Effects on phase transition and lithium-ion conductivity

The increasing popularity of electric vehicles and the emergence of 5G technology have created a demand for high-energy-density and safe batteries. Among various solid-state electrolytes, crystalline Li7La3Zr2O12 (c-LLZO) has garnered significant attention due to its exceptional properties. Researchers have explored doping in LLZO to modulate its phase transition and enhance lithium-ion conductivity. However, the mechanism by which doping induces a phase change and affects lithium-ion conductivity is currently unclear. In this study, we investigated LLZO doping and discovered that high-valence-element doping introduces vacancies, destabilizing the tetragonal phase and promoting the formation of the stable cubic phase. Moreover, we found that the introduction of lithium-ion vacancies significantly enhances lithium-ion conductivity. Nevertheless, doping also has adverse effects. Ga and Al dopants occupy the crucial Li24d sites, impeding lithium-ion diffusion and resulting in the closure of diffusion channels. Additionally, doping reduces the effective vacancy concentration within the structure, further restricting lithium-ion conductivity. In summary, our work elucidates the mechanism behind the influence of dopants on lithium-ion diffusion in LLZO.

5G Opportunities in the South Pacific: Leveraging Low-Band Spectrum for Socio-Economic Development

This paper explores the potential for deployment of 5G communication in the South Pacific, with a particular focus on leveraging the low-band spectrum for socio-economic development. The purpose of this study is to assess the feasibility of deploying 5G infrastructure in the South Pacific region, analyze the socio-economic benefits it may bring, and propose strategies to maximize these benefits. The research methodology includes a comprehensive review of existing literature on 5G deployment strategies, the socio-economic impacts of telecommunications infrastructure, and case studies of similar initiatives in other regions. The findings show that the deployment of 5G technology using low-band spectrum has the potential to significantly improve connectivity, healthcare, education, and economic opportunities in the South Pacific. Additionally, the paper proposes innovative approaches to address challenges such as infrastructure development in remote areas and affordability for marginalized communities. This study contributes to existing literature by providing tailored recommendations for leveraging 5G technology to address socio-economic inequalities in the South Pacific, thereby contributing to the development of telecommunications infrastructure in the region. Provides a new perspective on the possibilities of structure. Doi: 10.28991/HIJ-2024-05-02-020 Full Text: PDF

Optimizing high availability multi-controller placement in SDN/NFV 5G networks: a survey

<p>In meeting the diverse and occasionally conflicting quality of service (QoS) requirements associated with modern communication networks, 5G technology has emerged as a pivotal player. In its architecture, 5G has adopted network function virtualization (NFV) and cloud-based approaches, aiming to simplify network and service deployment, operational processes, and management. The convergence of software defined networking (SDN) and NFV offers an effective solution, enabling scalable and high-performance 5G networks. However, this integration poses critical challenges, with the placement of SDN controllers being a central concern due to its significant impact on network performance, covering aspects such as latency, costs, and energy efficiency. This challenge is known as the controller placement problem (CPP). The central theme of this paper revolves around the intricate relationship between 5G core networks, virtualization technology, and the pressing concern of SDN controller placement, underscoring its significance in the modern networking landscape. We provide a survey of recent methodologies aimed at solving the CPP within the realm of SDN, with a particular focus on resiliency and high availability.</p>

Deep reinforcement learning based latency-energy minimization in smart healthcare network

Significant breakthroughs in the Internet of Things (IoT) and 5G technologies have driven several smart healthcare activities, leading to a flood of computationally intensive applications in smart healthcare networks. Mobile Edge Computing (MEC) is considered as an efficient solution to provide powerful computing capabilities to latency or energy sensitive nodes. The low-latency and high-reliability requirements of healthcare application services can be met through optimal offloading and resource allocation for the computational tasks of the nodes. In this study, we established a system model consisting of two types of nodes by considering nondivisible and trade-off computational tasks between latency and energy consumption. To minimize processing cost of the system tasks, a Mixed-Integer Nonlinear Programming (MINLP) task offloading problem is proposed. Furthermore, this problem is decomposed into task offloading decisions and resource allocation problems. The resource allocation problem is solved using traditional optimization algorithms, and the offloading decision problem is solved using a deep reinforcement learning algorithm. We propose an Online Offloading based on the Deep Reinforcement Learning (OO-DRL) algorithm with parallel deep neural networks and a weight-sensitive experience replay mechanism. Simulation results show that, compared with several existing methods, our proposed algorithm can perform real-time task offloading in a smart healthcare network in dynamically varying environments and reduce the system task processing cost.

Study of the characteristics of broadband matching antennas for fifth-generation mobile communications based on new composite materials

The presented research aims to analyze in detail the characteristics of broadband matching antennas specifically designed for 5G mobile communications applications, with an emphasis on innovative composite materials. The study focuses on a compact planar loop antenna designed for use on smartphones, covering the LTE/WWAN frequency bands 824 to 960 MHz, 1,710 to 2,690 MHz, and 3,300 to 3,600 MHz for full coverage of modern 5G networks. Experimental and numerical methods are used to broadly analyze the frequency range associated with 5G networks. The features of the use of composite materials in the implementation of antenna devices in 5G technologies are noted. A broadband matching circuit (BMC) with elements with lumped parameters and a reduced sensitivity invariant has been synthesized. A 3D model of the adaptive selective surface controller (SSC) was developed using CST Studio. The study results highlight the benefits of new composite materials in improving the performance of 5G antennas. This research makes a significant contribution to the development of 5G technologies by optimizing antenna design for efficient data transmission in modern mobile networks and can be a valuable resource for engineers and designers working in this field.

5G-enabled UAVs for energy-efficient opportunistic networking

The article explores the potential of 5G-enabled Unmanned Aerial Vehicles (UAVs) in establishing opportunistic networks to improve network resource management, reduce energy use, and boost operational efficiency. The proposed framework utilizes 5G-enabled drones and edge command and control software to provide energy-efficient network topologies. As a result, UAVs operate edge computing for efficient data collecting and processing. This invention enhances network performance using modern Artificial Intelligence (AI) algorithms to improve UAV networking capabilities while conserving energy.An empirical investigation shows a significant improvement in network performance measures when using 5G technology compared to older 2.4 GHz systems. The communication failure rate decreased by 50 %, from 12 % to 6 %. The round-trip time was lowered by 58.3 %, from 120 Ms to 50 Ms. The payload efficiency improved by 13.3 %, dropping from 15 % to 13 %. The data transmission rate increased significantly from 1 Gbps to 5 Gbps, representing a 400 % boost. The numerical findings highlight the significant impact that 5G technology may have on UAV operations.Testing on a 5G-enabled UAV confirms the effectiveness of our technique in several domains, including precision agriculture, disaster response, and environmental monitoring. The solution seriously improves UAV network performance by reducing energy consumption and using peripheral network command-and-control software. Our results emphasize the versatile networking capacities of 5G-enabled drones, which provide new opportunities for UAV applications.

A reconstruction and recovery network-based channel estimation in high-speed railway wireless communications

The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development. Due to the considerable mobility of trains and the complex nature of the environment, the wireless channel exhibits non-stationary characteristics and fast time-varying characteristics, which presents significant hurdles in terms of channel estimation. In addition, the use of massive MIMO technology in the context of 5G networks also leads to an increase in the complexity of estimation. To address the aforementioned issues, this paper presents a novel approach for channel estimation in high mobility scenarios using a reconstruction and recovery network. In this method, the time-frequency response of the channel is considered as a two-dimensional image. The Fast Super-Resolution Convolution Neural Network (FSRCNN) is used to first reconstruct channel images. Next, the Denoising Convolution Neural Network (DnCNN) is applied to reduce the channel noise and improve the accuracy of channel estimation. Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method, while also exhibiting reduced algorithmic complexity.

A device to device driven approach towards optimizing energy efficiency for 6G networks

Our study aims to develop more energy-efficient mobile communication systems through the exploration of the 6th generation (6G) technology that is expected to be implemented in 2033. We focus on the impact of device-to-device (D2D) communication on power efficiency, which is a crucial need in this domain. To achieve this, we conducted a pioneering experiment using an in-house testbed and K-means clustering to classify locations as D2D enabled or disabled. Our findings show that there is a dynamic clustering mechanism that enables certain nodes to sustain D2D functionality around temporary base stations, resulting in a remarkable 5% improvement in network lifetime per second. This research not only enhances our understanding of 6G networks but also provides a practical methodology for optimizing energy consumption, which holds significant implications for society in advancing sustainable and efficient communication.

Compact dual-band antenna design for sub-6 GHz 5G application

A design of a compact dual-band antenna for 5G application is presented in this research article. The dual-band operation includes the 3.6 GHz and 5.4 GHz frequency bands of the sub-6 GHz frequency band for 5G technology. The proposed antenna offers a compact design with satisfactory antenna performance parameters. Moreover, the dual-band antenna showcases the independent tuning ability for both frequency bands. The prototype of the dual-band antenna is manufactured and when tested for various antenna performance parameters shows a good agreement between the simulated and measured results. The proposed dual-band antenna has compact dimensions along with a peak gain of 2.2 dB and antenna efficiency of more than 90%.The antenna performance parameters are also compared with various dual-band antenna designs from the literature. The proposed dual-band antenna offers a compact design with satisfactory performance parameters and outperforms its counterparts.

Bill on High Risk Suppliers

Abstract The subject of this article is the introduction of cybersecurity-related regulations on the providers of infrastructure for the provision of 5G technology services into the Polish legal system. In particular, the implementation of the recommendations of the report prepared by the Network and Information System Cooperation Group entitled Cybersecurity of 5G networks EU Toolbox of risk mitigating measures (referred to as the 5G Toolbox). Following the recommendations of the European Commission, Poland has undertaken work on introducing regulations that would implement the provisions of the 5G Toolbox regarding high-risk suppliers. An amendment to the Act on the National Cybersecurity System of 3 July 2023 (‘the Bill’) has been prepared, which includes recommendations of the 5G Toolbox. The article carries out an analysis to answer the question of whether the provisions of the Bill regarding proceedings in the case of the so-called high-risk suppliers are consistent with the Constitution and basic procedural principles, and in particular whether legal guarantees have been provided for participants in the proceedings regarding high-risk suppliers. The research hypothesis is that not all proposed regulations in this area meet the previously indicated requirements. The analysis takes into account the proposed regulations regarding: proceedings concerning recognition of a supplier as a high-risk supplier; application of the provisions of the Code of Administrative Procedure in these proceedings and the content of issued decisions and remedies. Mainly the dogmatic-legal method, as well as the theoretical-legal method, is used.

IMPROVING 5G NETWORK PERFORMANCE WITH MIMO TECHNOLOGY USING BEAMFORMING ALGORITHM

The advent of 5G technology aims to revolutionize wireless communication by providing significantly higher data rates, ultra- reliable low latency, and enhanced connectivity. However, optimizing 5G network performance remains a challenging task, particularly in terms of Bit Error Rate (BER) and spectral efficiency. Multiple-Input Multiple-Output (MIMO) technology, coupled with beamforming algorithms, offers a promising solution to these challenges. This study investigates the application of the Fractional Least Mean Square (FLMS) algorithm for beamforming in MIMO systems to improve BER and spectral efficiency in 5G networks. The primary problem addressed is the need for effective interference mitigation and signal enhancement in densely populated environments, which traditional methods struggle to handle. The proposed method utilizes the FLMS algorithm to dynamically adjust the beamforming weights, thereby optimizing the signal reception quality. The algorithm's fractional nature allows for finer adjustments and better adaptation to varying channel conditions compared to conventional LMS algorithms. Simulation results show the efficacy of the proposed method. Specifically, the implementation of the FLMS algorithm in a 4x4 MIMO system shows a reduction in BER by 30% and an improvement in spectral efficiency by 25% compared to traditional beamforming techniques. These numerical values highlight the potential of FLMS in enhancing 5G network performance, making it a viable approach for future wireless communication systems.

Additional Acceleration of Antenna Optimal Characterizationwith Modeling Support

Optimal characterization is assumed to provide the best solution for the designed cost function among the possible solutions within the specified range. These processes can take a long time depending on the applications and computer hardware used. Here, the optimization process is supported by ANN modeling in order to shorten the current optimization processes as much as possible. For this purpose, the selection of design parameters of the bowtie patch antenna (BPA) is presented as a multi-dimensional, multi-objective modeling-supported design optimization problem. The operating frequency of the proposed antenna is 28 GHz, which is the standard for millimeter wave band and 5G technologies. To overcome this challenging design optimization, a new, fast and powerful optimization algorithm was used by modifying the non-dominant sorting genetic algorithm (NSGA)-III, and the optimal characterization of the microwave antenna design was achieved. Although the proposed method gives the same results compared to the existing process, it takes much less time. Therefore, it is possible to shorten the process and reduce costs without the need for extra applications or hardware. As a whole, the proposed design optimization process is an efficient, fast and reliable solution for all design problems.

Lyapunov-guided deep reinforcement learning for delay-aware online task offloading in MEC systems

With the arrival of 5G technology and the popularization of the Internet of Things (IoT), mobile edge computing (MEC) has great potential in handling delay-sensitive and compute-intensive (DSCI) applications. Meanwhile, the need for reduced latency and improved energy efficiency in terminal devices is becoming urgent increasingly. However, the users are affected by channel conditions and bursty computational demands in dynamic MEC environments, which can lead to longer task correspondence times. Therefore, finding an efficient task offloading method in stochastic systems is crucial for optimizing system energy consumption. Additionally, the delay due to frequent user–MEC interactions cannot be overlooked. In this article, we initially frame the task offloading issue as a dynamic optimization issue. The goal is to minimize the system’s long-term energy consumption while ensuring the task queue’s stability over the long term. Using the Lyapunov optimization technique, the task processing deadline problem is converted into a stability control problem for the virtual queue. Then, a novel Lyapunov-guided deep reinforcement learning (DRL) for delay-aware offloading algorithm (LyD2OA) is designed. LyD2OA can figure out the task offloading scheme online, and adaptively offload the task with better network quality. Meanwhile, it ensures that deadlines are not violated when offloading tasks in poor communication environments. In addition, we perform a rigorous mathematical analysis of the performance of Ly2DOA and prove the existence of upper bounds on the virtual queue. It is theoretically proven that LyD2OA enables the system to realize the trade-off between energy consumption and delay. Finally, extensive simulation experiments verify that LyD2OA has good performance in minimizing energy consumption and keeping latency low.

A Review on 5G Antenna: Challenges and Parameter Enhancement Techniques

The need for a high-speed mobile network has increased due to the COVID19 pandemic.5G is the newest and most sophisticated technology designed to handle the demands of the internet. The 5G network ensures connection security and simplifies mobile device connectivity to wireless devices. This paper explains every parameter related to 5G technology that has been covered in various papers. It addresses some of the difficulties that 5G technology faces. The development of Vivaldi, conformal, MIMO antennas satisfies the requirements of the 5G mobile network and presents opportunities to overcome obstacles. In the paper, MIMO antenna is discussed along with various techniques for enhancing its parameters, such as appropriate substrate selection, antenna element placement, and mutual coupling reduction. Different techniques like isolation, DGS, slot, metamaterial, neutralizing line, and frequency reconfigurations are explained under mutual coupling reduction techniques. A comparative analysis of various antenna feeding techniques is presented in the paper. The article provides details on how various parameters are affected by parameter enhancement techniques.

Mobile Network Subscribers Market Share Evolution Of Telecommunication Companies In Senegal From 1996 To 2022

This research examines the evolution of market shares of telecommunications companies in Senegal over a period of 26 years, from 1996 to 2022. The study focuses on subscriber’s market share as a key indicator of mobile network operators' performance and competitiveness. It analyzes the mix market share for the three main mobile network operators (ORANGE, FREE, and EXPRESSO) consolidation periods, key success factors, and challenges faced by these companies in a dynamic and competitive environment.The analysis reveals a significant evolution in the telecommunications landscape in Senegal, marked by the emergence of new players, the advancement of technologies, the diversification of offerings, and the increase in connectivity. Major historical operators had to contend with growing competition, stimulating innovation and service improvement to meet changing consumer needs.Key events such as the introduction of 3G and 4G technology, had a significant impact on market share distribution and companies' differentiation strategies. Regulatory policies such as mobile telephony licensing, investments in infrastructure, brand changes, order entry, strategic partnerships, and operators’ number of years of experience also influenced the sector's competitive dynamics.In conclusion, this research highlights the complex and dynamic evolution of market shares of telecommunications companies in Senegal, highlighting the technological, strategic, and regulatory factors that have shaped this sector over the years.

Arsitektur Jaringan telekomunikasi

The development of technology in this world is increasingly growing rapidly, one of which is in the development of cellular telecommunications. 5G technology is the name of the 5th generation of mobile communication development, whose standards exceed those of the 4G generation. The literature review in this journal includes network architecture, LAN, CPU, UE, and MCC. The research method used by the author is descriptive research method. The results are that the use of cloud computing at the edge of the network will make the signal from 5G faster than 4G, because the data has been stored and the more users who use it will increase the speed even more and shortening the signaling delay is used to avoid signal transmission from SCeNBces to centralized SCM.

Multi-Traffic Resource Optimization for Real-Time Applications with 5G Configured Grant Scheduling

The fifth-generation (5G) technology standard in telecommunications is expected to support ultra-reliable low latency communication to enable real-time applications such as industrial automation and control. 5G configured grant (CG) scheduling features a pre-allocated periodicity-based scheduling approach, which reduces control signaling time and guarantees service quality. Although this enables 5G to support hard real-time periodic traffics, synthesizing the schedule efficiently and achieving high resource efficiency, while serving multiple communications, are still an open problem. In this work, we study the trade-off between scheduling flexibility and control overhead when performing CG scheduling. To address the CG scheduling problem, we first formulate it using satisfiability modulo theories (SMT) so that an SMT solver can be used to generate optimal solutions. To enhance scalability, we propose two heuristic approaches. The first one as the baseline, Co1, follows the basic idea of the 5G CG scheduling scheme that minimizes the control overhead. The second one, CoU, enables increased scheduling flexibility while considering the involved control overhead. The effectiveness and scalability of the proposed techniques and the superiority of CoU compared to Co1 have been evaluated using a large number of generated benchmarks as well as a realistic case study for industrial automation.

Migrating From 5g To 6g Technologies: A Paradigm Shift With Profound Concomitant Changes

Migrating From 5g To 6g Technologies: A Paradigm Shift With Profound Concomitant Changes

5G- Analysis and Characteristics in Comparison with Previous Generations

This paper explores the architecture and remarkable advantages of 5G technology in the current industry of wireless communication. The paper covers details of the recently developed 5th generation of networks and how its benefits overpower its drawbacks, majorly being its impact on health and environment. This study helps understanding 5G and highlights how this recent advancement has better chances of helping with wide area network connectivity, latency, economic growth, enhanced security features etc. While advancements in the cellular network technology continue to be one of the most important developments in the economic, telecom and healthcare sector among many others, many common beliefs about 5G which can be listed as its “drawbacks” have been brought to people’s attention recently, and with proper facts and studies, it can be easily proved how 5G, till this date, has no significant harm to any area, and simply has a few complexities which are natural with any advancement in technology. The paper covers the characteristics of the 5G network, and addresses common misconceptions and concerns surrounding health, security, and infrastructure.