Articles de revues : « Beyond 5G Networks »

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Abdellah, Ali, et Andrey Koucheryavy. « Artificial Intelligence Driven 5G and Beyond Networks ». Telecom IT 10, n^o 2 (12 avril 2023) : 1–13. http://dx.doi.org/10.31854/2307-1303-2022-10-2-1-13.

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5G networks and beyond are expected to meet numerous service requirements in various aspects of our daily lives. At the same time, the functional complexity of 5G telecommunication networks increases by an order of magnitude compared to existing networks. 5G data rates are dramatically faster, connection density is higher, and latency is much lower, among other improvements. An efficient 5G network cannot be complete without incorporating artificial intelligence (AI) techniques. All this requires the use of new technologies, including artificial intelligence, to ensure the stable operation of telecommunication networks, methodology, system analysis, and key results. Scientific tasks for 5G communication networks are identified where the use of artificial intelligence, including machine and deep learning, seems appropriate. Practical Relevance. The results of the work may be useful in training in networks and telecommunication systems and in defining new scientific tasks for PhD students.

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Yeonjoo Lim, Yeonjoo Lim, et Jong-Hyouk Lee Yeonjoo Lim. « Container-based Service Relocation for Beyond 5G Networks ». 網際網路技術學刊 23, n^o 4 (juillet 2022) : 911–18. http://dx.doi.org/10.53106/160792642022072304026.

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<p>With the advent of 5G networks, various research on Multi-access Edge Computing (MEC) to provide high-reliability and ultra-low latency services are being actively conducted. MEC is an intelligent service distributed cloud technology that provides a high level of personal services by deploying cloud servers to edge networks physically closed to users. However, there is a technical issue to be solved, e.g., the service being used by a user does not exist in the new edge network, and there may even be situations in which the service cannot be provided in the new edge network. To address this, the service application must be relocated according to the location of the user’s movement. Various research works are underway to solve this service relocation issue, e.g., cold/live migration studies have been carried in legacy cloud environments. In this paper, we propose a container migration technique that guarantees a smooth service application relocation for mobile users. We design scenarios for adaptive handoff and describe the detailed operation process. In addition, we present our MEC testbed, which has been used to experiment our container migration technique.</p> <p> </p>

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Kao, Hsiao-Wen, et Eric Hsiao-Kuang Wu. « QoE Sustainability on 5G and Beyond 5G Networks ». IEEE Wireless Communications 30, n^o 1 (février 2023) : 118–25. http://dx.doi.org/10.1109/mwc.007.2200260.

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Hashima, Sherief, Basem M. ElHalawany, Kohei Hatano, Kaishun Wu et Ehab Mahmoud Mohamed. « Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks ». Electronics 10, n^o 2 (14 janvier 2021) : 169. http://dx.doi.org/10.3390/electronics10020169.

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Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

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Tanveer, Jawad, Amir Haider, Rashid Ali et Ajung Kim. « Machine Learning for Physical Layer in 5G and beyond Wireless Networks : A Survey ». Electronics 11, n^o 1 (30 décembre 2021) : 121. http://dx.doi.org/10.3390/electronics11010121.

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Fifth-generation (5G) technology will play a vital role in future wireless networks. The breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where billions of connected devices, people, and processes will be simultaneously served. The services provided by 5G include several use cases enabled by the enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communication. Fifth-generation networks potentially merge multiple networks on a single platform, providing a landscape for seamless connectivity, particularly for high-mobility devices. With their enhanced speed, 5G networks are prone to various research challenges. In this context, we provide a comprehensive survey on 5G technologies that emphasize machine learning-based solutions to cope with existing and future challenges. First, we discuss 5G network architecture and outline the key performance indicators compared to the previous and upcoming network generations. Second, we discuss next-generation wireless networks and their characteristics, applications, and use cases for fast connectivity to billions of devices. Then, we confer physical layer services, functions, and issues that decrease the signal quality. We also present studies on 5G network technologies, 5G propelling trends, and architectures that help to achieve the goals of 5G. Moreover, we discuss signaling techniques for 5G massive multiple-input and multiple-output and beam-forming techniques to enhance data rates with efficient spectrum sharing. Further, we review security and privacy concerns in 5G and standard bodies’ actionable recommendations for policy makers. Finally, we also discuss emerging challenges and future directions.

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Agiwal, Anil, et Mamta Agiwal. « Enhanced Paging Monitoring for 5G and Beyond 5G Networks ». IEEE Access 10 (2022) : 27197–210. http://dx.doi.org/10.1109/access.2022.3157874.

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Pervaiz, Haris, Muhammad Ali Imran, Shahid Mumtaz, Anwer-al Dulaimi et Nikolaos Thomos. « Editorial : Spectrum extensions for 5G and beyond 5G networks ». Transactions on Emerging Telecommunications Technologies 29, n^o 10 (octobre 2018) : e3519. http://dx.doi.org/10.1002/ett.3519.

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Fathima Rubeena, Et al. « Revolutionizing 5G Networks : A Synergy of Routing, Clustering, and Energy Optimization for Unprecedented Performance and Extended Lifespan ». International Journal on Recent and Innovation Trends in Computing and Communication 11, n^o 9 (5 novembre 2023) : 3926–36. http://dx.doi.org/10.17762/ijritcc.v11i9.9719.

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The concept of revolutionizing 5G (Fifth Generation) networks through a synergy of routing, clustering, and energy optimization is indeed a promising approach to enhancing the performance and lifespan of wireless networks. Exciting changes will occur in the physical, digital, and biological worlds over the next ten years. Although the needs for Beyond 5G (B5G) are not yet fully understood, an effort has been made to stratify 5G progression and B5G. This work highlights the focus on revolutionizing 5G networks through the integration of routing, clustering, and energy optimization techniques. By combining these methodologies, this research work aims to address the complex challenges in 5G networking, such as efficient data routing, resource allocation, and energy consumption. The objective is to achieve both exceptional performance and an extended lifespan for these networks. The proposed work holds promise for significantly enhancing the capabilities of 5G networks, resulting in improved user experiences, optimized resource utilization, and prolonged network lifespan. In order to completely meet the most stringent 5G standards, such as stratification, or deconstruction into existing technologies, will comprise technology scenarios of 5G evolutions. Wireless sensor networks (WSNs), which offer essential data collecting and monitoring capabilities, are made up entirely of 5G networks. These methods are designed specifically for use in 5G networks to increase the network’s lifespan and overall performance. For 5G networks, routing and clustering techniques from WSNs can be modified and optimized to increase energy efficiency and prolong the network lifetime in 5G networks.

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Fathima Rubeena, Et al. « Revolutionizing 5G Networks : A Synergy of Routing, Clustering, and Energy Optimization for Unprecedented Performance and Extended Lifespan ». International Journal on Recent and Innovation Trends in Computing and Communication 11, n^o 10 (2 novembre 2023) : 528–37. http://dx.doi.org/10.17762/ijritcc.v11i10.8520.

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The concept of revolutionizing 5G (Fifth Generation) networks through a synergy of routing, clustering, and energy optimization is indeed a promising approach to enhancing the performance and lifespan of wireless networks. Exciting changes will occur in the physical, digital, and biological worlds over the next ten years. Although the needs for Beyond 5G (B5G) are not yet fully understood, an effort has been made to stratify 5G progression and B5G. This work highlights the focus on revolutionizing 5G networks through the integration of routing, clustering, and energy optimization techniques. By combining these methodologies, this research work aims to address the complex challenges in 5G networking, such as efficient data routing, resource allocation, and energy consumption. The objective is to achieve both exceptional performance and an extended lifespan for these networks. The proposed work holds promise for significantly enhancing the capabilities of 5G networks, resulting in improved user experiences, optimized resource utilization, and prolonged network lifespan. In order to completely meet the most stringent 5G standards, such as stratification, or deconstruction into existing technologies, will comprise technology scenarios of 5G evolutions. Wireless sensor networks (WSNs), which offer essential data collecting and monitoring capabilities, are made up entirely of 5G networks. These methods are designed specifically for use in 5G networks to increase the network’s lifespan and overall performance. For 5G networks, routing and clustering techniques from WSNs can be modified and optimized to increase energy efficiency and prolong the network lifetime in 5G networks.

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Mustafa, Ahmed Shamil, Mohammad Abdulrahman Al-Mashhadani, Salah Ayad Jasim, Ahmed Muhi Shantaf et Mustafa Maad Hamdi. « Blockchain in fifth-generation network and beyond : a survey ». Bulletin of Electrical Engineering and Informatics 11, n^o 3 (1 juin 2022) : 1399–408. http://dx.doi.org/10.11591/eei.v11i3.3209.

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Fifth-generation (5G) technologies enable a wide range of vertical applications by connecting heterogeneous equipment and machines, resulting in significantly improved service quality, increased network capacity, and improved system performance. As a result, the world is shifting to 5G wireless networks. Because 5G has the advantage of supporting various vertical applications, 5G systems must still overcome challenges such as transparency, data interoperability probabilities, decentralization, and network privacy. In this paper, we'll show how blockchain can be used to solve problems in 5G, as well as some of the idea’s researchers, have come up with to solve them, like resource sharing, security, and mobility.

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Bocu, Razvan, et Maksim Iavich. « Real-Time Intrusion Detection and Prevention System for 5G and beyond Software-Defined Networks ». Symmetry 15, n^o 1 (31 décembre 2022) : 110. http://dx.doi.org/10.3390/sym15010110.

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The philosophy of the IoT world is becoming important for a projected, always-connected world. The 5G networks will significantly improve the value of 4G networks in the day-to-day world, making them fundamental to the next-generation IoT device networks. This article presents the current advances in the improvement of the standards, which simulate 5G networks. This article evaluates the experience that the authors gained when implementing Vodafone Romania 5G network services, illustrates the experience gained in context by analyzing relevant peer-to-peer work and used technologies, and outlines the relevant research areas and challenges that are likely to affect the design and implementation of large 5G data networks. This paper presents a machine learning-based real-time intrusion detection system with the corresponding intrusion prevention system. The convolutional neural network (CNN) is used to train the model. The system was evaluated in the context of the 5G data network. The smart intrusion detection system (IDS) takes the creation of software-defined networks into account. It uses models based on artificial intelligence. The system is capable to reveal not previously detected intrusions using software components based on machine learning, using the convolutional neural network. The intrusion prevention system (IPS) blocks the malicious traffic. This system was evaluated, and the results confirmed that it provides higher efficiencies compared to less overhead-like approaches, allowing for real-time deployment in 5G networks. The offered system can be used for symmetric and asymmetric communication scenarios.

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Benzaid, Chafika, Tarik Taleb et Muhammad Zubair Farooqi. « Trust in 5G and Beyond Networks ». IEEE Network 35, n^o 3 (mai 2021) : 212–22. http://dx.doi.org/10.1109/mnet.011.2000508.

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Conti, Andrea, Flavio Morselli, Zhenyu Liu, Stefania Bartoletti, Santiago Mazuelas, William C. Lindsey et Moe Z. Win. « Location Awareness in Beyond 5G Networks ». IEEE Communications Magazine 59, n^o 11 (novembre 2021) : 22–27. http://dx.doi.org/10.1109/mcom.221.2100359.

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Careglio, Davide, Salvatore Spadaro, Albert Cabellos, Jose Antonio Lazaro, Pere Barlet-Ros, Joan Manel Gené, Jordi Perelló et al. « Results and Achievements of the ALLIANCE Project : New Network Solutions for 5G and Beyond ». Applied Sciences 11, n^o 19 (30 septembre 2021) : 9130. http://dx.doi.org/10.3390/app11199130.

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Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and intra-datacentre (DC) network and computational resources into a single converged 5G network infrastructure. The present paper overviews the main achievements obtained in the ALLIANCE project. This project ambitiously aims at architecting a converged 5G-enabled network infrastructure satisfying those needs to effectively realise the envisioned upcoming Digital Society. In particular, we present two networking solutions for 5G and beyond 5G (B5G), such as Software Defined Networking/Network Function Virtualisation (SDN/NFV) on top of an ultra-high-capacity spatially and spectrally flexible all-optical network infrastructure, and the clean-slate Recursive Inter-Network Architecture (RINA) over packet networks, including access, metro, core and DC segments. The common umbrella of all these solutions is the Knowledge-Defined Networking (KDN)-based orchestration layer which, by implementing Artificial Intelligence (AI) techniques, enables an optimal end-to-end service provisioning. Finally, the cross-layer manager of the ALLIANCE architecture includes two novel elements, namely the monitoring element providing network and user data in real time to the KDN, and the blockchain-based trust element in charge of exchanging reliable and confident information with external domains.

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Angalaeswari, T., et M. Logeswari. « Machine Learning Techniques for 5g And Beyond ». Data Analytics and Artificial Intelligence 3, n^o 2 (1 février 2023) : 54–58. http://dx.doi.org/10.46632/daai/3/2/11.

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In today's world, wireless communication systems are extremely important for applications related to entertainment, business, commerce, health and safety. These systems continue to advance from generation to generation and at this time, fifth generation (5G) wireless networks are being deployed globally the globe. Beyond 5G wireless systems, which will represent the sixth generation (6G) of the evolution, are already being discussed in academia and industry. The application of artificial intelligence (AI) and machine learning (ML) to such wireless networks will be one of the primary and essential elements of 6G systems. According to our present understanding of wireless technologies up to 5G, every component and building block of a wireless system, such as the physical, network, and application layers, will involve one or more of them.

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Enjie Liu, Youbing Zhao et Abimbola Efunogbon. « Boosting smarter digital health care with 5G and beyond networks ». ITU Journal on Future and Evolving Technologies 4, n^o 1 (10 mars 2023) : 157–65. http://dx.doi.org/10.52953/gjnn6958.

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With 5G and beyond on the horizon, ultra-fast and low latency data transmission on the cloud and via the Internet will enable more intelligent and interactive medical and health-care applications. This paper presents a review of 5G technologies and their related applications in the health-care sector. The introduction to 5G technology includes software defined network, 5G architecture and edge computing. The second part of the paper then presents the opportunities provided by 5G to the health-care sector and employs medical imaging applications as central examples to demonstrate the impacts of 5G and the cloud. Finally, this paper summarize the benefits brought by 5G and cloud computing to the health-care sector.

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Fayad, Abdulhalim, Tibor Cinkler, Jacek Rak et Manish Jha. « Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks : An Optimization Perspective ». Sensors 22, n^o 23 (1 décembre 2022) : 9394. http://dx.doi.org/10.3390/s22239394.

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Currently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient connections between a large number of remote radio heads (RRHs) in the cell sites and the baseband unit (BBU) pool in the central location, known as the fronthaul, has emerged as a new challenge. Many wired and wireless solutions have been proposed to address this bottleneck. Specifically, optical technologies presented by passive optical networks (PONs) are introduced as the best suitable solution for 5G and beyond network fronthaul due to their properties of providing high capacity and low latency connections. We considered time and wavelength division multiplexed passive optical networks (TWDM-PONs) as a fronthaul for 5G and beyond. Taking that into consideration, in this paper, we propose an integer linear program (ILP) that results in the optimal optical fronthaul deployment while minimizing the total cost of 5G and beyond instances. However, for larger network instances, solving the ILP problem becomes unscalable and time-consuming. To address that, we developed two heuristic-based algorithms (the K-means clustering algorithm and the one based on the genetic algorithm—GA). We evaluated the suitability of our proposed ILP and heuristic algorithms in simulations by utilizing them to plan different network instances (dense and sparse).

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Singh, Saurabh, C. Rajesh Babu, Kadiyala Ramana, In-Ho Ra et Byungun Yoon. « BENS−B5G : Blockchain-Enabled Network Slicing in 5G and Beyond-5G (B5G) Networks ». Sensors 22, n^o 16 (14 août 2022) : 6068. http://dx.doi.org/10.3390/s22166068.

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Fifth-generation (5G) technology is anticipated to allow a slew of novel applications across a variety of industries. The wireless communication of the 5G and Beyond-5G (B5G) networks will accommodate a wide variety of services and user expectations, including intense end-user connectivity, sub-1 ms delay, and a transmission rate of 100 Gbps. Network slicing is envisioned as an appropriate technique that can meet these disparate requirements. The intrinsic qualities of a blockchain, which has lately acquired prominence, mean that it is critical for the 5G network and B5G networks. In particular, the incorporation of blockchain technology into B5G enables the network to effectively monitor and control resource utilization and sharing. Using blockchain technology, a network-slicing architecture referred to as the Blockchain Consensus Framework is introduced that allows resource providers to dynamically contract resources, especially the radio access network (RAN) schedule, to guarantee that their end-to-end services are effortlessly executed. The core of our methodology is comprehensive service procurement, which offers the fine-grained adaptive allocation of resources through a blockchain-based consensus mechanism. Our objective is to have Primary User—Secondary User (PU—SU) interactions with a variety of services, while minimizing the operation and maintenance costs of the 5G service providers. A Blockchain-Enabled Network Slicing Model (BENS), which is a learning-based algorithm, is incorporated to handle the spectrum resource allocation in a sophisticate manner. The performance and inferences of the proposed work are analyzed in detail.

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Yadav, Ranjeet, Ashutosh Tripathi, Sunil Pathak et Harjot Singh Gill. « 5G and Beyond Networks for 3D MIMO Using Artificial Intelligence in 5G Network ». Journal of Physics : Conference Series 2273, n^o 1 (1 mai 2022) : 012007. http://dx.doi.org/10.1088/1742-6596/2273/1/012007.

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Abstract Today’s wireless systems would be incomplete without MIMO systems, which have become increasingly common in recent years due to their ability to increase both spectrum efficiency and energy efficiency at a significant rate. Prior MIMO, the most often utilised system was a single-input, single-output system, which had limited capability and could not reliably support a huge number of users. Throughout this study, an artificial intelligence machine training MIMO channel is developed to handle the huge customer demand.. However, the ever-increasing needs are not met by this new technology. AI techniques becoming more prominent in determining the angle of elevation and angle of arrival for 3D MIMO in 5G system. These days, more and more people are using wireless devices, and these devices generate an enormous volume of information that must be processed quickly and reliably. AI based machine learning solve the issue and provide more throughput and energy efficient 5G system.

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Yadav, Ranjeet, Ashutosh Tripathi, Sunil Pathak et Harjot Singh Gill. « 5G and Beyond Networks for 3D MIMO Using Artificial Intelligence in 5G Network ». Journal of Physics : Conference Series 2273, n^o 1 (1 mai 2022) : 012007. http://dx.doi.org/10.1088/1742-6596/2273/1/012007.

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Abstract Today’s wireless systems would be incomplete without MIMO systems, which have become increasingly common in recent years due to their ability to increase both spectrum efficiency and energy efficiency at a significant rate. Prior MIMO, the most often utilised system was a single-input, single-output system, which had limited capability and could not reliably support a huge number of users. Throughout this study, an artificial intelligence machine training MIMO channel is developed to handle the huge customer demand.. However, the ever-increasing needs are not met by this new technology. AI techniques becoming more prominent in determining the angle of elevation and angle of arrival for 3D MIMO in 5G system. These days, more and more people are using wireless devices, and these devices generate an enormous volume of information that must be processed quickly and reliably. AI based machine learning solve the issue and provide more throughput and energy efficient 5G system.

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Sylla, Tidiane, Leo Mendiboure, Sassi Maaloul, Hasnaa Aniss, Mohamed Aymen Chalouf et Stéphane Delbruel. « Multi-Connectivity for 5G Networks and Beyond : A Survey ». Sensors 22, n^o 19 (7 octobre 2022) : 7591. http://dx.doi.org/10.3390/s22197591.

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To manage a growing number of users and an ever-increasing demand for bandwidth, future 5th Generation (5G) cellular networks will combine different radio access technologies (cellular, satellite, and WiFi, among others) and different types of equipment (pico-cells, femto-cells, small-cells, macro-cells, etc.). Multi-connectivity is an emerging paradigm aiming to leverage this heterogeneous architecture. To achieve this, multi-connectivity proposes to enable UE to simultaneously use component carriers from different and heterogeneous network nodes: base stations, WiFi access points, etc. This could offer many benefits in terms of quality of service, energy efficiency, fairness, mobility, and spectrum and interference management. Therefore, this survey aims to present an overview of multi-connectivity in 5G networks and beyond. To do so, a comprehensive review of existing standards and enabling technologies is proposed. Then, a taxonomy is defined to classify the different elements characterizing multi-connectivity in 5G and future networks. Thereafter, existing research works using multi-connectivity to improve the quality of service, energy efficiency, fairness, mobility management, and spectrum and interference management are analyzed and compared. In addition, lessons common to these different contexts are presented. Finally, open challenges for multi-connectivity in 5G networks and beyond are discussed.

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Andrade-Hoz, Jimena, Qi Wang et Jose M. Alcaraz-Calero. « Infrastructure-Wide and Intent-Based Networking Dataset for 5G-and-beyond AI-Driven Autonomous Networks ». Sensors 24, n^o 3 (25 janvier 2024) : 783. http://dx.doi.org/10.3390/s24030783.

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In the era of Autonomous Networks (ANs), artificial intelligence (AI) plays a crucial role for their development in cellular networks, especially in 5G-and-beyond networks. The availability of high-quality networking datasets is one of the essential aspects for creating data-driven algorithms in network management and optimisation tasks. These datasets serve as the foundation for empowering AI algorithms to make informed decisions and optimise network resources efficiently. In this research work, we propose the IW-IB-5GNET networking dataset: an infrastructure-wide and intent-based dataset that is intended to be of use in research and development of network management and optimisation solutions in 5G-and-beyond networks. It is infrastructure wide due to the fact that the dataset includes information from all layers of the 5G network. It is also intent based as it is initiated based on predefined user intents. The proposed dataset has been generated in an emulated 5G network, with a wide deployment of network sensors for its creation. The IW-IB-5GNET dataset is promising to facilitate the development of autonomous and intelligent network management solutions that enhance network performance and optimisation.

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Papidas, Andreas G., et George C. Polyzos. « Self-Organizing Networks for 5G and Beyond : A View from the Top ». Future Internet 14, n^o 3 (17 mars 2022) : 95. http://dx.doi.org/10.3390/fi14030095.

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We describe self-organizing network (SON) concepts and architectures and their potential to play a central role in 5G deployment and next-generation networks. Our focus is on the basic SON use case applied to radio access networks (RAN), which is self-optimization. We analyze SON applications’ rationale and operation, the design and dimensioning of SON systems, possible deficiencies and conflicts that occur through the parallel operation of functions, and describe the strong reliance on machine learning (ML) and artificial intelligence (AI). Moreover, we present and comment on very recent proposals for SON deployment in 5G networks. Typical examples include the binding of SON systems with techniques such as Network Function Virtualization (NFV), Cloud RAN (C-RAN), Ultra-Reliable Low Latency Communications (URLLC), massive Machine-Type Communication (mMTC) for IoT, and automated backhauling, which lead the way towards the adoption of SON techniques in Beyond 5G (B5G) networks.

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Hayajneh, Khaled F. « Memory-Based LT Codes for Efficient 5G Networks and Beyond ». Electronics 10, n^o 24 (20 décembre 2021) : 3169. http://dx.doi.org/10.3390/electronics10243169.

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The next-generation networks (5G and beyond) require robust channel codes to support their high specifications, such as low latency, low complexity, significant coding gain, and flexibility. In this paper, we propose using a fountain code as a promising solution to 5G and 6G networks, and then we propose using a modified version of the fountain codes (Luby transform codes) over a network topology (Y-network) that is relevant in the context of the 5G networks. In such a network, the user can be connected to two different cells at the same time. In addition, the paper presents the necessary techniques for analyzing the system and shows that the proposed scheme enhances the system performance in terms of decoding success probability, error probability, and code rate (or overhead). Furthermore, the analyses in this paper allow us to quantify the trade-off between overhead, on the one hand, and the decoding success probability and error probability, on the other hand. Finally, based on the analytical approach and numerical results, our simulation results demonstrate that the proposed scheme achieves better performance than the regular LT codes and the other schemes in the literature.

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Sertac Kaya, Diego Tuzi, Pheobe Agbo, Thomas Marx, Ali Eltohamy, Florian Volk, Petra Weitkemper, Matthias Korb, Christian Hofmann et Andreas Knopp. « Mobile networks expanding to space : Overview of the seranis beyond 5G testbed ». ITU Journal on Future and Evolving Technologies 5, n^o 2 (3 juin 2024) : 172–93. http://dx.doi.org/10.52953/wibp9997.

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In recent years, Non-Terrestrial Networks (NTNs) have gained increased attention from the 3rd Generation Partnership Project (3GPP) due to their potential to enhance cellular networks by improving coverage, resiliency, and reliability, especially in rural areas and disaster scenarios. The upcoming Sixth-Generation (6G) cellular networks aim to establish layers of cells at different altitudes with Base Stations (BSs) on Earth and in space, providing a seamless user experience. Testing and experimentation are crucial for realizing this ambitious vision. University of the Bundeswehr Munich (UniBw M) is deploying a Beyond 5G (B5G) and 6G testbed comprising both space and ground segments. The space segment of the testbed is composed of the ATHENE-1 satellite that is going to be launched in 2025. The ground segment includes the satellite ground station with several full motion antennas for the radiofrequency links and an optical ground station for the free-space optical link based on laser technology, while the Terrestrial Network (TN) component is deployed using a Fifth-Generation (5G) Non-Public Network (NPN) with multiple gNodeBs (gNBs) and multiple 5G core solutions. In its current state, the testbed includes various measurement equipment and emulators in the 5G Lab, a Gnb with two active cells, a core network, a satellite ground station, and a mobile 5G on-the-move solution. This testbed allows various experiments including interference management between existing networks, positioning and localization, Public Protection and Disaster Recovery (PPDR) using Multi-Access Edge Computing (MEC) and NTN. This paper describes the components of the Seamless Radio Access Networks for Internet of Space (SeRANIS) B5G testbed, the current status, future deployment plan, preliminary test results, and planned tests.

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Masoudi, Meysam, Mohammad Galal Khafagy, Alberto Conte, Ali El-Amine, Brian Francoise, Chayan Nadjahi, Fatma Ezzahra Salem et al. « Green Mobile Networks for 5G and Beyond ». IEEE Access 7 (2019) : 107270–99. http://dx.doi.org/10.1109/access.2019.2932777.

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Thantharate, Anurag, Ankita Vijay Tondwalkar, Cory Beard et Andres Kwasinski. « ECO6G : Energy and Cost Analysis for Network Slicing Deployment in Beyond 5G Networks ». Sensors 22, n^o 22 (8 novembre 2022) : 8614. http://dx.doi.org/10.3390/s22228614.

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Fifth-generation (5G) wireless technology promises to be the critical enabler of use cases far beyond smartphones and other connected devices. This next-generation 5G wireless standard represents the changing face of connectivity by enabling elevated levels of automation through continuous optimization of several Key Performance Indicators (KPIs) such as latency, reliability, connection density, and energy efficiency. Mobile Network Operators (MNOs) must promote and implement innovative technologies and solutions to reduce network energy consumption while delivering high-speed and low-latency services to deploy energy-efficient 5G networks with a reduced carbon footprint. This research evaluates an energy-saving method using data-driven learning through load estimation for Beyond 5G (B5G) networks. The proposed ‘ECO6G’ model utilizes a supervised Machine Learning (ML) approach for forecasting traffic load and uses the estimated load to evaluate the energy efficiency and OPEX savings. The simulation results demonstrate a comparative analysis between the traditional time-series forecasting methods and the proposed ML model that utilizes learned parameters. Our ECO6G dataset is captured from measurements on a real-world operational 5G base station (BS). We showcase simulations using our ECO6G model for a given dataset and demonstrate that the proposed ECO6G model is accurate within $4.3 million over 100,000 BSs over 5 years compared to three other models that would increase OPEX cost from $370 million to $1.87 billion during varying network load scenarios against other data-driven and statistical learning models.

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Waqas, Abdullah, Nasir Saeed, Hasan Mahmood et Muhannad Almutiry. « Distributed Destination Search Routing for 5G and beyond Networks ». Sensors 22, n^o 2 (8 janvier 2022) : 472. http://dx.doi.org/10.3390/s22020472.

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Fifth-generation and beyond networks target multiple distributed network application such as Internet of Things (IoT), connected robotics, and massive Machine Type Communication (mMTC). In the absence of a central management unit, the device need to search and establish a route towards the destination before initializing data transmission. In this paper, we proposes a destination search and routing method for distributed 5G and beyond networks. In the proposed method, the source node makes multiple attempts to search for a route towards the destination by expanding disk-like patterns originating from the source node. The source node increases the search area in each attempt, accommodating more nodes in the search process. As a result, the probability of finding the destination increases, which reduces energy consumption and time delay of routing. We propose three variants of routing for high, medium, and low-density network scenarios and analyze their performance for various network configurations. The results demonstrate that the performance of the proposed solution is better than previously proposed techniques in terms of time latency and reduced energy consumption, making it applicable for 5G and beyond networks.

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Yu, Heejung, et Yousaf Bin Zikria. « Cognitive Radio Networks for Internet of Things and Wireless Sensor Networks ». Sensors 20, n^o 18 (16 septembre 2020) : 5288. http://dx.doi.org/10.3390/s20185288.

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Recent innovation, growth, and deployment of internet of things (IoT) networks are changing the daily life of people. 5G networks are widely deployed around the world, and they are important for continuous growth of IoT. The next generation cellular networks and wireless sensor networks (WSN) make the road to the target of the next generation IoT networks. The challenges of the next generation IoT networks remain in reducing the overall network latency and increasing throughput without sacrificing reliability. One feasible alternative is coexistence of networks operating on different frequencies. However, data bandwidth support and spectrum availability are the major challenges. Therefore, cognitive radio networks (CRN) are the best available technology to cater to all these challenges for the co-existence of IoT, WSN, 5G, and beyond-5G networks.

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Bojkovic, Zoran, Dragorad Milovanovic, Tulsi Pawan Fowdur et Mussawir Ahmad Hosany. « What 5G has been and what should 5G+ be ? » Athens Journal of Τechnology & ; Engineering 8, n^o 1 (20 janvier 2021) : 27–38. http://dx.doi.org/10.30958/ajte.8-1-2.

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In this work we aim to provide a comprehensive summary of the most inspiring aspects of 5G mobile networks. In addition, we present the latest findings on the promising 6G technology towards a world of fully digital connectivity. The key determinants are extreme system performance and combinations of requirements for new use cases. We study new performance targets beyond 5G in two stages: 5G+ evolution and new 6G step. Relevant technologies considered too immature for 5G or outside the defined scope are outlined. To justify our vision of future mobile networks, we point out the need for closer collaborations of academia, standardizing bodies, industrial organizations and governments. The contribution strategy is gradual evolution and performance enhancement of mobile communications. Finally, we identify challenges and directions on network technology roadmap toward 6G. Keywords: wireless communication, mobile broadband, low-latency communi-cation, 5G network, 3GPP, 6G vision

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Albagory, Yasser. « Modelling, Investigation, and Feasibility of Stratospheric Broadband mm-Wave 5G and beyond Networks for Aviation ». Electronics 9, n^o 11 (7 novembre 2020) : 1872. http://dx.doi.org/10.3390/electronics9111872.

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Recent advances in communication systems provide an enabling technology for aircraft connection and safety. A promising communication system that uses stratospheric platforms provides an efficient and improved communication performance and can be an efficient solution for establishing communication networks for aviation. Therefore, in this paper, a novel communication network based on stratospheric basestation (SB) is proposed to provide fifth-generation (5G) and beyond services for civil aviation aircrafts to improve global flight connectivity, control, and safety. The proposed aircraft–SB network is demonstrated, and its coverage geometry is modelled and investigated. As the 5G and beyond networks use millimeter wave frequency bands (mm-wave), the performance of different atmospheric losses including gaseous absorption, rain, and fog/cloud is analyzed to investigate the system’s practical feasibility at different 5G proposed frequencies ranging from 3.5 to 66 GHz through a flight model including three distinct stages which are takeoff/landing, climbing/descending, and cruise stages. Also, handover scenarios in the proposed aircraft–SB network are investigated and analyzed at the proposed 5G frequencies. In addition, the aircraft–SB 5G network is compared to the most recent low-Earth orbit (LEO) Internet satellites where the proposed system is expected to provide low latency, less atmospheric attenuation, longer aircraft–SB link duration, and very low handover rate.

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Sedhom, Germien G., Alshimaa H. Ismail et Basma M. Yousef. « Literature Review and Novel Trends of Mobile Edge Computing for 5G and Beyond ». Journal of Artificial Intelligence and Metaheuristics 2, n^o 2 (2022) : 18–28. http://dx.doi.org/10.54216/jaim.020202.

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Because of the rapid evolution of communications technologies, such as the Internet of Things (IoT) and fifth generation (5G) systems and beyond, the latest developments have seen a fundamental change in mobile computing. Mobile computing is moved from central mobile cloud computing to mobile edge computing (MEC). Therefore, MEC is considered an essential technology for 5G technology and beyond. The MEC technology permits user equipment (UEs) to execute numerous high-computational operations by creating computing capabilities at the edge networks and inside access networks. Consequently, in this paper, we extensively address the role of MEC in 5G networks and beyond. Accordingly, we first investigate the MEC architecture, the characteristics of edge computing, and the MEC challenges. Then, the paper discusses the MEC use cases and service scenarios. Further, computations offloading is explored. Lastly, we propose upcoming research difficulties in incorporating MEC with the 5G system and beyond.

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DAHLMAN, Erik, Gunnar MILDH, Stefan PARKVALL, Patrik PERSSON, Gustav WIKSTRÖM et Hideshi MURAI. « 5G Evolution and Beyond ». IEICE Transactions on Communications E104.B, n^o 9 (1 septembre 2021) : 984–91. http://dx.doi.org/10.1587/transcom.2020fgi0001.

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Paramonov, Alexander, Ammar Muthanna, Omar I. Aboulola, Ibrahim A. Elgendy, Riad Alharbey, Evgeny Tonkikh et Andrey Koucheryavy. « Beyond 5G Network Architecture Study : Fractal Properties of Access Network ». Applied Sciences 10, n^o 20 (15 octobre 2020) : 7191. http://dx.doi.org/10.3390/app10207191.

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Wireless networks connect various devices through radio waves in which the network connection may have different structures. Moreover, the network structure is determined based on the placement areas of the network elements, which can be affected by the building and their locations. However, the numerical characteristic which describe the features of the real environment and allow them to be related to the properties of the model are still a challenge that has not been well addressed. To this end, in this paper, we analyze the modeling problems related to the structure of user placement in the access network. Our proposed solution is based on a description of the user environment structure in which cities in the form of buildings and constructions are considered as a typical environment. We propose a new model for addressing the wireless network structure in an efficient manner in which the features of the environment are considered, which are numerically expressed in the form of the Hurst parameter or fractal dimension. In addition, the fractal dimension, geometric fractals, and the characteristics of the user’s distribution territory and urban development are efficiently utilized. Then, we analyze the influence of the fractal properties of the environment on the structure of promising communication networks; in particular, on the structure of the Internet of Things network. Finally, simulation results proved that the proposed model is considered as a beneficial solution for modeling mobile communication and wireless access networks, including fifth-generation networks.

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Saida, Angotu, R. K. Yadav et V. K. Sharma. « Analysis of LTE based an Antenna Design for 5G Communications ». International Journal on Recent and Innovation Trends in Computing and Communication 11, n^o 6 (8 août 2023) : 471–75. http://dx.doi.org/10.17762/ijritcc.v11i6.7785.

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As the world progresses towards the next generation of communications networks, new technological solutions, architectures and standards are urgently required. This evolution of communications networks will facilitate numerous convincing business and consumer applications and speed up large investments in network infrastructure, appliances and devices. Wireless technologies of the last generation, 5G networks, promise an era of all-round, secure and powerful radio network. The use of 5G technology extends beyond traditional telecoms, and includes extremely low latencies, high energy efficiency or comprehensive Gbps. This paper also accurately includes 5G requirements and antenna categorization accompanied by a comparative study of various antenna designs. The various researchers have previously suggested several 5G antenna designs, but an exhaustive examination using their performance improvement system of the various types of 5G antenna has not yet been completed. We thus tried to examine the various types of 5G antenna design, their mechanisms for improving performance, comparisons and possible worldwide breakthroughs.

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Barbosa, Raul, João Fonseca, Marco Araújo et Daniel Corujo. « Vinia : Voice-enabled intent-based networking for industrial automation ». Computer Science and Information Systems, n^o 00 (2024) : 2. http://dx.doi.org/10.2298/csis230213002b.

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Intent Based Networking (IBN) is a promising approach for automating and managing large and complex networks. Integrating Voice-enabled Virtual Assistants (VVAs) with IBN and Software Defined Networking (SDN) has improved network management efficiency and flexibility. However, there is still room for optimization improvement in installing intents in industrial scenarios. Network Orchestration Automation plays an important role within the Beyond 5G and 6G Networks, considering existing practices for orchestrating 5G Network Functions. This work presents an extended preliminary architecture for a voice-enabled IBN system called VINIA for industrial network automation. The new approach allows the configuration of more network assets (e.g., 5G networks), leveraging Network Orchestrators and Network Slice Managers, thus improving the system?s capabilities. The results provide insights into this solution?s potential benefits and limitations to enhance the automation of industrial networks? management and orchestration procedures.

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Sufyan, Ali, Khan Bahadar Khan, Osama A. Khashan, Talha Mir et Usama Mir. « From 5G to beyond 5G : A Comprehensive Survey of Wireless Network Evolution, Challenges, and Promising Technologies ». Electronics 12, n^o 10 (12 mai 2023) : 2200. http://dx.doi.org/10.3390/electronics12102200.

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The histrionic growth of mobile subscribers, disruptive ecosystems such as IoT-based applications, and astounding channel capacity requirements to connect trillions of devices are massive challenges of the earlier mobile generations, 5G turned up the key solution. The prime objective of the 5G network is not only to maintain a 1000-fold capacity gain and 10 Giga Bits per second delivered to a single user, but it also assured quality-of-service, higher spectral efficiency, the ultra-reliable and improved battery lifetime of devices and massive machine-type communication (mMTC). The huge traffic load and high amount of resource consumption in 5G applications, augmented reality and virtual reality for magnificent virtual experience, and wireless body area networks will seriously affect the channel capacity of cellular cells and interrupt the admission and service of other users which makes compulsory new means of channel capacity and spectral efficiency enhancement techniques. In this research, we review several key emerging wireless technologies to increase channel capacity and spectral efficiency that will not only lead to improve network performance but also meets the ever-increasing user demands. We investigate various benefits and current research challenges of using these technologies. We analyze massive multi-input multi-output technology (mMIMO) an efficient technique and promising solution for the 5G and Beyond 5G (B5G) networks with several benefits and features. Moreover, this paper will be of vast help to the researchers who will involve advance investigation and also to the wireless network operator industry that is in the search for smooth development of state-of-the-art 5G and B5G networks.

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Khaturia, Meghna, Pranav Jha et Abhay Karandikar. « 5G-Flow : A unified Multi-RAT RAN architecture for beyond 5G networks ». Computer Networks 198 (octobre 2021) : 108412. http://dx.doi.org/10.1016/j.comnet.2021.108412.

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Nyangaresi, Vincent Omollo, et Anthony Joachim Rodrigues. « Efficient handover protocol for 5G and beyond networks ». Computers & ; Security 113 (février 2022) : 102546. http://dx.doi.org/10.1016/j.cose.2021.102546.

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Zhang, Yan, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid et Chunfen Cui. « Guest Editorial : Edge Intelligence for Beyond 5G Networks ». IEEE Wireless Communications 28, n^o 2 (avril 2021) : 10–11. http://dx.doi.org/10.1109/mwc.2021.9430853.

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Zou, Fang, Lei Zou, Bo Yang, Qian Ma, Xihua Zou, Jim Zou, Siming Chen, Dusan Milosevic, Zizheng Cao et Huiyun Liu. « Optoelectronic oscillator for 5G wireless networks and beyond ». Journal of Physics D : Applied Physics 54, n^o 42 (3 août 2021) : 423002. http://dx.doi.org/10.1088/1361-6463/ac13f2.

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Andersson, Cecilia, Jonas Bengtsson, Greger Bystrom, Pal Frenger, Ylva Jading et My Nordenstrom. « Improving energy performance in 5G networks and beyond ». Ericsson Technology Review 2022, n^o 8 (août 2022) : 2–11. http://dx.doi.org/10.23919/etr.2022.9911220.

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Kannan, Yamini, et Dharika Kapil. « Implementing Machine Learning Algorithms for Predictive Network Maintenance in 5G and Beyond Networks ». International Journal of Wireless & ; Mobile Networks 16, n^o 1/2 (28 avril 2024) : 01–11. http://dx.doi.org/10.5121/ijwmn.2024.16201.

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With the evolution of fifth generation (5G) network technologies, network maintenance strategies have become increasingly complex, necessitating the use of predictive analysis enabled by Machine Learning (ML) algorithms. This paper emphasizes exploring how ML algorithms can further enhance predictive maintenance in 5G and future networks. It reviews the current literature on this interdisciplinary topic, identifying key ML models such as Decision Trees, Neural Networks, and Support Vector Machines, and discussing their benefits and limitations. Special attention is given to the methodologies in applying these models, handling of data stages, and the training process. Major challenges in implementing ML in the context of network maintenance, such as data privacy, data gathering, model training, and generalizability, are discussed. Furthermore, the research aims to go beyond predicting maintenance needs to introduce a proactive approach in improving overall network performance and pre-empting potential issues based on ML predictions. The paper also discusses possible future trends including advancements in ML algorithms, Automated Machine Learning (AutoML), Explainable AI, and others. The objective is to provide a comprehensive understanding of the current ML-based predictive maintenance field and outline possibilities for future research. The study finds that the application of ML algorithms continues to show promise in transforming the landscape of network management by improving predictive maintenance and proactive performance enhancement strategies. It remains a challenging yet important area in the context of 5G networks.

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Mourtzis, Dimitris, John Angelopoulos et Nikos Panopoulos. « Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0 : Challenges, Applications and New Trends ». Electronics 10, n^o 24 (20 décembre 2021) : 3175. http://dx.doi.org/10.3390/electronics10243175.

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For many applications deployed in manufacturing networks, communication latency has been a significant barrier. Despite the constant development of improved communication protocols and standards during Industry 4.0, the latency problem persists, lowering quality of services (QoS) and quality of experience (QoE). Tactile internet (TI), with its high availability, security, and ultra-low latency, will add a new dimension to human-machine interaction (HMI) by enabling haptic and tactile sensations. The tactile internet (TI) is a cutting-edge technology that uses 5G and beyond (B5G) communications to enable real-time interaction of haptic data over the internet between tactile ends. This emerging TI technology is regarded as the next evolutionary step for the Internet of Things (IoT) and is expected to bring about massive changes towards Society 5.0 and to address complex issues in current society. To that end, the 5G mobile communication systems will support the TI at the wireless edge. As a result, TI can be used as a backbone for delay mitigation in conjunction with 5G networks, allowing for ultra-reliable low latency applications like Smart Manufacturing, virtual reality, and augmented reality. Consequently, the purpose of this paper is to present the current state of 5G and TI, as well as the challenges and future trends for 5G networks beyond 2021, as well as a conceptual framework for integrating 5G and TI into existing industrial case studies, with a focus on the design aspects and layers of TI, such as the master, network, and slave layers. Finally, the key publications focused on the key enabling technologies of TI are summarized and the beyond 5G era towards Society 5.0 based on cyber-physical systems is discussed.

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Sohaib, Rana Muhammad, Oluwakayode Onireti, Yusuf Sambo et Muhammad Ali Imran. « Network Slicing for Beyond 5G Systems : An Overview of the Smart Port Use Case ». Electronics 10, n^o 9 (5 mai 2021) : 1090. http://dx.doi.org/10.3390/electronics10091090.

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As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance’s (NGMN’s) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyond 5G networks and elaborate on how ML techniques can be useful for mobility prediction and resource management. Lastly, we propose the use case of network slicing based on ML techniques in a smart seaport environment, which will help to manage the resources more efficiently.

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Salameh, Ahmed I., et Mohamed El Tarhuni. « From 5G to 6G—Challenges, Technologies, and Applications ». Future Internet 14, n^o 4 (12 avril 2022) : 117. http://dx.doi.org/10.3390/fi14040117.

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As the deployment of 5G mobile radio networks gains momentum across the globe, the wireless research community is already planning the successor of 5G. In this paper, we highlight the shortcomings of 5G in meeting the needs of more data-intensive, low-latency, and ultra-high-reliability applications. We then discuss the salient characteristics of the 6G network following a hierarchical approach including the social, economic, and technological aspects. We also discuss some of the key technologies expected to support the move towards 6G. Finally, we quantify and summarize the research work related to beyond 5G and 6G networks through an extensive search of publications and research groups and present a possible timeline for 6G activities.

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Anicho, Ogbonnaya, Philip Charlesworth, Gurvinder Baicher et Atulya Nagar. « Multi-HAPS Network Implementation within 3GPP’s NTN framework for 5G and beyond ». International Journal of Information, Communication Technology and Applications 7, n^o 1 (30 décembre 2021) : 7–12. http://dx.doi.org/10.17972/ijicta20217152.

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High Altitude Platform Station (HAPS) is part of the 3GPP defined non-terrestrial network (NTN) infrastructure for 5G networks. Various technical studies by 3GPP have addressed NTN-based implementations and have significantly studied satellite-based scenarios. However, the study does not sufficiently address HAPS or multi-HAPS based scenarios specifically. Though HAPS, is captured under Unmanned Aerial Systems (UAS), it has unique operational realities that set it apart from other NTN platforms. For instance, HAPS come in different variants of fixed-wing, balloons and airships. This paper highlights the need for expanded studies specifically aimed at HAPS for more seamless integration. The work also analyses the Doppler effect associated with fixed-wing HAPS systems to further demonstrate how operational scenarios may differ for these platforms and the need for targeted studies. HAPS is expected to contribute significantly to the NTN-based implementations and may require more specialised considerations within the 3GPP NTN technical specification process, especially for 5G and beyond 5G (B5G) networks.

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Sahinel, Doruk, Simon Rommel et Idelfonso Tafur Monroy. « Resource Management in Converged Optical and Millimeter Wave Radio Networks : A Review ». Applied Sciences 12, n^o 1 (27 décembre 2021) : 221. http://dx.doi.org/10.3390/app12010221.

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Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at the edge key resources similar to the available bandwidth in network communication channels. Aiming to understand the relationship between resource management, virtualization, and the dense 5G access and fronthaul with an emphasis on converged radio and optical communications, this article presents a review of how resource management solutions have dealt with optimizing millimeter wave radio and optical resources from an autonomic network management perspective. A research agenda is also proposed by identifying current state-of-the-art solutions and the need to shift all the convergent issues towards building an advanced resource management mechanism for beyond-5G.

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Munir, Rizwan, Yifei Wei, Chao Ma et Bizhu Yang. « Dynamically Resource Allocation in Beyond 5G (B5G) Network RAN Slicing Using Deep Deterministic Policy Gradient ». Wireless Communications and Mobile Computing 2022 (21 décembre 2022) : 1–13. http://dx.doi.org/10.1155/2022/9958786.

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Network slicing makes it possible for future applications with a variety of adaptability requirements and performance requirements by spliting the physical network into several logical networks. Radio access network (RAN) slicing’s main goal is to assign physical resource blocks (RBs) to mMTC, eMBB, and uRLLC services while ensuring the Quality of service (QoS). Consequently, it is challenging to determine the optimal strategies for 5G radio access network (5G-RAN) slicing because of dynamically changes in slice needs and environmental data, and conventional approaches have difficulty addressing resource allocation issues. In this paper, we present an energy-efficient deep deterministic policy gradient resource allocation (EE-DDPG-RA) method for RAN slicing in 5G networks to choose the resource allocation policy that increases long-term throughput while satisfying the requirements of B5G systems for quality of service. This method’s main goal is to remove unnecessary actions in order to lower the amount of available action space. The numerical outcomes demonstrate that the proposed approach outperforms boundaries by enhancing deep-rooted throughput and effectively managing resources.

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Siddiqui, Maraj Uddin Ahmed, Faizan Qamar, Muhammad Tayyab, MHD Nour Hindia, Quang Ngoc Nguyen et Rosilah Hassan. « Mobility Management Issues and Solutions in 5G-and-Beyond Networks : A Comprehensive Review ». Electronics 11, n^o 9 (25 avril 2022) : 1366. http://dx.doi.org/10.3390/electronics11091366.

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The fully accomplished standardization of the new mobile generation has led to the deployment of fifth-generation (5G) wireless networks to gratify enormous traffic volume for Internet services. The current centralized mobility system could not be sufficient to manage an explosive increase in data volume and is considered a steadily rising issue in modern wireless communication. A new technique that can affluently handle traffic problems and completely avoid network breakdown chances is indispensable. Recently, distributed mobility management (DMM) was introduced to overcome the inevitable obstacles that destructively impact the existing networks. Specifically, a novel design based on the deployment of distributed mobility anchors, closer to the terminal points, was introduced. Several works have been proposed to build DMM solutions with different focuses for 5G-and-beyond networks (B5G), which are also referred to as sixth-generation solutions (6G). In this paper, we present the potential and benefits of flat network design for efficient and fast routing of traffic and furnish the effectiveness of the scheme toward mobility management in B5G by delineating recent research works. We also present the current limitations, challenges, and future research directions for seamless mobility to achieve the desired objectives in the current 5G and upcoming 6G cellular communications.

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