Mobility Management Issues and Solutions in 5G-and-Beyond Networks: A Comprehensive Review

Siddiqui, Maraj Uddin Ahmed; Qamar, Faizan; Tayyab, Muhammad; Hindia, Mohammad Nour; Nguyễn, Quang Ngọc; Hassan, Rosilah

doi:10.3390/electronics11091366

Cited by 46 publications

(24 citation statements)

References 136 publications

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“…One of such requirements is backhaul link management, which occurs due to composing a large number of small cells based dense radio access network. SDN has emerged as a promising approach for handling the Distributed Mobility Management (DMM) paradigm in dense wireless communication [85]. The authors in [86] suggested an SDN-based implementation for IPv6 compatible MAC layer control through Southbound API (Application Layer Interface) in SDN.…”

Section: A Distributed Mobility Managementmentioning

confidence: 99%

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

et al. 2023

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The outright aim of Beyond Fifth Generation (B5G) communication is to bring a revolution in Quality of Service (QoS) through enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), and massive Machine Type Communication (mMTC). Thereby, due to this massive expansion in the communication paradigm, interference is bound to surface unexpected challenges in the wireless domain. Thus, interference mitigation is a foundational aim in the research paraphernalia of B5G communication. Presently, Software Defined Networking (SDN) is emerging to empower wireless communication with centralized routing-based interference mitigation. With this premise, we aim to present a focused review on SDN-based interference mitigation in wireless communication. Initially, we discuss current research horizon in the subject domain and briefly explore literature for routing-based interference mitigation. Thereby, we analyze the potential of SDN through evaluation of existing solutions for interference mitigation in B5G communication. We conclude our survey by highlighting prominent future research directions in SDN-based interference mitigation.

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Section: A Distributed Mobility Managementmentioning

confidence: 99%

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

et al. 2023

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“…On the other hand, in order to effectively deploy D2D communication technology, a number of problems must be resolved. D2D technology needs efficient power and spectrum allocation algorithms, advanced interference mitigation methods, and intelligent mode selection and mobility strategies [67]. Many research investigations in D2D communications have been introduced to realize different aspects of D2D technology.…”

Section: Related Work and Contributionmentioning

confidence: 99%

A Survey of Resource Management in D2D Communication for B5G Networks

et al. 2023

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Due to the vast rise of users, the variety of application requirements, and the enormous necessity for ubiquitous connectivity anytime and anywhere, integration of new technologies and ideas are required. Therefore, Device to Device (D2D) communication technology has been regarded as a critical concern for Beyond Fifth Generation (B5G) networks. In the D2D technology, devices in close proximity may connect without using a Base Station (BS). Consequently, improving the capacity and performance of traditional networks. The major objectives are to accomplish a high geared data rate, increase the network coverage with low latency, and improve Energy Efficiency (EE) and Spectrum Efficiency (SE). However, the coexistence of D2D technology in the traditional network can pose many issues and challenges, such as power control, interference, spectrum access, security, and mode selection. Consequently, a comprehensive survey that includes an investigation of the current issues in D2D technology is required. In this survey, we present a new categorization of the most important aspects of resource management in B5G D2D communication, such as power allocation, spectrum allocation, interference management, and mode selection. Furthermore, we discuss the limitations and open issues of the current techniques and propose a model approach and future directions for D2D communication in B5G wireless networks. Our survey aims to assist researchers in exploring and improving D2D communication within the framework of forthcoming wireless networks.

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“…A new solution for managing mobility should be created to provide seamless changeover for 5G new radio in network slicing. The management of mobility is divided into two levels of mode: idle mode for user reachability and connected mode for handover, making mobility one of the major concerns in a service level for future networks [18]. According to the explanation of the mobility management architecture in [19] based on network slicing, each slice maintains its users across various radio access technologies.…”

Section: Literature Reviewmentioning

confidence: 99%

Management and Evaluation of the Performance of end-to-end 5G Inter/Intra Slicing using Machine Learning in a Sustainable Environment

Mohammedali¹,

Kanakis²,

Al-Sherbaz³

et al. 2023

JCOMSS

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The 3G Partnership Project (3GPP) defined network slicing as a set of resources that could be scaled up and down to cover users' requirements. Machine learning and network slicing will be used together to manage and optimize resources efficiently. Sharing resources across multiple operators, such as towers, spectrum and infrastructure, can reduce the cost of 5G resources. In the proposed prototype, the end-user is connected to more than eight inter and intra-slices according to the demands. A set of slices is implemented over the 5G networks to provide an efficient service to the end-user using softwarization and virtualization technologies. Traffic is generated over multiple scenarios then End-to-End slicing traffic was analyzed after generating realtime traffic over the 5G networks. Also, all the features extracted from the traffic based on the flow behaviours and a set of elements selected from the datasets according to machine learning behaviours. Multiple machine learning algorithms are applied to our datasets using MATLAB classification application. After that, the best model is chosen to train and predict the slices using less CPU and training time to reduce the computational power in future networks and build a sustainable environment. Furthermore, the regression application predicts the slice type on the third dataset with the minimum squared error.

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Mobility Management Issues and Solutions in 5G-and-Beyond Networks: A Comprehensive Review

Cited by 46 publications

References 136 publications

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

A Survey of Resource Management in D2D Communication for B5G Networks

Management and Evaluation of the Performance of end-to-end 5G Inter/Intra Slicing using Machine Learning in a Sustainable Environment

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