A Survey on Device-to-Device Communication in 5G Wireless Networks

The Device-to-Device (D2D) communication model in 5G networks provides a useful infrastructure to enable different applications. D2D communication, with use of cellular or ad-hoc links, improve the spectrum utilization, system throughput, and energy efficiency of the network thereby preparing the ability for the user equipment to start communications with each other in proximity. The purpose of this paper is preparing a survey based on the D2D communication and review the available literature that in a widespread way research about the D2D paradigm, different application scenarios, and use cases. Moreover, new suspicion in this area that leads to identifying open research problems of D2D communications in cellular networks.info:eu-repo/semantics/publishedVersio

Investigating network services abstraction in 5G enabled device-to-device (D2D) communications

The increased demand of data rate by mobile users has led to the evolution of mobile network technologies from the fourth generation to fifth generation (5G). 5G mobile network will support various technologies that will be able to provide low latency, offload traffic and connect vertical industries. Device-to-device (D2D) communications will be used as the underlay technology for 5G network in the offloading of traffic from the cellular network and pushing content closer to the user. With D2D communication, various network services can be implemented to improve spectral efficiency and reduce energy consumption of mobile devices. This paper gives a brief overview of D2D communication and discusses different D2D applications. It proposes a network services abstraction and suggests the mapping of existing studies with the network service abstraction which can be used in the harnessing the development and implementation of D2D communication applications in 5G network. The paper also highlights possible future research for D2D communication in 5G network

Investigating network services abstraction in 5G enabled device-to-device (D2D) communications

The increased demand of data rate by mobile users has led to the evolution of mobile network technologies from the fourth generation to fifth generation (5G). 5G mobile network will support various technologies that will be able to provide low latency, offload traffic and connect vertical industries. Device-to-device (D2D) communications will be used as the underlay technology for 5G network in the offloading of traffic from the cellular network and pushing content closer to the user. With D2D communication, various network services can be implemented to improve spectral efficiency and reduce energy consumption of mobile devices. This paper gives a brief overview of D2D communication and discusses different D2D applications. It proposes a network services abstraction and suggests the mapping of existing studies with the network service abstraction which can be used in the harnessing the development and implementation of D2D communication applications in 5G network. The paper also highlights possible future research for D2D communication in 5G network

Efficient Traffic Management Algorithms for the Core Network using Device-to-Device Communication and Edge Caching

Exponentially growing number of communicating devices and the need for faster, more reliable and secure communication are becoming major challenges for current mobile communication architecture. More number of connected devices means more bandwidth and a need for higher Quality of Service (QoS) requirements, which bring new challenges in terms of resource and traffic management. Traffic offload to the edge has been introduced to tackle this demand-explosion that let the core network offload some of the contents to the edge to reduce the traffic congestion. Device-to-Device (D2D) communication and edge caching, has been proposed as promising solutions for offloading data. D2D communication refers to the communication infrastructure where the users in proximity communicate with each other directly. D2D communication improves overall spectral efficiency, however, it introduces additional interference in the system. To enable D2D communication, efficient resource allocation must be introduced in order to minimize the interference in the system and this benefits the system in terms of bandwidth efficiency. In the first part of this thesis, low complexity resource allocation algorithm using stable matching is proposed to optimally assign appropriate uplink resources to the devices in order to minimize interference among D2D and cellular users. Edge caching has recently been introduced as a modification of the caching scheme in the core network, which enables a cellular Base Station (BS) to keep copies of the contents in order to better serve users and enhance Quality of Experience (QoE). However, enabling BSs to cache data on the edge of the network brings new challenges especially on deciding on which and how the contents should be cached. Since users in the same cell may share similar content-needs, we can exploit this temporal-spatial correlation in the favor of caching system which is referred to local content popularity. Content popularity is the most important factor in the caching scheme which helps the BSs to cache appropriate data in order to serve the users more efficiently. In the edge caching scheme, the BS does not know the users request-pattern in advance. To overcome this bottleneck, a content popularity prediction using Markov Decision Process (MDP) is proposed in the second part of this thesis to let the BS know which data should be cached in each time-slot. By using the proposed scheme, core network access request can be significantly reduced and it works better than caching based on historical data in both stable and unstable content popularity

Mobile Edge Computing

This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management. The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists