D2D Communications for 5G and Beyond

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 6221

Special Issue Editors


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Guest Editor
Large networks & complex systems, attlanTTic Research Center, Universidade de Vigo, 36310 Vigo, Spain
Interests: wireless communications; information theory; resource allocation; distributed optimization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal
Interests: IoT; wireless and mobile networks; network and system security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Device-to-device (D2D) communications operating within cellular networks are among the enabling technologies for 5G systems and many of their applications. Their advantages include enhanced spectral efficiency, better resource utilization, reduced power consumption, and decentralized control. In parallel, the expected widespread deployment of sensing devices in infrastructures, smart cities, vehicle-to-everything, and other cyberphysical systems in the coming years arises as one of the areas where D2D is likely to play a role in reducing the latency of communications and enabling massive machine-type communications or the realization of tactile Internet. Intelligent interference coordination and resource allocation are the main challenges in D2D, related to coexistence with traditional cellular wireless and other communication networks. However, the emergence of novel network architectures (e.g., cell-less) and innovative techniques for adapting the wireless medium demand new approaches for embedding D2D into these emerging wireless connectivity environments. In order to cope with this diversity of use cases and requirements, devices in a D2D system will have to apply novel and advanced solutions to dynamically monitor the medium and the network state, while efficiently using the available resources at any moment, either for spectrum reuse, mitigation of interference, caching information, multiple access, selection of its peer device(s), or switching its communication mode.

This Special Issue solicits the submission of high-quality and unpublished papers from academia and industry that aim to solve open technical problems or challenges in the context of D2D communications for cellular 5G+ networks and for cell-less architectures. Original and innovative contributions on all aspects, both theoretical and experimental, are welcomed.

Topics of interest include but are not limited to:

  • Dynamic spectrum and cognitive techniques for D2D communication;
  • Software-defined networks (SDN) and software-defined radio (SDR) for D2D communications;
  • Orthogonal and non-orthogonal multiple access (NOMA) for D2D;
  • D2D communications for mMTC and URLLC;
  • Performance evaluation of D2D communications;
  • Energy efficiency, interference and power control;
  • Cache-aided protocols and policies for D2D systems;
  • Multicast D2D (MD2D);
  • Relay-assisted D2D and MD2D;
  • Security and privacy issues in D2D;
  • Integrated D2D communication techniques for 5G networks;
  • D2D and MD2D for vehicular communications and vehicle-to-everything (V2X) communications;
  • Deep and reinforcement learning for D2D;
  • D2D testbeds, prototypes, and implementations;
  • D2D and fog/edge network architectures.

Dr. Manuel Fernández-Veiga
Dr. Pedro Pinto
Guest Editors

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Keywords

  • Device-to-device communications
  • Interference coordination
  • Resource allocation
  • Vehicle-to-anything (V2X)
  • Infrastructure-less networks

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Published Papers (1 paper)

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16 pages, 923 KiB  
Article
Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks
by Sherief Hashima, Basem M. ElHalawany, Kohei Hatano, Kaishun Wu and Ehab Mahmoud Mohamed
Electronics 2021, 10(2), 169; https://doi.org/10.3390/electronics10020169 - 14 Jan 2021
Cited by 30 | Viewed by 5208
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue D2D Communications for 5G and Beyond)
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