5G D2D Networks: Techniques, Challenges, and Future Prospects

By R. I. Ansari, Chrysostomos Chrysostomou, Syed Ali Hassan, Mohsen Guizani, Shahid Mumtaz, Jonathan Rodriguez, J. Rodrigues. IEEE Systems Journal, 2018

298 citations recorded by the source corpus.

The increasing number of mobile users has given impetus to the demand for high data rate proximity services. The fifth-generation (5G) wireless systems promise to improve the existing technology according to the future demands and provide a road map for reliable and resource-efficient solutions. Device-to-device (D2D) communication has been envisioned as an allied technology of 5G wireless systems for providing services that include live data and video sharing. A D2D communication technique opens new horizons of device-centric communications, i.e., exploiting direct D2D links instead of relying solely on cellular links. Offloading traffic from traditional network-centric entities to D2D network enables low computational complexity at the base station besides increasing the network capacity. However, there are several challenges associated with D2D communication. In this paper, we present a survey of the existing methodologies related to aspects such as interference management, network discovery, proximity services, and network security in D2D networks. We conclude by introducing new dimensions with regard to D2D communication and delineate aspects that require further research.

View Paper: https://www.semanticscholar.org/paper/f13dde51c2b9ba3db9b78c8a465fdb002ff3292b

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Citations in the corpus

Blockchain for 5G and Beyond Networks: A State of the Art Survey (2019, background): “D2D takes advantage of the proximity of device communication for efficient utilization of available resources, enabling to improve the overall system throughput, mitigate communication delays and reduce energy consumption and traffic load [133].”
Space-Air-Ground Integrated Network: A Survey (2018, background): “Recently, focusing on the challenging issues of D2D communication in 5G system including interference management, network discovery, network coding, and network security, lots of research works have been done, which can be found in the detailed surveys [178]–[180].”
Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open Challenges (2019, background): “the main BS and also improves the spectral efficiency as well as energy efficiency (EE) of the network [164].”