AuthorsDe Alwis, Chamitha
AffiliationUniversity of Bedfordshire
University of Sri Jayewardenepura
Pusan National University
Munster Technological University
Uka Tarsadia University
University College Dublin
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AbstractWhile 5G is at the early deployment state around the globe, the research and industrial communities have already started concentrating their efforts on formulating the overall 6G vision comprising requirements, key enabling technologies, performance indicators, and applications. Following the trend, it is evident that 6G will emerge as highly softwarized and open networks allowing the participation of multiple stakeholders. This undoubtedly will make 6G more flexible, agile, autonomous, intelligent, and cost-efficient networks. However, the programmability and openness will make 6G networks more prone to issues like security, privacy, traceability, interoperability, auditability, resource manageability, spectrum efficiency, and 3D mobility. To address these issues, a deep integration of blockchain technology with 6G networks is foreseen. Thus, we aim to put together blockchain and 6G under a magnifying lens to gain a comprehensive understanding of the role of blockchain in the 6G ecosystem. We begin by providing an overview of the envisioned 6G networks and blockchain technology. Next, we present a high-level view of the role of blockchain for 6G trends and requirements. Following that, we conduct an in-depth study on how the blockchain can provide a secure, transparent, and decentralized underpinning to various technical aspects and use cases of 6G. Thereafter, we discuss the deployment challenges to be faced while integrating blockchain in 6G and the possible solutions. Finally, future research directions are expounded to set the floor for further advancements in the blockchainized 6G.
CitationDe Alwis C, Kumar P, Pham QV, Dev K, Kalla A, Liyanage M, Hwang WJ (2022) 'Towards 6G: key technological directions', Elsevier ICT Express, 9 (4), pp.525-533.
JournalElsevier ICT Express
SponsorsThis work was supported in part by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIT) under Grant NRF-2019R1C1C1006143 and Grant NRF-2019R1I1A3A01060518; in part by BK21 Four, Korean Southeast Center for the 4th Industrial Revolution Leader Education; and in part by the Institute of Information & Communications Technology Planning & Evaluation (IITP) Grant funded by the Korea Government (MSIT) under Grant 2020-0- 01450 (Artificial Intelligence Convergence Research Center [Pusan National University]).
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