Publication: Wireless 6G connectivity for massive number of devices and critical services
dc.contributor.coauthor | Kalor, Anders E. | |
dc.contributor.coauthor | Durisi, Giuseppe | |
dc.contributor.coauthor | Parkvall, Stefan | |
dc.contributor.coauthor | Yu, Wei | |
dc.contributor.coauthor | Mueller, Andreas | |
dc.contributor.coauthor | Popovski, Petar | |
dc.contributor.department | Department of Electrical and Electronics Engineering | |
dc.contributor.kuauthor | Ergen, Sinem Çöleri | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.date.accessioned | 2025-03-06T21:00:07Z | |
dc.date.issued | 2024 | |
dc.description.abstract | Compared to the generations up to 4G, whose main focus was on broadband and coverage aspects, 5G has expanded the scope of wireless cellular systems toward embracing two new types of connectivity: massive machine-type communications (mMTCs) and ultrareliable low-latency communications (URLLCs). This article discusses the possible evolution of these two types of connectivity within the umbrella of 6G wireless systems. This article consists of three parts. The first part deals with the connectivity for a massive number of devices. While mMTC research in 5G predominantly focuses on the problem of uncoordinated access in the uplink for a large number of devices, the traffic patterns in 6G may become more symmetric, leading to closed-loop massive connectivity. One of the drivers for this type of traffic pattern is distributed/decentralized learning and inference. The second part of this article discusses the evolution of wireless connectivity for critical services. While latency and reliability are tightly coupled in 5G, 6G will support a variety of safety-critical control applications with different types of timing requirements, as evidenced by the emergence of metrics related to information freshness and information value. In addition, ensuring ultrahigh reliability for safety-critical control applications requires modeling and estimation of the tail statistics of the wireless channel, queue length, and delay. The fulfillment of these stringent requirements calls for the development of novel artificial intelligence (AI)-based techniques, incorporating optimization theory, explainable AI (XAI), generative AI, and digital twins (DTs). The third part analyzes the coexistence of massive connectivity and critical services. Specifically, we consider scenarios in which a massive number of devices need to support traffic patterns of mixed criticality. This is followed by a discussion about the management of wireless resources shared by services with different criticality. | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | TÜBİTAK | |
dc.description.sponsorship | The work of Anders E. Kalor was supported by the Independent Research Fund Denmark (IRFD) under Grant 1056-00006B. The work of Giuseppe Durisi was supported in part by the Swedish Research Council under Grant 2021-04970 and in part by the Swedish Foundation for Strategic Research. The work of Sinem Coleri was supported in part by the Scientific and Technological Research Council of Turkiye 2247-A National Leaders Research Grant 121C314 and in part by Ford Otosan. The work of Wei Yu was supported by the Natural Sciences and Engineering Research Council (NSERC) through the Canada Research Chairs Program and the Discovery Grant. The work of Petar Popovski was supported by the Velux Foundation, Denmark, through the Villum Investigator Grant "WATER." | |
dc.identifier.doi | 10.1109/JPROC.2024.3484529 | |
dc.identifier.eissn | 1558-2256 | |
dc.identifier.grantno | Independent Research Fund Denmark (IRFD) [1056-00006B];Swedish Research Council [2021-04970];Swedish Foundation for Strategic Research;Scientific and Technological Research Council of Turkiye 2247-A National Leaders Research Grant [121C314];Ford Otosan;Natural Sciences and Engineering Research Council (NSERC);Velux Foundation, Denmark;Swedish Research Council [2021-04970] Funding Source: Swedish Research Council | |
dc.identifier.issn | 0018-9219 | |
dc.identifier.quartile | Q1 | |
dc.identifier.scopus | 2-s2.0-85209066196 | |
dc.identifier.uri | https://doi.org/10.1109/JPROC.2024.3484529 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/27847 | |
dc.identifier.wos | 1351537200001 | |
dc.keywords | 6G mobile communication | |
dc.keywords | 5G mobile communication | |
dc.keywords | Wireless communication | |
dc.keywords | Internet of Things | |
dc.keywords | Ultra reliable low latency communication | |
dc.keywords | Reliability | |
dc.keywords | Wireless sensor networks | |
dc.keywords | Sensors | |
dc.keywords | Artificial intelligence | |
dc.keywords | Traffic control | |
dc.keywords | 6G | |
dc.keywords | Internet of Things (IoT) | |
dc.keywords | Machine-type communications (MTCs) | |
dc.keywords | Massive access | |
dc.keywords | Massive connectivity | |
dc.keywords | Ultrareliable low-latency communications (URLLC) | |
dc.keywords | Wireless networks | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
dc.relation.ispartof | Proceedings of the IEEE | |
dc.subject | Engineering, electrical and electronic | |
dc.title | Wireless 6G connectivity for massive number of devices and critical services | |
dc.type | Journal Article | |
dc.type.other | Early access | |
dspace.entity.type | Publication | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Electrical and Electronics Engineering | |
relation.isOrgUnitOfPublication | 21598063-a7c5-420d-91ba-0cc9b2db0ea0 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 21598063-a7c5-420d-91ba-0cc9b2db0ea0 | |
relation.isParentOrgUnitOfPublication | 8e756b23-2d4a-4ce8-b1b3-62c794a8c164 | |
relation.isParentOrgUnitOfPublication.latestForDiscovery | 8e756b23-2d4a-4ce8-b1b3-62c794a8c164 |
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