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Traffic Scheduling and Resource Allocation for Heterogeneous Services in 5G New Radio Networks: A Scoping Review

datacite.subject.fosEngenharia e Tecnologia
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorPindi, Ntunitangua René
dc.contributor.authorVelez, Fernando J.
dc.date.accessioned2025-10-13T10:31:32Z
dc.date.available2025-10-13T10:31:32Z
dc.date.issued2025-10-10
dc.description.abstractThe rapid evolution of 5G New Radio networks has introduced a wide range of services with diverse requirements, complicating their coexistence within the shared radio spectrum and posing challenges in traffic scheduling and resource allocation. This study aims to analyze and categorize the methods, approaches, and techniques proposed to ensure efficient joint and dynamic packet scheduling and resource allocation among heterogeneous services—namely eMBB, URLLC, and mMTC—in 5G and beyond, with a focus on Quality of Service and user satisfaction. This scoping review draws from publications indexed in IEEE Xplore and Scopus and synthesizes the most relevant evidence related to packet scheduling across heterogeneous services, highlighting key approaches, core performance metrics, and emerging trends. Following the PRISMA-ScR methodology, 48 out of an initial 140 articles were included for explicitly addressing coexistence, scheduling, and resource allocation. The findings reveal a research emphasis on eMBB and URLLC coexistence, while integration with mMTC remains underexplored. Moreover, the evidence suggests that hybrid and deep learning-based approaches are particularly promising for tackling coexistence and resource management challenges in future mobile networks.por
dc.description.sponsorshipCOST Action CA20120 INTERACT—Intelligence-Enabling Radio Communications for Seamless Inclusive Interaction; INAGBE (support provided through the doctoral scholarship for faculty staff, awarded via the Instituto Superior Politécnico de Ndalatando, ISPNd)
dc.identifier.citationNtunitangua René Pindi and Fernando J. Velez, “Traffic Scheduling and Resource Allocation for Heterogeneous Services in 5G New Radio Networks: A Scoping Review,” Smart Cities, vol. 8, no. 5, Oct. 2025, pp. 168-168, doi: 10.3390/smartcities8050168.
dc.identifier.doi10.3390/smartcities8050168
dc.identifier.eissn2624-6511
dc.identifier.urihttp://hdl.handle.net/10400.6/18955
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationInstituto de Telecomunicações
dc.relation.hasversionhttps://www.mdpi.com/2624-6511/8/5/168
dc.relation.ispartofseriesSpecial Issue Architectures, Protocols and Algorithms of Sensor Networks—Second Edition; Internet of Things
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/
dc.subjectframe scheduling
dc.subjectcoexistence
dc.subjecteMBB
dc.subjectURLLC
dc.subjectmMTC
dc.subject5G
dc.titleTraffic Scheduling and Resource Allocation for Heterogeneous Services in 5G New Radio Networks: A Scoping Reviewpor
dc.typeresearch article
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50008%2F2013/PT
oaire.citation.endPage32
oaire.citation.issue5
oaire.citation.startPage1
oaire.citation.titleSmart Cities
oaire.citation.volume8
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNamePindi
person.familyNameVelez
person.givenNameNtunitangua René
person.givenNameFernando J.
person.identifier.ciencia-id1510-E247-C9DB
person.identifier.orcid0000-0003-3494-5179
person.identifier.orcid0000-0001-9680-123X
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication251ff689-de09-4dce-b601-cfe56cbfc5ee
relation.isAuthorOfPublicationeb831c87-4af4-4978-ba42-43d4d55dbe1f
relation.isAuthorOfPublication.latestForDiscoveryeb831c87-4af4-4978-ba42-43d4d55dbe1f
relation.isProjectOfPublication7918ee4a-2bcc-42d4-8ea8-7233682ef215
relation.isProjectOfPublication.latestForDiscovery7918ee4a-2bcc-42d4-8ea8-7233682ef215

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