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Subgroup-Centric Multicast Cell-Free Massive MIMO

dc.contributor.authorde la Fuente, Alejandro
dc.contributor.authorFemenias, Guillem
dc.contributor.authorRiera-Palou, Felip
dc.contributor.authorInterdonato, Giovanni
dc.date.accessioned2024-10-30T15:59:57Z
dc.date.available2024-10-30T15:59:57Z
dc.date.issued2024-10-29
dc.identifier.citationA. D. L. Fuente, G. Femenias, F. Riera-Palou and G. Interdonato, "Subgroup-Centric Multicast Cell-Free Massive MIMO," in IEEE Open Journal of the Communications Society, doi: 10.1109/OJCOMS.2024.3487912. keywords: {Precoding;Unicast;Multicast communication;Channel estimation;6G mobile communication;Spectral efficiency;Resource management;Reliability;Massive MIMO;Internet of Things;Cell-free massive MIMO;multicasting;user subgrouping;scalability},es
dc.identifier.issn2644-125X (online)
dc.identifier.urihttps://hdl.handle.net/10115/40899
dc.description.abstractCell-free massive multiple-input multiple-output (CF-mMIMO) is an emerging technology for beyond fifth-generation (5G) systems aimed at enhancing the energy and spectral efficiencies of future mobile networks while providing nearly uniform quality of service to all users. Moreover, multicasting has garnered increasing attention in recent years, as physical-layer multicasting proves to be an efficient approach for serving multiple users simultaneously, all with identical service demands while sharing radio resources. A multicast service is typically delivered using either unicast or a single multicast transmission. In contrast, this work introduces a subgroup-centric multicast CF-mMIMO framework that splits the users into several multicast subgroups. The subgroup creation is based on the similarities in the spatial channel characteristics of the multicast users. This framework benefits from efficiently sharing the pilot sequence used for channel estimation and the precoding filters used for data transmission. The proposed framework relies on two scalable precoding strategies, namely, the centralized improved partial MMSE (IP-MMSE) and the distributed conjugate beamforming (CB). Numerical results demonstrate that the centralized IP-MMSE precoding strategy outperforms the CB precoding scheme in terms of sum SE when multicast users are uniformly distributed across the service area. In contrast, in cases where users are spatially clustered, multicast subgrouping significantly enhances the sum spectral efficiency (SE) of the multicast service compared to both unicast and single multicast transmission. Interestingly, in the latter scenario, distributed CB precoding outperforms IP-MMSE, particularly in terms of per-user SE, making it the best solution for delivering multicast content. Heterogeneous scenarios that combine uniform and clustered distributions of users validate multicast subgrouping as the most effective solution for improving both the sum and per-user SE of a multicast CF-mMIMO service.es
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineerses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectcell-free massive MIMOes
dc.subjectmulticastinges
dc.subjectuser subgroupinges
dc.subjectscalabityes
dc.titleSubgroup-Centric Multicast Cell-Free Massive MIMOes
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1109/OJCOMS.2024.3487912es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses


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Attribution-NonCommercial-NoDerivatives 4.0 InternacionalExcept where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional