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An Assessment of Receiver Algorithms for Distributed Massive MIMO Systems

2024-04-19Artigo científico Acesso aberto
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dc.contributor.authorGashtasbi, Ali
dc.contributor.authorMarques da Silva, Mário
dc.contributor.authorDinis, Rui
dc.contributor.institutionDEE - Departamento de Engenharia Electrotécnica e de Computadores
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2024-09-23T22:21:38Z
dc.date.available2024-09-23T22:21:38Z
dc.date.issued2024-04-19
dc.descriptionFunding Information: This work is funded by FCT/MCTES through national funds and when applicable co-funded by EU funds under the projects UIDB/EEA/50008/2020 and 2022.03897. PTDC. Funding Information: We acknowledge the support of FCT/MCTES, as described above under \u201CFunding\u201D. We also acknowledge the support of Autonoma TechLab for providing an interesting environment to carry out this research. Publisher Copyright: © 2024 by the authors.
dc.description.abstractThis study investigates receiver design solutions for distributed Massive Multiple Input Multiple Output (D-m MIMO) systems, taking into account parameters such as number of access points as well as concerns related to channel estimates that use single-carrier frequency-domain equalization (SC-FDE). A significant contribution of this research is the integration of Low-Density Parity-Check (LDPC) codes to simplify coding complexity and enhance communication efficiency. The research examines different receiver designs, such as spatial antenna correlation and sophisticated channel estimation methods. The authors propose integrating LDPC codes into the receiver architecture to simplify computations and enhance error correction and decoding. Moreover, the paper examines performance evaluation measures and approaches, highlighting the trade-offs among complexity, spectral efficiency, and error performance. The comparative analysis indicates the benefits, in terms of performance, of incorporating LDPC codes and improving system throughput and dependability. We examine four distinct receiver algorithms: zero-forcing (ZF), minimum mean square error (MMSE), maximum ratio combining (MRC), and equal gain combining (EGC). The study shows that MRC and EGC receivers work well in D-m MIMO because they make the receiver system less computationally demanding.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent14
dc.format.extent3172599
dc.identifier.doi10.3390/electronics13081560
dc.identifier.issn2079-9292
dc.identifier.otherPURE: 99762281
dc.identifier.otherPURE UUID: 71941b1c-e931-47bb-bb03-835fa6ab6a78
dc.identifier.otherScopus: 85191407874
dc.identifier.otherWOS: 001210259400001
dc.identifier.otherORCID: /0000-0002-8520-7267/work/168127833
dc.identifier.urihttp://hdl.handle.net/10362/172266
dc.identifier.urlhttps://www.scopus.com/pages/publications/85191407874
dc.language.isoeng
dc.peerreviewedyes
dc.subjectD-m MIMO
dc.subjectLDPC
dc.subjectreceiver
dc.subjectSC-FDE
dc.subjectControl and Systems Engineering
dc.subjectSignal Processing
dc.subjectHardware and Architecture
dc.subjectComputer Networks and Communications
dc.subjectElectrical and Electronic Engineering
dc.titleAn Assessment of Receiver Algorithms for Distributed Massive MIMO Systemsen
dc.title.subtitleInvestigating Design Solutions and Performanceen
dc.typejournal article
degois.publication.issue8
degois.publication.titleElectronics (Switzerland)
degois.publication.volume13
dspace.entity.typePublication
rcaap.rightsopenAccess

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