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Hardware Evaluation of Interference Alignment Algorithms Using USRPs for Beyond 5G Networks

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dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Comunicacioneses
dc.contributor.authorUrquiza Villalonga, David Alejandro
dc.contributor.authorLopez Barrios, Alejandro
dc.contributor.authorFernández-Getino García, María Julia
dc.contributor.funderEuropean Commissionen
dc.contributor.funderAgencia Estatal de Investigación (España)es
dc.date.accessioned2023-09-19T11:59:32Z
dc.date.available2023-09-19T11:59:32Z
dc.date.issued2023-07-06
dc.descriptionProceedings of the 20th IEEE Region 8 EUROCON Conference, EUROCON 2023, 6-8 July 2023, Turín, Italyen
dc.description.abstractNetwork densification is a key technology to achieve the spectral efficiency (SE) expected in 5G wireless networks and beyond. However, the proximity between transmitters and receivers increases the interference levels, becoming a major drawback. To overcome this problem, several interference management techniques have been proposed to increase the signal-to-interference-plus-noise ratio (SINR). Interference alignment (IA) algorithms have been extensively studied due to their capability to achieve optimal degrees of freedom (DoFs) in interference channels (ICs). Nevertheless, most of the works are limited to a purely theoretical analysis based on non-realistic assumptions such as perfect channel state information (CSI) and the synchronization of all nodes in the network. To the best of our knowledge, only a few articles address the IA implementation using reconfigurable hardware. To cover this lack, this paper proposes a practical design of the IA algorithm based on the SINR maximization, known as MAX-SINR, considering a multi-user IC. Each transmitter and receiver is implemented on the National Instruments USRP-2942. A practical solution for the channel estimation and synchronization stages in an IC, that are usually omitted in theoretical works, is developed. The performance of the proposed implementation is shown in terms of the SINR gain, SE, and bit error rate (BER). Unlike previous works, all the results are based on real measurements providing valuable insights into the performance of IA algorithms.en
dc.description.sponsorshipThis work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie ETN TeamUp5G, grant agreement No. 813391. Also, this work has been partially funded by the Spanish National project IRENE-EARTH (PID2020- 115323RB-C33 / AEI / 10.13039/501100011033)en
dc.format.extent6es
dc.identifier.bibliographicCitationUrquiza Villalonga, D. A., López Barrios, A., Fernández-Getino García, M. J. (2023). Hardware Evaluation of Interference Alignment Algorithms Using USRPs for Beyond 5G Networks [proceedings]. In Proceedings of the 20th IEEE Region 8 EUROCON Conference, EUROCON 2023, Torino, Italy.en
dc.identifier.doihttps://doi.org/10.1109/EUROCON56442.2023.10199035
dc.identifier.isbn978-1-6654-6397-3
dc.identifier.publicationfirstpage1es
dc.identifier.publicationlastpage6es
dc.identifier.publicationtitleProceedings of the 20th IEEE Region 8 EUROCON Conference, EUROCON 2023en
dc.identifier.urihttps://hdl.handle.net/10016/38380
dc.identifier.uxxiCC/0000034507
dc.language.isoengen
dc.publisherIEEEen
dc.relation.eventdate2023-07-06es
dc.relation.eventplaceItaliaes
dc.relation.eventtitleThe 20th IEEE Region 8 EUROCON Conference, EUROCON 2023en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/GA-813391es
dc.relation.projectIDGobierno de España. PID2020-115323RB-C33es
dc.rights© 2023, IEEEen
dc.rights.accessRightsopen accessen
dc.subject.ecienciaElectrónicaes
dc.subject.ecienciaIngeniería Industriales
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherInterference alignment (ia)en
dc.subject.otherMulti-user interference channels (ics)en
dc.subject.otherUniversal software radio peripheral (usrp)en
dc.titleHardware Evaluation of Interference Alignment Algorithms Using USRPs for Beyond 5G Networksen
dc.typeconference output*
dc.type.hasVersionAM*
dspace.entity.typePublication
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