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Parallel signal detection for generalized spatial modulation MIMO systems

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Parallel signal detection for generalized spatial modulation MIMO systems

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dc.contributor.author García Mollá, Víctor Manuel es_ES
dc.contributor.author Simarro, M. Angeles es_ES
dc.contributor.author Martínez Zaldívar, Francisco José es_ES
dc.contributor.author Boratto, Murilo es_ES
dc.contributor.author Alonso-Jordá, Pedro es_ES
dc.contributor.author Gonzalez, Alberto es_ES
dc.date.accessioned 2022-10-28T10:28:57Z
dc.date.available 2022-10-28T10:28:57Z
dc.date.issued 2022-04 es_ES
dc.identifier.issn 0920-8542 es_ES
dc.identifier.uri http://hdl.handle.net/10251/188909
dc.description.abstract [EN] Generalized Spatial Modulation is a recently developed technique that is designed to enhance the efficiency of transmissions in MIMO Systems. However, the procedure for correctly retrieving the sent signal at the receiving end is quite demanding. Specifically, the computation of the maximum likelihood solution is computationally very expensive. In this paper, we propose a parallel method for the computation of the maximum likelihood solution using the parallel computing library OpenMP. The proposed parallel algorithm computes the maximum likelihood solution faster than the sequential version, and substantially reduces the worst-case computing times. es_ES
dc.description.sponsorship This work has been partially supported by the Spanish Ministry of Science, Innovation and Universities and by the European Union through grant RTI2018- 098085-BC41 (MCUI/AEI/FEDER), by GVA through PROMETEO/2019/109, and by RED 2018-102668-T. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof The Journal of Supercomputing es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject MIMO communications es_ES
dc.subject Maximum likelihood detection es_ES
dc.subject Parallel computing es_ES
dc.subject Generalized spatial modulation es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.title Parallel signal detection for generalized spatial modulation MIMO systems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11227-021-04163-y es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098085-B-C41/ES/DYNAMIC ACOUSTIC NETWORKS FOR CHANGING ENVIRONMENTS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MCIU//RED2018-102668-T/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//RTI2018-098085-B-C41//DYNAMIC ACOUSTIC NETWORKS FOR CHANGING ENVIRONMENTS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//PROMETEO%2F2019%2F109//COMUNICACION Y COMPUTACION INTELIGENTES Y SOCIALES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation García Mollá, VM.; Simarro, MA.; Martínez Zaldívar, FJ.; Boratto, M.; Alonso-Jordá, P.; Gonzalez, A. (2022). Parallel signal detection for generalized spatial modulation MIMO systems. The Journal of Supercomputing. 78(5):7059-7077. https://doi.org/10.1007/s11227-021-04163-y es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s11227-021-04163-y es_ES
dc.description.upvformatpinicio 7059 es_ES
dc.description.upvformatpfin 7077 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 78 es_ES
dc.description.issue 5 es_ES
dc.relation.pasarela S\451336 es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades es_ES
dc.description.references Telatar E (1999) Capacity of multi-antenna Gaussian channels. Eur Trans Telecommun 10(6):585–595. https://doi.org/10.1002/ett.4460100604 es_ES
dc.description.references Foschini G, Gans M (1998) On limits of wireless communications in a fading environment when using multiple antennas. Wireless Pers Commun 6(3):311–335. https://doi.org/10.1023/A:1008889222784 es_ES
dc.description.references Hassibi B, Vikalo H (2005) On Sphere Decoding algorithm. I Expected Complexity, IEEE Trans Signal Process 53:2806–2818 es_ES
dc.description.references Wolniansky P, Foschini G, Golden G, Valenzuela R (1998) V-BLAST: An Architecture for realizing very high data rates over the rich-scattering wireless channel. In: 1998 URSI International Symposium on Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167), pp. 295–300. https://doi.org/10.1109/ISSSE.1998.738086 es_ES
dc.description.references Li X-Y, Cao X (2005) Low complexity signal detection algorithm for MIMO-OFDM systems. Electron Lett 41:83–85 es_ES
dc.description.references Guo Z, Nilsson P (2006) Algorithm and implementation of the K-best Sphere decoding for MIMO detection. Select Areas Commun, IEEE J 24:491–503. https://doi.org/10.1109/JSAC.2005.862402 es_ES
dc.description.references Hassibi B (200) An efficient square-root algorithm for BLAST. In: 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), Vol. 2, 2000, pp. II737–II740 vol.2. https://doi.org/10.1109/ICASSP.2000.859065 es_ES
dc.description.references Agrell E, Eriksson T, Vardy A, Zeger K (2002) Closest point search in lattices. IEEE Trans Commun 48:2201–2214 es_ES
dc.description.references Schnorr C, Euchner M (1994) Lattice basis reduction: improved practical algorithms and solving subset sum problems. Math Program 48(66):181–191 es_ES
dc.description.references Fincke U, Pohst M (1985) Improved methods for calculating vectors of short length in a lattice, including a complexity analysis. Math Comput 44(170):463–471 es_ES
dc.description.references Wang J, Jia S, Song J (2012) Generalised spatial modulation system with multiple active transmit antennas and low complexity detection scheme. IEEE Trans Wireless Commun 11–4:1605–1615 es_ES
dc.description.references Di Renzo M, Haas H, Ghrayeb A, Sugiura S, Hanzo L (2014) Spatial modulation for generalized MIMO: challenges, opportunities, and implementation. Proc IEEE 102:56–103. https://doi.org/10.1109/JPROC.2013.2287851 es_ES
dc.description.references Patcharamaneepakorn P, Wu S, Wang C-X, Aggoune H, Alwakeel M, Ge X, Di Renzo M (2016) Spectral, energy, and economic efficiency of 5g multicell massive MIMO systems with generalized spatial modulation. IEEE Trans Veh Technol 65:11. https://doi.org/10.1109/TVT.2016.2526628 es_ES
dc.description.references Liu T, Chen C, Liu C (2019) Fast maximum likelihood detection of the generalized spatially modulated signals using successive sphere decoding algorithms. IEEE Commun Lett 23–4:656–659. https://doi.org/10.1109/LCOMM.2019.2898398 es_ES
dc.description.references OpenMP v 4.5 specification (2015). http://www.openmp.org/wp-content/uploads/openmp-4.5.pdf es_ES
dc.description.references Damen MO, Gamal HE, Caire G (2003) On maximum-likelihood detection and the search for the closest lattice point. IEEE Trans Inform Theor 49:2389–2402 es_ES
dc.description.references Kailath T, Vikalo H, Hassibi B (2006) MIMO receive algorithms, Cambridge University Press, p. 302–321. https://doi.org/10.1017/CBO9780511616815.016 es_ES
dc.description.references Barbero LG, Ratnarajah T, Cowan C (2008) A low-complexity soft-mimo detector based on the fixed-complexity sphere decoder. In: 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2669–2672. https://doi.org/10.1109/ICASSP.2008.4518198 es_ES
dc.description.references Garcia-Molla VM, Vidal A, Gonzalez A, Roger S (2014) Improved maximum likelihood detection through sphere decoding combined with box optimization. Signal Processing, Elsevier 98:287–294 es_ES
dc.description.references Altin G, Çelebi M (2018) A simple low-complexity algorithm for generalized spatial modulation. AEU-Int J Electron C 97:63–67 es_ES
dc.description.references MATLAB, (R2018b), The MathWorks Inc., Natick, Massachusetts, 2018 es_ES


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