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dc.contributor.authorMueller, Axel
dc.contributor.authorKammoun, Abla
dc.contributor.authorBjörnson, Emil
dc.contributor.authorDebbah, Mérouane
dc.date.accessioned2016-03-13T13:59:36Z
dc.date.available2016-03-13T13:59:36Z
dc.date.issued2016-02-29
dc.identifier.citationLinear precoding based on polynomial expansion: reducing complexity in massive MIMO 2016, 2016 (1) EURASIP Journal on Wireless Communications and Networking
dc.identifier.issn1687-1499
dc.identifier.doi10.1186/s13638-016-0546-z
dc.identifier.urihttp://hdl.handle.net/10754/601296
dc.description.abstractMassive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively “antenna-efficient” regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.
dc.description.sponsorshipThis research has been supported by the ERC Starting Grant 305123 MORE (Advanced Mathematical Tools for Complex Network Engineering). Parts of the results were previously presented at the 8th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2014. E. Björnson is funded by the International Postdoc Grant 2012-228 from the Swedish Research Council.
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.urlhttp://jwcn.eurasipjournals.com/content/2016/1/63
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
dc.subjectMassive MIMO
dc.subjectLinear precoding
dc.subjectMultiuser systems
dc.subjectPolynomial expansion
dc.subjectRandom matrix theory
dc.titleLinear precoding based on polynomial expansion: reducing complexity in massive MIMO
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalEURASIP Journal on Wireless Communications and Networking
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionMathematical and Algorithmic Sciences Lab, France Research Center, Huawei Technologies Co. Ltd., Arcs de Seine Bâtiment A, 20 Quai du Point du Jour, 92100 Boulogne-Billancourt, France
dc.contributor.institutionAlcatel-Lucent on Flexible Radio, SUPELEC, Plateau de Moulon, 3 Rue Joliot Curie, 91190 Gif-sur-Yvette, France
dc.contributor.institutionLinköping University, Department of Electrical Engineering, SE-581 83 Linköping, Sweden
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personKammoun, Abla
refterms.dateFOA2018-06-14T07:48:46Z
dc.date.published-online2016-02-29
dc.date.published-print2016-12


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