Max-min SINR low complexity transceiver design for single cell massive MIMO

Handle URI:
http://hdl.handle.net/10754/622656
Title:
Max-min SINR low complexity transceiver design for single cell massive MIMO
Authors:
Sifaou, Houssem ( 0000-0003-0630-7073 ) ; Kammoun, Abla ( 0000-0002-0195-3159 ) ; Sanguinetti, Luca; Debbah, Mérouane; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
This work focuses on large scale multi-user MIMO systems in which the base station (BS) outfitted with M antennas communicates with K single antenna user equipments (UEs). In particular, we aim at designing the linear precoder and receiver that maximizes the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. To gain insights into the structure of the optimal precoder and receiver as well as to reduce the computational complexity for their implementation, we analyze the asymptotic regime where M and K grow large with a given ratio and make use of random matrix theory (RMT) tools to compute accurate approximations. Although simpler, the implementation of the asymptotic precoder and receiver requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each UE and make use of RMT to determine the optimal weighting coefficients that asymptotically solve the max-min SINR problem. Numerical results are used to show that the proposed TPE-based precoder and receiver almost achieve the same performance as the optimal ones while requiring a lower complexity.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Sifaou H, Kammoun A, Sanguinetti L, Debbah M, Alouini M-S (2016) Max-min SINR low complexity transceiver design for single cell massive MIMO. 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Available: http://dx.doi.org/10.1109/SPAWC.2016.7536729.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Conference/Event name:
17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016
Issue Date:
11-Aug-2016
DOI:
10.1109/SPAWC.2016.7536729
Type:
Conference Paper
Sponsors:
L. Sanguinetti and M. Debbah were supported by the ERC Starting Grant 305123 MORE. This research was also partially supported by the research project 5GIOTTO funded by the University of Pisa
Additional Links:
http://ieeexplore.ieee.org/document/7536729/
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorSifaou, Houssemen
dc.contributor.authorKammoun, Ablaen
dc.contributor.authorSanguinetti, Lucaen
dc.contributor.authorDebbah, Mérouaneen
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2017-01-09T11:52:21Z-
dc.date.available2017-01-09T11:52:21Z-
dc.date.issued2016-08-11en
dc.identifier.citationSifaou H, Kammoun A, Sanguinetti L, Debbah M, Alouini M-S (2016) Max-min SINR low complexity transceiver design for single cell massive MIMO. 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Available: http://dx.doi.org/10.1109/SPAWC.2016.7536729.en
dc.identifier.doi10.1109/SPAWC.2016.7536729en
dc.identifier.urihttp://hdl.handle.net/10754/622656-
dc.description.abstractThis work focuses on large scale multi-user MIMO systems in which the base station (BS) outfitted with M antennas communicates with K single antenna user equipments (UEs). In particular, we aim at designing the linear precoder and receiver that maximizes the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. To gain insights into the structure of the optimal precoder and receiver as well as to reduce the computational complexity for their implementation, we analyze the asymptotic regime where M and K grow large with a given ratio and make use of random matrix theory (RMT) tools to compute accurate approximations. Although simpler, the implementation of the asymptotic precoder and receiver requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each UE and make use of RMT to determine the optimal weighting coefficients that asymptotically solve the max-min SINR problem. Numerical results are used to show that the proposed TPE-based precoder and receiver almost achieve the same performance as the optimal ones while requiring a lower complexity.en
dc.description.sponsorshipL. Sanguinetti and M. Debbah were supported by the ERC Starting Grant 305123 MORE. This research was also partially supported by the research project 5GIOTTO funded by the University of Pisaen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7536729/en
dc.subjectlinear transceiversen
dc.subjectlow complexityen
dc.subjectMassive MIMO systemsen
dc.subjectrandom matrix theoryen
dc.subjecttruncated polynomial expansionen
dc.titleMax-min SINR low complexity transceiver design for single cell massive MIMOen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)en
dc.conference.date2016-07-03 to 2016-07-06en
dc.conference.name17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016en
dc.conference.locationEdinburgh, GBRen
dc.contributor.institutionDipartimento di Ingegneria dell'Informazione, University of Pisa, Italyen
dc.contributor.institutionLarge Networks and System Group (LANEAS), CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, Franceen
dc.contributor.institutionMathematical and Algorithmic Sciences Lab, Huawei France RandD, Paris, Franceen
kaust.authorSifaou, Houssemen
kaust.authorKammoun, Ablaen
kaust.authorAlouini, Mohamed-Slimen
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