Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers

Handle URI:
http://hdl.handle.net/10754/622091
Title:
Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers
Authors:
Sifaou, Houssem ( 0000-0003-0630-7073 ) ; Kammoun, Abla ( 0000-0002-0195-3159 ) ; Sanguinetti, Luca; Debbah, Merouane; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
This work focuses on the downlink and uplink of large-scale single-cell MU-MIMO systems in which the base station (BS) endowed with M antennas communicates with K single-antenna user equipments (UEs). Particularly, we aim at reducing the complexity of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio subject to a given power constraint. To this end, we consider the asymptotic regime in which M and K grow large with a given ratio. Tools from random matrix theory (RMT) are then used to compute, in closed form, accurate approximations for the parameters of the optimal precoder and receiver, when imperfect channel state information (modeled by the generic Gauss-Markov formulation form) is available at the BS. The asymptotic analysis allows us to derive the asymptotically optimal linear precoder and receiver that are characterized by a lower complexity (due to the dependence on the large scale components of the channel) and, possibly, by a better resilience to imperfect channel state information. However, the implementation of both is still challenging as it 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 on a per- UE basis that asymptotically solve the max-min SINR problem. Numerical results are used to validate the asymptotic analysis in the finite system regime and to show that the proposed TPE transceivers efficiently mimic the optimal ones, while requiring much lower computational complexity.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Sifaou H, Kammoun A, Sanguinetti L, Debbah M, Alouini M (2016) Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers. IEEE Transactions on Signal Processing: 1–1. Available: http://dx.doi.org/10.1109/TSP.2016.2645518.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Signal Processing
Issue Date:
28-Dec-2016
DOI:
10.1109/TSP.2016.2645518
Type:
Article
ISSN:
1053-587X; 1941-0476
Sponsors:
The research of L. Sanguinetti and M. Debbah has been supported by the ERC Starting Grant 305123 MORE. The work of H. Sifaou, A. Kammoun, and M. -S. Alouini was supported by the Qatar National Research Fund (a member of Qatar Foundation) under NPRP Grant NPRP 6-001-2-001 . The statements made herein are solely the responsibility of the authors.
Additional Links:
http://ieeexplore.ieee.org/document/7801160/
Appears in Collections:
Articles; 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, Merouaneen
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2016-12-29T13:20:21Z-
dc.date.available2016-12-29T13:20:21Z-
dc.date.issued2016-12-28en
dc.identifier.citationSifaou H, Kammoun A, Sanguinetti L, Debbah M, Alouini M (2016) Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers. IEEE Transactions on Signal Processing: 1–1. Available: http://dx.doi.org/10.1109/TSP.2016.2645518.en
dc.identifier.issn1053-587Xen
dc.identifier.issn1941-0476en
dc.identifier.doi10.1109/TSP.2016.2645518en
dc.identifier.urihttp://hdl.handle.net/10754/622091-
dc.description.abstractThis work focuses on the downlink and uplink of large-scale single-cell MU-MIMO systems in which the base station (BS) endowed with M antennas communicates with K single-antenna user equipments (UEs). Particularly, we aim at reducing the complexity of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio subject to a given power constraint. To this end, we consider the asymptotic regime in which M and K grow large with a given ratio. Tools from random matrix theory (RMT) are then used to compute, in closed form, accurate approximations for the parameters of the optimal precoder and receiver, when imperfect channel state information (modeled by the generic Gauss-Markov formulation form) is available at the BS. The asymptotic analysis allows us to derive the asymptotically optimal linear precoder and receiver that are characterized by a lower complexity (due to the dependence on the large scale components of the channel) and, possibly, by a better resilience to imperfect channel state information. However, the implementation of both is still challenging as it 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 on a per- UE basis that asymptotically solve the max-min SINR problem. Numerical results are used to validate the asymptotic analysis in the finite system regime and to show that the proposed TPE transceivers efficiently mimic the optimal ones, while requiring much lower computational complexity.en
dc.description.sponsorshipThe research of L. Sanguinetti and M. Debbah has been supported by the ERC Starting Grant 305123 MORE. The work of H. Sifaou, A. Kammoun, and M. -S. Alouini was supported by the Qatar National Research Fund (a member of Qatar Foundation) under NPRP Grant NPRP 6-001-2-001 . The statements made herein are solely the responsibility of the authors.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7801160/en
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleMax-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceiversen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Transactions on Signal Processingen
dc.eprint.versionPost-printen
dc.contributor.institutionUniversity of Pisa, Dipartimento di Ingegneria dell’Informazione, Italyen
dc.contributor.institutionLarge Systems and Networks Group (LANEAS), CentraleSupelec, Universite Paris- Saclay, 3 rue Joliot-Curie, 91192 Gif-sur-Yvette, Franceen
dc.contributor.institutionMathematical and Algorithmic Sciences Lab, Huawei Technologies Co. Ltd., Franceen
kaust.authorSifaou, Houssemen
kaust.authorKammoun, Ablaen
kaust.authorAlouini, Mohamed-Slimen
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