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Optimal linear precoding in multi-user MIMO systems: A large system analysis
KTH, School of Electrical Engineering (EES), Signal Processing. Ecole Supérieure d'Électricité (Supélec), France; Linköping University, Sweden .
2014 (English)In: 2014 IEEE Global Communications Conference, GLOBECOM 2014, 2014, 3922-3927 p.Conference paper (Refereed)
Abstract [en]

We consider the downlink of a single-cell multi-user MIMO system in which the base station makes use of N antennas to communicate with K single-antenna user equipments (UEs) randomly positioned in the coverage area. In particular, we focus on the problem of designing the optimal linear precoding for minimizing the total power consumption while satisfying a set of target signal-to-interference-plus-noise ratios (SINRs). To gain insights into the structure of the optimal solution and reduce the computational complexity for its evaluation, we analyze the asymptotic regime where N and K grow large with a given ratio and make use of recent results from large system analysis to compute the asymptotic solution. Then, we concentrate on the asymptotically design of heuristic linear precoding techniques. Interestingly, it turns out that the regularized zero-forcing (RZF) precoder is equivalent to the optimal one when the ratio between the SINR requirement and the average channel attenuation is the same for all UEs. If this condition does not hold true but only the same SINR constraint is imposed for all UEs, then the RZF can be modified to still achieve optimality if statistical information of the UE positions is available at the BS. Numerical results are used to evaluate the performance gap in the finite system regime and to make comparisons among the precoding techniques.

Place, publisher, year, edition, pages
2014. 3922-3927 p.
Keyword [en]
Antennas, Beamforming, MIMO systems, Signal interference, Signal to noise ratio, Spurious signal noise, Structural optimization, Systems analysis, Telecommunication links, Asymptotic regimes, Asymptotic solutions, Channel attenuation, Large system analysis, Linear pre-coding, Multi-user MIMO systems, Statistical information, Total power consumption, Optimization
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-167495DOI: 10.1109/GLOCOM.2014.7037420ScopusID: 2-s2.0-84924368078ISBN: 9781479935116OAI: diva2:820648
2014 IEEE Global Communications Conference, GLOBECOM 2014, 8 December 2014 through 12 December 2014

QC 20150612

Available from: 2015-06-12 Created: 2015-05-22 Last updated: 2015-06-12Bibliographically approved

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