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  4. Team MMSE Precoding With Applications to Cell-Free Massive MIMO
 
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2022
Journal Article
Titel

Team MMSE Precoding With Applications to Cell-Free Massive MIMO

Abstract
This article studies a novel distributed precoding design, coined team minimum mean-square error (TMMSE) precoding, which rigorously generalizes classical centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSIT). Building on the so-called theory of teams, we derive a set of necessary and sufficient conditions for optimal TMMSE precoding, in the form of an infinite dimensional linear system of equations. These optimality conditions are further specialized to cell-free massive MIMO networks, and explicitly solved for two important examples, i.e., the classical case of local CSIT and the case of unidirectional CSIT sharing along a serial fronthaul. The latter case is relevant, e.g., for the recently proposed radio stripe concept and the related advances on sequential processing exploiting serial connections. In both cases, our optimal design outperforms the heuristic methods that are known from the previous literature. Duality arguments and numerical simulations validate the effectiveness of the proposed team theoretical approach in terms of ergodic achievable rates under a sum-power constraint.
Author(s)
Miretti, Lorenzo
Department of Communication Systems, EURECOM, Sophia Antipolis, France
Bjornson, E.
The Royal Institute of Technology (KTH)
Gesbert, D.
EURECOM Ecole d'Ingénieur et Centre de Recherche en Sciences du Numérique
Zeitschrift
IEEE Transactions on Wireless Communications
Thumbnail Image
DOI
10.1109/TWC.2022.3147895
Language
English
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Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI
Tags
  • Cell-free massive MIM...

  • radio stripes

  • distributed processin...

  • precoding

  • team minimum mean-squ...

  • team theory

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