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Team MMSE Precoding With Applications to Cell-Free Massive MIMO
EURECOM, Dept Commun Syst, F-06904 Sophia Antipolis, France.;Heinrich Hertz Inst Nachrichtentech Berlin GmbH, Fraunhofer Inst Telecommun, D-10587 Berlin, Germany.;Tech Univ Berlin, Dept Telecommun Syst, D-10587 Berlin, Germany..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0002-5954-434x
EURECOM, Dept Commun Syst, F-06904 Sophia Antipolis, France..
2022 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 21, no 8, p. 6242-6255Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. Vol. 21, no 8, p. 6242-6255
Keywords [en]
Precoding, Massive MIMO, Wireless communication, Interference, Distributed databases, Mathematical models, Wireless networks, Cell-free massive MIMO, radio stripes, distributed processing, team minimum mean-square error (TMMSE), team theory
National Category
Applied Mechanics Telecommunications Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-317014DOI: 10.1109/TWC.2022.3147895ISI: 000841840300040Scopus ID: 2-s2.0-85124746020OAI: oai:DiVA.org:kth-317014DiVA, id: diva2:1693171
Note

QC 20220906

Available from: 2022-09-06 Created: 2022-09-06 Last updated: 2022-09-06Bibliographically approved

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