2021 55th Asilomar Conference on Signals, Systems, and Computers 2021
DOI: 10.1109/ieeeconf53345.2021.9723321
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Team Precoding Towards Scalable Cell-free Massive MIMO Networks

Abstract: In a recent work, we studied a novel precoding design for cell-free networks called team minimum mean-square error (TMMSE) precoding, which rigorously generalizes centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSI). Despite its flexibility in handling different cooperation regimes at the CSI sharing level, TMMSE precoding assumes networkwide sharing of the data bearing signals, and hence it is inherently not scalable. In this work, inspired by rece… Show more

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Cited by 11 publications
(17 citation statements)
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References 20 publications
(69 reference statements)
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“…Popular examples are the distributed or centralized usercentric clustered models reviewed in [5], or the special case of cellular massive MIMO [10]. Since the focus of this article is on power control, we omit the details on such constraints, and refer to [24], [25] for details. In the following, we simply assume that {Ú k } k∈K are given, and that the expectations in the following matrices and vector exist:…”
Section: Applications To Cell-free Network a System Modelmentioning
confidence: 99%
“…Popular examples are the distributed or centralized usercentric clustered models reviewed in [5], or the special case of cellular massive MIMO [10]. Since the focus of this article is on power control, we omit the details on such constraints, and refer to [24], [25] for details. In the following, we simply assume that {Ú k } k∈K are given, and that the expectations in the following matrices and vector exist:…”
Section: Applications To Cell-free Network a System Modelmentioning
confidence: 99%
“…More specifically, scalable cell-free networks are expected to implement some type of user-centric rule [3], which allocates to each UE a cluster of serving APs. As shown in [11], this practical limitation can be modeled by setting H N l in (1) to the set {0 N (a.s.)} if AP l is not serving UE k. Considering both impairments, we remark that V k is a linear subspace of H N L .…”
Section: B Information Constraintsmentioning
confidence: 99%
“…The solution to (7), which can be interpreted as the best distributed approximation of a regularized zero-forcing beamformer, can be obtained via the recently developed team MMSE beamforming framework given by [10]. Although presented in the context of downlink beamforming with perfect message sharing, the method in [10] directly applies to the uplink case and to user-centric clustering [11]. This method states that the solution to (7) corresponds to the unique solution to a linear feasibility problem, which, depending on the CSI structure, can be solved explicitly or approximately via efficient numerical techniques.…”
Section: Team Mmse Beamformingmentioning
confidence: 99%
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