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- W4386858086 abstract "Hybrid precoding in cell-free massive MIMO (CF-mMIMO) faces many challenges, e.g., large cascaded beamspace and high signaling overhead. In this letter, we propose a two-stage distributed beam selection for CF-mMIMO hybrid precoding. Each base station (BS) first learns an efficient beamspace compression with a deep neural network (DNN) from the local received signal strength indicator (RSSI), based on which good beam-selection labels are obtained with a proposed potential game algorithm. By learning the mapping from local RSSI to the corresponding label, a DenseNet-based online local beam selection can be realized at each BS. Simulations verify the effectiveness of our proposed scheme." @default.
- W4386858086 created "2023-09-20" @default.
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- W4386858086 date "2023-01-01" @default.
- W4386858086 modified "2023-09-29" @default.
- W4386858086 title "Intelligent Distributed Beam Selection for Cell-free Massive MIMO Hybrid Precoding" @default.
- W4386858086 doi "https://doi.org/10.1109/lcomm.2023.3317312" @default.
- W4386858086 hasPublicationYear "2023" @default.
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